Urban-Rural Disparities in the Prevalence, Awareness, Treatment, and Control of Hypertension among Adult Diabetic Patients in Northern State, Sudan: A cross sectional Analytical Community-based Study, 2026

Urban-Rural Disparities in the Prevalence, Awareness, Treatment, and Control of Hypertension among Adult Diabetic Patients in Northern State, Sudan: A cross sectional Analytical Community-based Study, 2026 | 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 Urban-Rural Disparities in the Prevalence, Awareness, Treatment, and Control of Hypertension among Adult Diabetic Patients in Northern State, Sudan: A cross sectional Analytical Community-based Study, 2026 Al-Mowafag Anwer Omer, Mohamed Osman Abdelaziz, Roaa Ebrahim Bashir, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9173542/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Diabetes and hypertension constitute a dual public health burden, particularly in low-income countries. While urban-rural disparities in healthcare access are well documented, this study aims to compare the prevalence, awareness, treatment, and control of hypertension among adult diabetic patients in rural and urban areas of Northern State, Sudan, in 2026. Methods A community-based analytical cross-sectional study was conducted among 595 diabetic adults (320 urban, 275 rural) selected via multi-stage stratified random sampling. Data were collected using interviewer-administered questionnaires and clinical measurements following standardized protocols. Hypertension was defined as systolic blood pressure ≥ 140 mmHg and/or diastolic ≥ 90 mmHg, or current antihypertensive medication use. Results The overall prevalence of hypertension was 67.4% (401/595), comprising 42.8% previously diagnosed and 24.5% newly discovered cases. Contrary to expectations, no significant urban-rural differences were observed across all measured parameters: hypertension prevalence of previously diagnosed (42.9% vs. 42.8%, p = 0.964), awareness (62.1% vs. 64.9%, p = 0.959), treatment adherence (86.4% vs. 86.1%, p = 0.938), or blood pressure control among diagnosed patients (31.6% vs. 35.5%, p = 0.966). Despite high treatment adherence, 66.3% of hypertensive patients had uncontrolled blood pressure, and 36.4% of all hypertensive patients remained undiagnosed. Conclusion Hypertension affects two-thirds of diabetic adults in Northern State, Sudan, with over one-third of cases unrecognized and two-thirds uncontrolled. The absence of significant urban-rural disparities in disease burden or management challenges conventional assumptions about healthcare access gaps and supports population-based interventions targeting all diabetic patients, regardless of geographic location. Clinical trial number: Not applicable Awareness Control Diabetes mellitus Hypertension Northern State Prevalence Sudan Urban-Rural Disparities Figures Figure 1 Figure 2 1. Background Diabetes is a chronic illness characterized by elevated levels of blood glucose and disturbed metabolism of fats and proteins [1]. Diabetes is recognized as a significant factor in both mortality and morbidity worldwide, affecting various demographics regardless of geographic location, age group, or gender [2]. The prevalence of diabetes among adults (20-79 years) is approximately 10.5% of the global adult population, with approximately 589 million people living with diabetes [3]. In the Middle East and North Africa region, the prevalence rises significantly to approximately 32.5% among adults, making it one of the regions most affected by the disease [4]. As a consequence of the rising diabetes prevalence, 1.5 million people died directly from diabetes in 2012 [1]. Hypertension is a frequent, chronic, age-related disorder [5]. Hypertension rates have rasen globally, particularly in low- and middle-income countries (LMICs), according to global Estimates from 2010, approximately 31.1% of adults population (1.39 billion people) worldwide were living with this condition [6]. In patients with diabetes hypertension synergistically accelerate renal function decline, particularly when moderate to severe albuminuria is present, and exacerbates the development of retinopathy, and cerebral diseases [7]. This makes hypertension a key contributor to both microvascular and macrovascular chronic diabetic complications. While high blood pressure is uncommon at onset of Type 1 Diabetes (T1DM), but emerges as kidney disease progression, contributing to end-stage renal failure. In contrast, many patients with Type 2 Diabetes (T2DM) already have hypertension when they are first diagnosed [8]. Moreover, the pathophysiological links in the co-existence of hypertension and diabetes are profound and multifactorial, with multiple mechanisms playing different roles. The link between diabetes and hypertension is well established, with 70% of diabetic patient develop hypertension [9]. This means hypertension is about twice as frequent in this group as in the general population. Supporting this epidemiological data confirms that the prevalence of hypertension among diabetic patients is approximately 1.5 to 2.0 times higher than in matched non-diabetic groups [8]. Hypertension is a critical comorbidity in diabetic patients. In Sudan, the dual burden of diabetes and hypertension represents a growing public health crisis, straining an already fragile healthcare system. While studies have documented the overall prevalence of hypertension among diabetic patients to be about 47.7% [10, 11], a critical and unaddressed dimension is the potential inequity in healthcare delivery and outcomes between rural and urban populations. Rural and urban diabetic communities often demonstrate marked variability in the prevalence and management of hypertension [12]. These variables are influenced by different factors, particularly healthcare accessibility, socioeconomic conditions, health-seeking behavior, and behavioral patterns, and these differences might aggravate the risk for developing these conditions and accelerating their complications. Without a clear, evidence-based understanding of where and how disparities exist, public health interventions and clinical programs risk being misdirected, inefficient, or inequitable. Consequently, there is an urgent need for localized research that systematically compares hypertension-related indicators among diabetic adults across rural and urban settings to inform targeted, effective, and equitable health policies and programs. Therefore, this study aims to investigate these disparities in the Northern State of Sudan. The findings will provide basic evidence to inform equitable and effective major health policies and interventions aimed at reducing the hypertension burden in this high-risk population. 2. Methods Study Design and setting This research employed a community-based, analytical cross-sectional study design. The cross-sectional design was chosen as it is effective for determining the prevalence of hypertension and associated factors (awareness, treatment, control) at a single point in time and for making comparisons between groups (rural vs. urban). The study was conducted in the Northern State, one of Sudan's 18 states located in the far north, about 328 km north of Khartoum, the capital of Sudan, bordering Egypt and Libya. It has an area of 348,876 km² and an estimated population of 1,132,000. It is characterized by a predominantly arid landscape and its position along the River Nile bank [13, 14]. The Northern State is divided into 7 localities: Wadi Halfa, Dalgo, Al-Burgaig, Dongola, Al-Golid, Al-Dabbah, and Merowe [13]. The state has been impacted by the internal displacement of thousands of people (13% of the internally displaced) due to the recent war conflict between the Sudanese Armed Forces and the Rapid Support Forces [15, 16]. Study Population The target populations of this study were selected according to fallowing criteria: Inclusion Criteria: 1. Adult aged 18 years or above. 2. Confirmed diagnosis of diabetes mellitus by a physician or based on self-report with evidence of medication use. 3. Permanent resident of the Northern State (≥1 year). Exclusion Criteria: 1. Internally displaced people from other states due to the war conflict. 2. Pregnant women due to physiological changes in Blood Pressure (BP). 3. Individuals with severe mental illness or cognitive impairment preventing informed consent or a reliable interview. 4. Critically ill individuals or those unable to participate in the interview or measurements. Sampling The sample size was calculated using the Cochran formula, with a 95% confidence level, a 4% margin of error, and a 70% estimated prevalence of hypertension among diabetics [9]. n = Z 2 * p(1-p)/e 2 n = minimum required sample size. e= desired margin of error (4%). P = estimated population proportion, prevalence of hypertension in diabetic (70%). Z = Z-score for 95% confidence level (1.96). Accounting for a potential non-response rate of 10%, the final minimum sample size was adjusted to 555 participants. The study successfully enrolled 595 participants. Sampling Technique A multi-stage stratified random sampling technique was used to ensure representativeness across rural and urban populations: • Stage 1: Locality Selection: Three of the seven localities were selected by simple random sampling technique. The selected localities were Dongola, Al-Burgaig, and Merowe. • Stage 2: Stratification by Location: Each locality was divided into urban and rural strata. Lists of different villages and cities were obtained from the official registries of the administrative unit of each locality. The capital city of the locality was non-randomly selected to represent the urban population as it is the biggest city with the largest urban population. Three villages from each locality were selected by a simple random selection technique to represent the rural population. • Stage 3: Selection of Clusters: A number of communities or neighborhoods were randomly selected from each stratum. • Stage 4: Household Selection: Within each selected community, households were selected by systematic random sampling. • Stage 5: Individual Participant Selection: In each household, all adult diabetic patients meeting the inclusion criteria were selected. Methods of Data Collection The data were collected over a two-month period by a team of trained data collectors (senior medical students). An interviewer-administered structured questionnaire was devolved for this study, used to gather data on sociodemographic factors, diabetes-related history (type of diabetes, duration since diagnosis, current treatment, self-reported adherence, and last known glycated hemoglobin (HbA1c) result), hypertension-related data (awareness of hypertension diagnosis, duration, family history, knowledge of the diabetes-hypertension relationship, current antihypertensive medication, self-reported adherence, and self-monitoring behaviors), and lifestyle and behavioral factors (smoking status, alcohol use, and physical activity),[supplementary file 1]. Blood pressure measurements were obtained using calibrated mercury sphygmomanometers fitted with an appropriate cuff size, following the American Heart Association's recommended procedures [17]. For each participant, three consecutive readings were taken on the right arm at two-minute intervals, with the individual seated comfortably and the arm properly supported. The final blood pressure was determined by calculating the mean of these three measurements. Hypertension was defined as a mean systolic pressure of 140 mmHg or higher, a mean diastolic pressure of 90 mmHg or higher, or current pharmacological treatment for a previously established diagnosis. Among hypertensive individuals, controlled blood pressure was defined as an average below 140/90 mmHg. Additionally, participants without a prior diagnosis of hypertension who were found to have an average reading of 140/90 mmHg or higher were classified as having undiagnosed hypertension. Participant weight was recorded to the closest 0.1 kg using a digital scale while they wore light clothing. Height was measurement was taken to closest 0.1 cm using a portable stadiometer. Body mass index (BMI) was calculated using the standard formula (kg/m²). The last HbA1c level, or the last blood glucose level if HbA1c was unavailable, was obtained from the participants. The patient was considered to have uncontrolled diabetes mellitus (DM) if their last HbA1c was ≥7% (53 mmol/mol) or their last blood glucose was ≥140 mg/dl (7.8 mmol/l). Data Preparation and Presentation Completed questionnaires were checked daily for completeness and consistency by field supervisors. Data were then entered into Microsoft Excel software with double-entry verification to minimize errors. The cleaned dataset was exported to the Statistical Package for the Social Sciences (SPSS) version 27 (IBM) for analysis by a professional data analyst. Results are presented using tables, bar charts, and pie charts for clarity. Data Analysis 1. Descriptive Statistics: Frequencies and percentages were used to describe categorical variables (e.g., sex, residence, awareness status). Means and standard deviations were used for continuous variables (e.g., age, BMI, BP). 2. Analytical Statistics: • Group Comparisons: Chi-square tests (or Fisher's exact test) were used to compare categorical outcomes (prevalence, awareness, treatment, control) between rural and urban groups. Independent samples t-tests (or Mann-Whitney U tests for non-normal data) were used to compare continuous variables (e.g., mean BP, BMI, and HbA1c) between the two groups. Analysis of Variance (ANOVA) was also employed for multi-group comparisons as shown in the results. • A p-value of <0.05 was considered statistically significant for all tests. 3. Results Table 1. Socio-demographic Characteristics of the adult diabetic patients, (total number = 595). Characteristic Category Urban (n =320) Rural (n = 275) Total (n =595) p-value F* % F* % Gender Male 125 39.1% 108 39.3% 233 (39.1%) 0.917 Female 195 60.9% 167 60.7% 362 (60.9%) Age (years) 18-39 27 8.4% 23 8.4% 50 (8.4%) 0.981 40-59 153 47.8% 131 47.6% 284 (47.8%) >60 140 43.8% 121 44.0% 261 (43.8%) Occupation Not working 55 17.2% 47 17.1% 102 (17.1%) 0.999 Housewife 139 43.4% 119 43.3% 258 (43.4%) Self-employed 75 23.4% 65 23.6% 140 (23.5%) Government sector 39 12.2% 33 12.0% 72 (12.2%) Private sector 12 3.8% 11 4.0% 23 (3.8%) Educational Level Illiterate 41 12.8% 36 13.1% 77 (13%) 0.984 Pre-university 223 69.7% 191 69.5% 414 (69.5%) University or higher 56 17.5% 48 17.5% 104 (17.5%) Marital Status Married 289 90.3% 249 90.5% 538 (90.4%) 0.964 Unmarried 31 9.7% 26 9.5% 57 (9.6%) Income Level Insufficient 147 45.9% 127 46.2% 274 (46%) 0.879 Sufficient 173 54.1% 148 53.8% 321 (54%) Family Size ≤5 139 43.4% 119 43.3% 258 (43.4%) 0.949 >5 181 56.6% 156 56.7% 337 (56.6%) Number of Family Members with Diabetes ≤2 295 92.2% 254 92.4% 549 (92.3%) 0.944 >2 25 7.8% 21 7.6% 46 (7.7%) Body Mass Index (BMI) ≤30.0 214 66.9% 183 66.5% 397 (66.8%) 0.882 >30.0 106 33.1% 92 33.5% 198 (33.3%) Regular Exercise Yes 173 54.1% 148 53.8% 321 (54%) 0.906 No 147 45.9% 127 46.2% 274 (46%) Consumption of Foods High Salts intake 132 41.3% 114 41.5% 246 (41.4%) 0.879 Adequate Fruits/Vegetables intake 270 84.4% 232 84.4% 349 (58.6%) Smoking Yes 10 3.1% 8 2.9% 18 (3%) 0.975 No 310 96.9% 267 97.1% 577 (97%) Knowledge of Link Between Diabetes and Hypertension Yes 206 64.4% 177 64.4% 443 (74.5%) 0.975 No 114 35.6% 98 35.6% 152 (25.5%) Family History of Hypertension Yes 213 66.6% 183 66.5% 396 (66.6%) 0.975 No 107 33.4% 92 33.5% 199 (33.4%) *F= Frequency The total number of participants was 595, urban participants constituted 320 (53.8%), while females were 362 (60.8%). There was no significant difference between the rural and urban participants with regards to socio-demographic characteristics as shown in Table 1. The sample was demographically homogeneous between urban and rural areas; predominantly females, married, housewives, with intermediate education, had limited income, knew the link between hypertension and diabetes and had positive family history of hypertension. Table 2. Diabetes-Related Characteristics by Residence, (total number = 595). Characteristic Category Urban (n=320) Rural (n=275) Total (n =595) p-value F % F % Type of Diabetes Type 1 29 9.1% 25 9.1% 54 (9%) 0.998 Type 2 183 57.2% 157 57.1% 340 (57.1%) Unsure 108 33.8% 93 33.8% 201 (33.9%) Duration Since Diagnosis (Years) ≤10 155 48.4% 133 48.4% 288 (48.4%) 0.976 11-20 113 35.3% 97 35.3% 210 (35.3%) >20 52 16.3% 45 16.4% 97 (16.3%) Current Treatments Used Diet only 11 3.4% 10 3.6% 21 (3.5%) 0.964 Oral tablets 215 67.2% 185 67.3% 400 (67.2%) Insulin 83 25.9% 71 25.8% 154(25.9%) Insulin + Oral tablets 11 3.4% 9 3.3% 20 (3.4%) Adherence to Diabetes Treatment Yes 265 82.8% 228 82.9% 493 (82.8%) 0.994 No 55 17.2% 47 17.1% 102 (17.2%) Blood Sugar Monitoring Blood glucose level 133 41.6% 114 41.5% 247 (41.5%) 0.975 HbA1c 147 45.9% 127 46.2% 274 (46%) Did not monitor blood sugar 40 12.5% 34 12.4% 74 (12.5%) Latest HbA1c/ estimated A1c (Among those tested) Controlled 86 30.7% 74 30.7% 160* (30.7%) 0.899 Uncontrolled 176 62.8% 151 62.6% 327* (62.7%) *among 521 of participants (monitoring blood sugar), 14 of them did not remember their last HbA1c, and 20 did not remember last blood glucose With regards to clinical, treatment and laboratory related characteristics of the study participants as demonstrated in Table 2, no statistically significant differences were found between urban and rural diabetic patients. The high proportion of "Unsure" regarding the type of diabetes might indicate poor knowledge or differentiation between diabetic types, necessitating better education. More than half of the patients were taking oral anti-diabetic medications, a high proportion (83%) were adherent to their medication but near two-thirds had poor glycemic control. Table 3. Characteristics of hypertension by residence, (total number = 595). Characteristic Category Urban (n=320) Rural (n=275) Total p-value F % F % Diagnosed with Hypertension Yes 137 42.8% 118 42.9% 255 (42.8%) 0.964 No 183 57.2% 157 57.1% 340 (57.2%) Duration Since Hypertension Diagnosis (Years) ≤15 99 72.3% 85 72.0% 184 (72.1%) 0.887 >15 38 27.7% 33 28.0% 71 (27.9%) Adherence to Hypertension Treatment (among diagnosed) Yes 118 86.1% 102 86.4% 220 (86.3%) 0.938 No 19 13.9% 16 13.6% 35 (13.7%) Attendance at Regular Follow-up (among diagnosed) Yes 91 66.4% 78 66.1% 169 (66.3%) 0.924 No 46 33.6% 40 33.9% 86 (33.7%) Hypertension Complications (among diagnosed) Yes 31 22.6% 27 22.9% 58 (22.7%) 0.924 No 106 77.4% 91 77.1% 197 (77.3%) Type of Complication (among those with complications) Cardiovascular 19 61.3% 16 59.3% 35 (60.3%) 0.924 Renal 6 19.4% 6 22.2% 12(20.6%) Cerebral hemorrhage 4 12.9% 3 11.1% 7 (12%) Multiple complications 2 6.5% 2 7.4% 4 (6.9%) Table 3 demonstrates the prevalence and clinical characteristics of hypertension among the study population. Participants already diagnosed with hypertension comprised about 43%, with good adherence to treatment and regular follow up. There were no statistically significant differences between rural and urban participants. Among all participants who were not known hypertensive, 146/340 (42.9%) had high blood pressure (≥140/90), making the total number of participants with hypertension to be 401 (67.4%), this is demonstrated in Figure 1. The overall awareness rate of hypertension (known hypertensive/Total hypertensive%) was 63.6%. Table 4. Mean systolic and diastolic blood pressure levels among rural and urban, (total number=595). Group N Mean Systolic (mmHg) Standard Deviation Mean Diastolic (mmHg) Standard Deviation p-value All Patients 595 137.5 19.5 83.3 10.1 - Urban 320 135.2 19.8 81.5 11.5 - Rural 275 139.5 22.1 84.1 13.2 - Diagnosed 255 144.3 21.4 85.6 12.8 0.023 Undiagnosed 340 130.5 17.2 78.9 10.5 Diagnosed (Urban) 137 140.5 20.1 84.2 11.9 0.017 Diagnosed (Rural) 118 145.8 23.5 88.1 13.8 Undiagnosed (Urban) 183 130.1 16.8 78.5 10.2 0.449 Undiagnosed (Rural) 157 131.9 18.5 80.3 11.3 The mean blood pressure levels (systolic & Diastolic) were higher among rural compared to urban population and were also higher among known hypertensive individuals compared to newly diagnosed participants as shown in Table 4. Table 5. Blood pressure parameters among rural and urban, (total number = 595). Characteristic Category Urban Rural Total p-value F % F % Current BP Reading for All Participants <140/90 192 60.0% 165 60.0% 357 (60%) 0.975 ≥140/90 128 40.0% 110 40.0% 238 (40%) Hypertensive Patients (Diagnosed) Controlled 49 35.5% 37 31.6% 86 (33.7%) 0.966 Uncontrolled 89 64.5% 80 68.4% 169 (66.3%) Undiagnosed for Hypertension Normal BP 107 58.4% 87 55.4% 194 (57%) 0.908 Elevated Undiagnosed (Unaware) 74 40.5% 72 45.8% 146 (43%) Total number of hypertensive (known + new) is 401 (67.4%, n = 595) Awareness Rate Known hypertensive 137 64.9% 118 62.1% 255 (63.6%) 0.959 Unawareness rate Newly diagnosed 74 35.1% 72 37.9% 146 (36.4) 0.998 Nearly two third of diagnosed individuals 66.3% had uncontrolled BP despite good treatment adherence, but regular follow-up and consistent BP measurement were less than optimal, which may explain why they were uncontrolled. Complications were not rare, about 23% of known hypertensive patients developed complications related to hypertension that necessitates intensified prevention efforts. The overall awareness rate of hypertension was 63.6%. There were no statistically significant differences between rural and urban participants with regards to blood pressure levels, control rate and undiagnosed hypertension as demonstrated in Table 5. Discussion Prevalence of Hypertension The overall prevalence of hypertension was 67.4% (comprising 42.9% previously diagnosed plus 24.5% newly discovered cases). This aligns closely with global estimates that hypertension affects approximately 70% of patients with diabetes [ 18 ], and is close to Middle East and North Africa (MENA) data, which reports a pooled prevalence of 56% among diabetic patients [ 19 ]. A multinational study from the Middle East and Africa cohort similarly found that over 40% of diabetic patients had hypertension [ 20 ]. Nationally, our findings showed a high prevalence of hypertension among diabetic patients, comparable to previous Sudanese studies reporting 47.7% in a survey at a diabetes healthcare facility [ 11 ] and 47.4% prevalence among diabetics in El-Gezira State [ 21 ], as well as 47.6% in northern Sudan [ 10 ]. The slightly higher rate in our study may reflect the inclusion of undiagnosed cases identified through active blood pressure measurement. This may also be explained by the increasing prevalence of diabetes in the MENA region and in Sudan [ 4 , 22 ]. Our findings on management reveal both strengths and gaps. The high treatment adherence rates for hypertension 86.3% and diabetes 82.8% are commendable and exceed those often reported in similar resource-limited settings and are even higher than in some high-income areas [ 23 ]. Even with high treatment adherence, disease control was suboptimal; 66.3% of hypertensive patients had uncontrolled BP (Rural: 68.4% vs. Urban: 64.5%, p = 0.966). The predominant use of monotherapy (amlodipine-based, 72.9% of hypertensive patients) aligns with standard first-line treatment protocols [ 17 ]. The most striking and potentially important finding is the lack of statistically significant differences between urban and rural residents across most parameters: HTN prevalence, treatment complexity, awareness rate, and achieved blood pressure control. This contrasts with the common paradigm of a health access gap favoring urban areas. Hypertension prevalence was nearly identical among previously diagnosed patients (urban: 42.8% vs. rural: 42.9%, p = 0.964). Blood pressure control rates among diagnosed hypertensive patients showed no statistical difference (urban: 35.5% vs. rural: 31.6%, p = 0.966). Furthermore, the proportion of undiagnosed hypertension (those with blood pressure ≥ 140/90 mmHg who were considered unaware) was slightly higher in the rural area, with no statistically significant differences (urban: 40.5% vs. rural: 45.8%, p = 0.908). This homogeneity contrasts with global literature, which often demonstrates significant urban-rural gradients. For example, a meta-analysis of 62 studies involving 108,110 participants found that slum residents were 35% more likely to be hypertensive than rural dwellers [ 24 ]. Other research has shown that awareness and treatment were significantly lower in rural compared to urban communities in low-income countries [ 25 ]. However, our findings align with recent meta-analyses demonstrating narrowing urban-rural differences in low-income countries, from 5.75% (1990–2004) to 1.38% (2005–2020) [ 26 ]. The absence of disparities in our study may reflect an epidemiological transition, demographic similarity, and equitable health information access in Northern Sudan. The overall awareness rate 63.6% substantially exceeded the 46.5% reported in the multinational Prospective Urban Rural Epidemiology (PURE) study and the 40.8% observed in low-income countries. Treatment adherence among aware individuals 86.3% was comparable to the 87.5% in PURE. However, uncontrolled blood pressure among treated patients 66.3% is double the global challenge (32.5% in PURE). Monotherapy predominated 73%, mainly amlodipine 72.9%, contrasting with PURE, where 30.8% received combination therapy. The 42.9% undiagnosed hypertension patients remains concerning and aligns with the 46.5% awareness gap reported globally [ 27 ]. Factors Associated with Hypertension and Poor Control Consistent with the literature, age (91.6% >40 years) [ 12 , 27 ], obesity (33% with BMI > 30) [ 11 , 12 , 27 ], physical inactivity (46%), high salt intake (41%), and family history (66%) were prevalent. Importantly, 34% of diagnosed patients lacked regular follow-up, and 40.4% had not measured their BP for > 3 weeks, explaining the 68.4% uncontrolled rate despite high reported adherence. Complications affected 23% (60% cardiovascular), underscoring the clinical significance of optimal control [ 18 ] and consistent with the association between hypertension and retinopathy reported nationally [ 11 ]. Limitations The cross-sectional design prevents causal inference, and single-state conduct limits generalizability. Self-reported data (adherence, lifestyle) are subject to recall and social desirability bias, as evidenced by the discordance between high reported adherence (> 80%) and poor objective control (66% uncontrolled BP). Non random selection of capital cities to represent urban areas may have introduced selection bias. Reliance on recalled HbA1c with 6% missing data compromises glycemic control assessment. These limitations highlight the need for longitudinal studies with objective measures and broader population inclusion. Conclusion This study demonstrates a high prevalence of hypertension among diabetic adults in Northern Sudan. Contrary to expectations, a significant urban-rural disparity was absent in prevalence, awareness, treatment adherence, or control rates. While the awareness rate 63.6% and treatment adherence (86.3%) are commendable, control remains suboptimal, with 66.3% having uncontrolled hypertension, and 36.4% of hypertension cases remaining undiagnosed. Abbreviations AHA American Heart Association ANOVA Analysis of Variance BMI Body Mass Index BP Blood Pressure DM Diabetes Mellitus HbA1c Glycated Hemoglobin HTN Hypertension IDF International Diabetes Federation LMICs Low- and Middle-Income Countries MENA Middle East and North Africa mmHg Millimeters of Mercury PURE Prospective Urban Rural Epidemiology SD Standard Deviation SPSS Statistical Package for the Social Sciences T1DM Type 1 Diabetes Mellitus T2DM Type 2 Diabetes Mellitus WHO World Health Organization Declarations Ethics approval and consent to participate This study was conducted in Accordance with the principles of the Declaration of Helsinki. Prior to the commencement of the study, ethical clearance was obtained from the Community Medicine Department, Faculty of Medicine, University of Dongola, as well as from the Ethics Committee of the Northern State Ministry of Health for each locality as they requested (Approval ID not applicable). Permissions were obtained from the administrative personnel and community leaders of each selected locality, city, or village. Written informed consent was obtained from every participant after a detailed explanation of the study's purpose, procedures, potential benefits (free BP check and referral if needed), and risks (minimal, related to time and discomfort from the BP cuff), in a language they understand, informed consent for illiterate participants obtained from their legal guardians. All participants were assured of the confidentiality of their personal information, and their right to withdraw from the study at any time without any consequences. Consent for publication Not Applicable. Availability of data The Dataset used and analyzed during the current study, are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding The authors and participants did not receive any type of funding for this study. Authors' Contributions Al-Mowafag Anwer Omer and Mohamed Osman Abdelaziz; developed the research concept, and drafted and reviewed the study reports and manuscript. Roaa Ebrahim Bashir, Moshtaha Emadeldin, Asma Siddeeg, Haniss Mustafa, Asma Mahmoud, and Selsabeel Abd Alraheim; designed the data collection process and revising the manuscript. Outhman Alsadiq performed the statistical analysis and interpreted the data. All authors read and approved the final manuscript. Acknowledgements The authors would like to thank all the participants from all rural and urban areas of the Northern State. They would also like to thank the administrators of the State Ministry of Health, the three localities, as well as the villages and cities included in the study. Many thanks to the local community leaders who facilitated and helped the data collectors. Author information Al-Mowafag Anwer Omer 1 Mohamed Osman Abdelaziz 2 Roaa Ebrahim Bashir 3 Moshtha Emadeldin 4 Asma Siddeeg 5 Haniss Mustafa 6 Asma Mahmoud 7 Selsabeel Abd Alrahim 8 Outhman Alsadiq 9 1 Medical Student, Faculty of Medicine, University of Dongola. E-mail: [email protected] 2 MD,Professor, Head Department of Internal Medicine, Faculty of Medicine, University of Dongola. E-mail: [email protected] 3 Internal Medicine Registrar (SMSB), Lecturer, Department of Internal Medicine, Faculty of Medicine, University of Dongola. E-mail: [email protected] 4 Medical Student, Faculty of Medicine, University of Dongola. E-mail: [email protected] 5 Medical Student, Faculty of Medicine, University of Dongola. E-mail: [email protected] 6 Medical Student, Faculty of Medicine, University of Dongola. E-mail: [email protected] 7 Medical Student, Faculty of Medicine, University of Dongola. E-mail: [email protected] 8 Medical Student, Faculty of Medicine, University of Dongola. E-mail: [email protected] 9 Assistant Professor, Faculty of Economic and Administrative Sciences, University of Dongola. E-mail: [email protected] References Roglic G. WHO Global report on diabetes: A summary. Int J Noncommunicable Dis 2016 Apr-Jun;1(1):3–8. 10.4103/2468-8827.184853 Hossain MJ, Al-Mamun M, Islam MR. Diabetes mellitus, the fastest growing global public health concern: Early detection should be focused. Health Sci Rep. 2024;7(3):e2004. doi: 10.1002/hsr2.2004. PMID: 38524769; PMCID: PMC10958528. International Diabetes Federation. IDF Atlas 11th Edition. Available from: https://diabetesatlas.org/resources/idf-diabetes-atlas-2025/ [Accessed 1st September 2025]. International Diabetes Federation. Middle East and North Africa: diabetes report 2000–2050. In: IDF Diabetes Atlas, 11th ed. Brussels: International Diabetes Federation. 2025. Available from: https://diabetesatlas.org/data-by-location/region/middle-east-and-north-africa [Accessed 1st September 2025]. Staessen JA, Wang J, Bianchi G, Birkenhäger WH. Essential hypertension. Lancet. 2003;361(9369):1629-41. 10.1016/S0140-6736(03)13302-8 . PMID: 12747893. Mills KT, Stefanescu A, He J. The global epidemiology of hypertension. Nat Rev Nephrol. 2020;16(4):223–37. 10.1038/s41581-019-0244-2 . Epub 2020 Feb 5. PMID: 32024986; PMCID: PMC7998524. Grossman E, Messerli FH. Hypertension and diabetes. In: Fishman EZ, Tenenbaum A, editors. Cardiovascular Diabetology: Clinical, Metabolic and Inflammatory Facets. Advances in Cardiology. Volume 45. Basel: Karger; 2008. pp. 82–106. 10.1159/isbn.978-3-8055-8428-9 . Simonson DC. Etiology and prevalence of hypertension in diabetic patients. Diabetes Care. 1988 Nov-Dec;11(10):821–7. 10.2337/diacare.11.10.821 . Hezam AA, Mohammed1;, Shaghdar, Hanan Basheer Mohammed2, Chen. Liying2. The connection between hypertension and diabetes and their role in heart and kidney disease development. Journal of Research in Medical Sciences 29(1):22, April 2024. | 10.4103/jrms.jrms_470_23 Abdelbagi O, Musa IR, Musa SM, ALtigani SA, Adam I. Prevalence and associated factors of hypertension among adults with diabetes mellitus in northern Sudan: a cross-sectional study. BMC Cardiovasc Disord. 2021;21(1):168. 10.1186/s12872-021-01983-x . PMID: 33838664; PMCID: PMC8037914. Almobarak AO, Badi S, Siddiq SB, Noor SM, Elmadhoun WM, Suliman M, Ahmed MH. The prevalence and risk factors for systemic hypertension among Sudanese patients with diabetes mellitus: a survey in diabetes healthcare facility. Diabetes Metab Syndr. 2020 Nov-Dec;14(6):1607–11. 10.1016/j.dsx.2020.08.010 . Venkatesh U, Grover A, Vignitha B, Ghai G, Malhotra S, Kishore J, Jaswal N, Yashwanth RD, Durga R, Goel S, Kishore S. Urban-rural disparities in blood pressure and lifestyle risk factors of hypertension among Indian individuals. J Family Med Prim Care. 2022;11(9):5746–56. Epub 2022 Oct 14. PMID: 36505536; PMCID: PMC9730999. Northern State Government [Internet]. Sudan: Alshmalia State Government; Available from: https://www.alshamaliastate.gov.sd/ [Accessed 11th March 2026]. Central Bureau of Statistics (Sudan). Population projections for Sudan 2025 [Internet]. Khartoum: Central Bureau of Statistics. 2025. Table 3.5. Available from: https://drive.google.com/file/d/1VplW60uDgAn5OyhDS9UN_fp75OwG0IFt/view [Accessed 28th August 2025]. Migration Policy Centre. Overview of displacement in Sudan: the causes, dynamics and consequences [Internet]. Florence: Migration Policy Centre; Available from: https://migrationpolicycentre.eu/overview-of-displacement-in-sudan-the-causes-dynamics-and-consequences/ [Accessed 8th March 2026]. Internal Displacement Monitoring Centre. Sudan: the world's largest internal displacement crisis deepens [Internet]. Geneva: Internal Displacement Monitoring Centre. Available from: https://www.internal-displacement.org/spotlights/sudan-the-world-s-largest-internal-displacement-crisis-deepens/ [Accessed 8th March 2026]. Jones DW, Ferdinand KC, Taler SJ, Johnson HM et al. 2025 AHA/ACC/AANP/ AAPA/ABC/ACCP/ACPM/AGS/AMA/ASPC/NMA/PCNA/SGIM Guideline for the Prevention, Detection, Evaluation and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Hypertension. 2025;82(10):e212-e316. 10.1161/HYP.0000000000000249 . Epub 2025 Aug 14. Erratum in: Hypertension. 2025;82(12):e350. doi: 10.1161/HYP.0000000000000257. PMID: 40811516. Lago RM, Singh PP, Nesto RW. Diabetes and hypertension. Nat Clin Pract Endocrinol Metab. 2007;3(10):667. 10.1038/ncpendmet0638 . PMID: 17893686. Khalil SA, Azar S, Hafidh K, Ayad G, Safwat M. Prevalence and co-prevalence of comorbidities among patients with type 2 diabetes mellitus in the MENA region: a systematic review. Curr Diabetes Rev. 2024;20(7):e310723219277. 10.2174/1573399820666230731105704 . PMID: 37526192; PMCID: PMC11092551. Hafidh K, Malek R, Al-Rubeaan K, Kok A, Bayram F, Echtay A, Rajadhyaksha V, Hadaoui A. Prevalence and risk factors of vascular complications in type 2 diabetes mellitus: results from the DISCOVER Middle East and Africa cohort. Front Endocrinol (Lausanne). 2022;13:940309. 10.3389/fendo.2022.940309 . PMID: 36017310; PMCID: PMC9396276. Omer SA, Elamin MFM, Mahgoub AMA, et al. Prevalence and associated risk factors of hypertension among adults with diabetes mellitus in Wad-Medani, Gezira State, Sudan: A cross-sectional study. Biomed J Sci Tech Res (BJSTR). 2024;58(5). 10.26717/BJSTR.2024.58.009228 . Article ID: BJSTR.MS.ID.009228. International Diabetes Federation. Sudan: diabetes country report 2000–2050 [Internet]. In: IDF Diabetes Atlas, 11th ed. Brussels: International Diabetes Federation. 2025. Available from: https://diabetesatlas.org/data-by-location/country/sudan/ [Accessed 8th March 2026]. Algabbani FM, Algabbani AM. Treatment adherence among patients with hypertension: findings from a cross-sectional study. Clin Hypertens. 2020;26:18. 10.1186/s40885-020-00151-1 . PMID: 32944283; PMCID: PMC7491181. Uthman OA, Ayorinde A, Oyebode O, Sartori J, Gill P, Lilford RJ. Global prevalence and trends in hypertension and type 2 diabetes mellitus among slum residents: a systematic review and meta-analysis. BMJ Open. 2022;12(2):e052393. 10.1136/bmjopen-2021-052393 . PMID: 35210339; PMCID: PMC8883228. Chow CK, Teo KK, Rangarajan S, Islam S, Gupta R, Avezum A et al. PURE (Prospective Urban Rural Epidemiology) Study investigators. Prevalence, awareness, treatment, and control of hypertension in rural and urban communities in high-, middle-, and low-income countries. JAMA. 2013;310(9):959 – 68. 10.1001/jama.2013.184182 . PMID: 24002282. Ranzani OT, Kalra A, Di Girolamo C, Curto A, Valerio F, Halonen JI, et al. Urban-rural differences in hypertension prevalence in low-income and middle-income countries, 1990–2020: a systematic review and meta-analysis. PLoS Med. 2022;19(8):e1004079. 10.1371/journal.pmed.1004079 . PMID: 36007101; PMCID: PMC9410549. Naseri MW, Esmat HA, Bahee MD. Prevalence of hypertension in type 2 diabetes mellitus. Ann Med Surg (Lond). 2022;78:103758. 10.1016/j.amsu.2022.103758 . PMID: 35620043; PMCID: PMC9127167. Additional Declarations No competing interests reported. Supplementary Files Supplementaryfile1Questionnaire.pdf Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 03 May, 2026 Reviewers agreed at journal 16 Apr, 2026 Reviewers invited by journal 15 Apr, 2026 Editor assigned by journal 13 Apr, 2026 Editor invited by journal 25 Mar, 2026 Submission checks completed at journal 25 Mar, 2026 First submitted to journal 25 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9173542","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":624968146,"identity":"4ca06bc7-8c21-4ff7-aafd-83888330269e","order_by":0,"name":"Al-Mowafag Anwer 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and newly discovered hypertension, (total number = 595).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9173542/v1/99271fb767a8c7cbe4a58899.jpg"},{"id":107634275,"identity":"9ca9d5b9-3d96-4271-bb07-7580bdf58952","added_by":"auto","created_at":"2026-04-23 12:21:25","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81681,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTreatment types of hypertension among rural and urban, (n = 255).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9173542/v1/e913bcda3c8e8e4d62f36ccc.jpg"},{"id":107708929,"identity":"bc8bf027-3119-4849-8b54-caef3d19305e","added_by":"auto","created_at":"2026-04-24 09:33:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":748571,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9173542/v1/ea988449-a94b-4a1c-8033-7a7b89d17aa2.pdf"},{"id":107634273,"identity":"77fe072f-cb0f-4169-ac6d-711ffc8cdcf3","added_by":"auto","created_at":"2026-04-23 12:21:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":341286,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile1Questionnaire.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9173542/v1/7eaedb115f7fc1f326745c51.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Urban-Rural Disparities in the Prevalence, Awareness, Treatment, and Control of Hypertension among Adult Diabetic Patients in Northern State, Sudan: A cross sectional Analytical Community-based Study, 2026","fulltext":[{"header":"1. Background","content":"\u003cp\u003eDiabetes is a chronic illness characterized by elevated levels of blood glucose and disturbed metabolism of fats and proteins [1]. Diabetes is recognized as a significant factor in both mortality and morbidity worldwide, affecting various demographics regardless of geographic location, age group, or gender [2]. The prevalence of diabetes among adults (20-79 years) is approximately 10.5% of the global adult population, with approximately 589 million people living with diabetes [3]. In the Middle East and North Africa region, the prevalence rises significantly to approximately 32.5% among adults, making it one of the regions most affected by the disease [4]. As a consequence of the rising diabetes prevalence, 1.5 million people died directly from diabetes in 2012 [1].\u003c/p\u003e\n\u003cp\u003eHypertension is a frequent, chronic, age-related disorder [5]. Hypertension rates have rasen globally, particularly in low- and middle-income countries (LMICs), according to global Estimates from 2010, approximately 31.1% of adults population (1.39 billion people) worldwide were living with this condition [6]. \u0026nbsp;In patients with diabetes hypertension synergistically accelerate renal function decline, particularly when moderate to severe albuminuria is present, \u0026nbsp;and exacerbates the development of retinopathy, and cerebral diseases [7]. This makes hypertension a key contributor to both microvascular and macrovascular chronic diabetic complications.\u003c/p\u003e\n\u003cp\u003eWhile high blood pressure is uncommon at onset of Type 1 Diabetes (T1DM), but emerges as kidney disease progression, contributing to end-stage renal failure. In contrast, many patients with Type 2 Diabetes (T2DM) already have hypertension when they are first diagnosed [8]. Moreover, the pathophysiological links in the co-existence of hypertension and diabetes are profound and multifactorial, with multiple mechanisms playing different roles.\u003c/p\u003e\n\u003cp\u003eThe link between diabetes and hypertension is well established, with 70% of diabetic patient develop hypertension [9]. This means hypertension is about twice as frequent in this group as in the general population. Supporting this epidemiological data confirms that the prevalence of hypertension among diabetic patients is approximately 1.5 to 2.0 times higher than in matched non-diabetic groups [8].\u003c/p\u003e\n\u003cp\u003eHypertension is a critical comorbidity in diabetic patients. In Sudan, the dual burden of diabetes and hypertension represents a growing public health crisis, straining an already fragile healthcare system. While studies have documented the overall prevalence of hypertension among diabetic patients to be about 47.7% [10, 11], a critical and unaddressed dimension is the potential inequity in healthcare delivery and outcomes between rural and urban populations. Rural and urban diabetic communities often demonstrate marked variability in the prevalence and management of hypertension [12]. These variables are influenced by different factors, particularly healthcare accessibility, socioeconomic conditions, health-seeking behavior, and behavioral patterns, and these differences might aggravate the risk for developing these conditions and accelerating their complications. Without a clear, evidence-based understanding of where and how disparities exist, public health interventions and clinical programs risk being misdirected, inefficient, or inequitable. Consequently, there is an urgent need for localized research that systematically compares hypertension-related indicators among diabetic adults across rural and urban settings to inform targeted, effective, and equitable health policies and programs. Therefore, this study aims to investigate these disparities in the Northern State of Sudan. The findings will provide basic evidence to inform equitable and effective major health policies and interventions aimed at reducing the hypertension burden in this high-risk population.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003eStudy Design and setting\u003c/p\u003e\n\u003cp\u003eThis research employed a community-based, analytical cross-sectional study design. The cross-sectional design was chosen as it is effective for determining the prevalence of hypertension and associated factors (awareness, treatment, control) at a single point in time and for making comparisons between groups (rural vs. urban).\u003c/p\u003e\n\u003cp\u003eThe study was conducted in the Northern State, one of Sudan's 18 states located in the far north, about 328 km north of Khartoum, the capital of Sudan, bordering Egypt and Libya. It has an area of 348,876 km² and an estimated population of 1,132,000. It is characterized by a predominantly arid landscape and its position along the River Nile bank [13, 14]. The Northern State is divided into 7 localities: Wadi Halfa, Dalgo, Al-Burgaig, Dongola, Al-Golid, Al-Dabbah, and Merowe [13]. The state has been impacted by the internal displacement of thousands of people (13% of the internally displaced) due to the recent war conflict between the Sudanese Armed Forces and the Rapid Support Forces [15, 16].\u003c/p\u003e\n\u003cp\u003eStudy Population\u003c/p\u003e\n\u003cp\u003eThe target populations of this study were selected according to fallowing criteria:\u003c/p\u003e\n\u003cp\u003eInclusion Criteria:\u003c/p\u003e\n\u003cp\u003e1. Adult aged 18 years or above.\u003c/p\u003e\n\u003cp\u003e2. Confirmed diagnosis of diabetes mellitus by a physician or based on self-report with evidence of medication use.\u003c/p\u003e\n\u003cp\u003e3. Permanent resident of the Northern State (≥1 year).\u003c/p\u003e\n\u003cp\u003eExclusion Criteria:\u003c/p\u003e\n\u003cp\u003e1. Internally displaced people from other states due to the war conflict.\u003c/p\u003e\n\u003cp\u003e2. Pregnant women due to physiological changes in Blood Pressure (BP).\u003c/p\u003e\n\u003cp\u003e3. Individuals with severe mental illness or cognitive impairment preventing informed consent or a reliable interview.\u003c/p\u003e\n\u003cp\u003e4. Critically ill individuals or those unable to participate in the interview or measurements.\u003c/p\u003e\n\u003cp\u003eSampling\u003c/p\u003e\n\u003cp\u003eThe sample size was calculated using the Cochran formula, with a 95% confidence level, a 4% margin of error, and a 70% estimated prevalence of\u0026nbsp;hypertension among diabetics [9].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003en = Z\u003csup\u003e2\u003c/sup\u003e* p(1-p)/e\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003en = minimum required sample size.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ee= desired margin of error (4%).\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eP = estimated population proportion, prevalence of hypertension in diabetic (70%).\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eZ = Z-score for 95% confidence level (1.96).\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccounting for a potential non-response rate of 10%, the final minimum sample size was adjusted to 555 participants. The study successfully enrolled 595 participants.\u003c/p\u003e\n\u003cp\u003eSampling Technique\u003c/p\u003e\n\u003cp\u003eA multi-stage stratified random sampling technique was used to ensure representativeness across rural and urban populations:\u003c/p\u003e\n\u003cp\u003e• Stage 1: Locality Selection: Three of the seven localities were selected by simple random sampling technique. The selected localities were Dongola, Al-Burgaig, and Merowe.\u003c/p\u003e\n\u003cp\u003e• Stage 2: Stratification by Location: Each locality was divided into urban and rural strata. Lists of different villages and cities were obtained from the official registries of the administrative unit of each locality. The capital city of the locality was non-randomly selected to represent the urban population as it is the biggest city with the largest urban population. Three villages from each locality were selected by a simple random selection technique to represent the rural population.\u003c/p\u003e\n\u003cp\u003e• Stage 3: Selection of Clusters: A number of communities or neighborhoods were randomly selected from each stratum.\u003c/p\u003e\n\u003cp\u003e• Stage 4: Household Selection: Within each selected community, households were selected by systematic random sampling.\u003c/p\u003e\n\u003cp\u003e• Stage 5: Individual Participant Selection: In each household, all adult diabetic patients meeting the inclusion criteria were selected.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods of Data Collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data were collected over a two-month period by a team of trained data collectors (senior medical students). An interviewer-administered structured questionnaire was devolved for this study, used to gather data on sociodemographic factors, diabetes-related history (type of diabetes, duration since diagnosis, current treatment, self-reported adherence, and last known glycated hemoglobin (HbA1c) result), hypertension-related data (awareness of hypertension diagnosis, duration, family history, knowledge of the diabetes-hypertension relationship, current antihypertensive medication, self-reported adherence, and self-monitoring behaviors), and lifestyle and behavioral factors (smoking status, alcohol use, and physical activity),[supplementary file 1].\u003c/p\u003e\n\u003cp\u003eBlood pressure measurements were obtained using calibrated mercury sphygmomanometers fitted with an appropriate cuff size, following the American Heart Association's recommended procedures [17]. For each participant, three consecutive readings were taken on the right arm at two-minute intervals, with the individual seated comfortably and the arm properly supported. The final blood pressure was determined by calculating the mean of these three measurements. Hypertension was defined as a mean systolic pressure of 140 mmHg or higher, a mean diastolic pressure of 90 mmHg or higher, or current pharmacological treatment for a previously established diagnosis. Among hypertensive individuals, controlled blood pressure was defined as an average below 140/90 mmHg. Additionally, participants without a prior diagnosis of hypertension who were found to have an average reading of 140/90 mmHg or higher were classified as having undiagnosed hypertension.\u003c/p\u003e\n\u003cp\u003eParticipant weight was recorded to the closest 0.1 kg using a digital scale while they wore light clothing. Height was measurement was taken to closest 0.1 cm using a portable stadiometer. Body mass index (BMI) was calculated using the standard formula (kg/m²).\u003c/p\u003e\n\u003cp\u003eThe last HbA1c level, or the last blood glucose level if HbA1c was unavailable, was obtained from the participants. The patient was considered to have uncontrolled diabetes mellitus (DM) if their last HbA1c was ≥7% (53 mmol/mol) or their last blood glucose was ≥140 mg/dl (7.8 mmol/l).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Preparation and Presentation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompleted questionnaires were checked daily for completeness and consistency by field supervisors. Data were then entered into Microsoft Excel software with double-entry verification to minimize errors. The cleaned dataset was exported to the Statistical Package for the Social Sciences (SPSS) version 27 (IBM) for analysis by a professional data analyst. Results are presented using tables, bar charts, and pie charts for clarity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1. Descriptive Statistics: Frequencies and percentages were used to describe categorical variables (e.g., sex, residence, awareness status). Means and standard deviations were used for continuous variables (e.g., age, BMI, BP).\u003c/p\u003e\n\u003cp\u003e2. Analytical Statistics:\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp;• Group Comparisons: Chi-square tests (or Fisher's exact test) were used to compare categorical outcomes (prevalence, awareness, treatment, control) between rural and urban groups. Independent samples t-tests (or Mann-Whitney U tests for non-normal data) were used to compare continuous variables (e.g., mean BP, BMI, and HbA1c) between the two groups. Analysis of Variance (ANOVA) was also employed for multi-group comparisons as shown in the results.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp;• A p-value of \u0026lt;0.05 was considered statistically significant for all tests.\u003c/p\u003e"},{"header":"3.\tResults","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 1.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eSocio-demographic Characteristics of the adult diabetic patients, (total number = 595).\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003cp\u003e(n =320)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003cp\u003e(n = 275)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003cp\u003e(n =595)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eF*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eF*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e233 (39.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.917\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e60.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e60.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e362 (60.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18-39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003cp\u003e(8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e0.981\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e40-59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e47.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e47.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e284 (47.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026gt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e43.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e44.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e261 (43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\"\u003e\n \u003cp\u003eOccupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNot working\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e102 (17.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHousewife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e43.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e43.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e258 (43.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSelf-employed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e140 (23.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGovernment sector\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72 (12.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePrivate sector\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eEducational Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eIlliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e77 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePre-university\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e69.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e69.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e414 (69.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUniversity or higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e104 (17.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eMarital Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e538 (90.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.964\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e57 (9.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eIncome Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInsufficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e45.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e46.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e274 (46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.879\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSufficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e54.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e53.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e321 (54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eFamily Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026le;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e43.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e43.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e258 (43.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.949\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026gt;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e56.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e56.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e337 (56.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eNumber of Family Members with Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026le;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e92.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e92.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e549 (92.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.944\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026gt;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eBody Mass Index (BMI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026le;30.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e66.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e66.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e397 (66.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.882\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026gt;30.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e198 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eRegular Exercise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e54.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e53.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e321 (54%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.906\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e45.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e46.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e274 (46%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eConsumption of Foods\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHigh Salts intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e41.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e41.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e246 (41.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.879\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAdequate Fruits/Vegetables intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e84.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e84.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e349 (58.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18 (3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.975\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e96.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e97.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e577 (97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eKnowledge of Link Between Diabetes and Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e64.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e64.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e443 (74.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.975\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e152 (25.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eFamily History of Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e66.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e66.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e396 (66.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.975\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e199 (33.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e*F= Frequency\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe total number of participants was 595, urban participants constituted 320 (53.8%), while females were 362 (60.8%). There was no significant difference between the rural and urban participants with regards to socio-demographic characteristics as shown in Table 1. The sample was demographically homogeneous between urban and rural areas; predominantly females, married, housewives, with intermediate education, had limited income, knew the link between hypertension and diabetes and had positive family history of hypertension.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 2.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eDiabetes-Related Characteristics by Residence, (total number = 595).\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003cp\u003e(n=320)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003cp\u003e(n=275)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003cp\u003e(n =595)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eType of Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eType 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54 (9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eType 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e57.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e57.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e340 (57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUnsure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e201 (33.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eDuration Since Diagnosis (Years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026le;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e48.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e48.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e288 (48.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e0.976\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e11-20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e210 (35.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026gt;20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e97 (16.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003eCurrent Treatments Used\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDiet only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21 (3.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e0.964\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOral tablets\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e67.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e67.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e400 (67.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eInsulin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e154(25.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eInsulin + Oral tablets\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20 \u0026nbsp; (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eAdherence to Diabetes Treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e82.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e228\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e82.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e493 (82.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.994\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e102 (17.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003eBlood Sugar Monitoring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eBlood glucose level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e41.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e41.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e247 (41.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e0.975\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHbA1c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e45.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e46.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e274 (46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDid not monitor blood sugar\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e74 (12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eLatest HbA1c/ estimated A1c (Among those tested)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eControlled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e160* (30.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.899\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUncontrolled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e62.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e62.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e327* (62.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e*among 521 of participants (monitoring blood sugar), 14 of them did not remember their last HbA1c, and 20 did not remember last blood glucose\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWith regards to clinical, treatment and laboratory related characteristics of the study participants as demonstrated in Table 2, no statistically significant differences were found between urban and rural diabetic patients. The high proportion of \u0026quot;Unsure\u0026quot; regarding the type of diabetes might indicate poor knowledge or differentiation between diabetic types, necessitating better education. More than half of the patients were taking oral anti-diabetic medications, a high proportion (83%) were adherent to their medication but near two-thirds had poor glycemic control.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 3.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eCharacteristics of hypertension by residence, (total number = 595).\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003cp\u003e(n=320)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003cp\u003e(n=275)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eDiagnosed with Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e42.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e42.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e255 (42.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.964\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e57.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e57.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e340 (57.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eDuration Since Hypertension Diagnosis (Years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026le;15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e72.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e72.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e184 (72.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.887\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026gt;15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e71 (27.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eAdherence to Hypertension Treatment (among diagnosed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e86.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e86.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e220 (86.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.938\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35 (13.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eAttendance at Regular Follow-up (among diagnosed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e66.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e66.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e169 (66.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.924\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e86 (33.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eHypertension Complications (among diagnosed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58 (22.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.924\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e77.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e77.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e197 (77.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003eType of Complication (among those with complications)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCardiovascular\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e61.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e59.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35 (60.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e0.924\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRenal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12(20.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCerebral hemorrhage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (12%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMultiple complications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 (6.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3 demonstrates the prevalence and clinical characteristics of hypertension among the study population. Participants already diagnosed with hypertension comprised about 43%, with good adherence to treatment and regular follow up. There were no statistically significant differences between rural and urban participants.\u003c/p\u003e\n\u003cp\u003eAmong all participants who were not known hypertensive, 146/340 (42.9%) had high blood pressure (\u0026ge;140/90), making the total number of participants with hypertension to be 401 (67.4%), this is demonstrated in\u0026nbsp;Figure 1. The overall awareness rate of hypertension (known hypertensive/Total hypertensive%) was 63.6%.\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 4.\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eMean systolic and diastolic blood pressure levels among rural and urban, (total number=595).\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean Systolic (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eStandard Deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMean Diastolic (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eStandard Deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAll Patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e137.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e19.5\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e83.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e135.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e81.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e139.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e84.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDiagnosed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e144.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e85.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUndiagnosed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e130.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e78.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDiagnosed (Urban)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e140.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e84.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDiagnosed (Rural)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e145.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e88.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUndiagnosed (Urban)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e130.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e78.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.449\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUndiagnosed (Rural)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e131.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e80.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe mean blood pressure levels (systolic \u0026amp; Diastolic) were higher among rural compared to urban population and were also higher among known hypertensive individuals compared to newly diagnosed participants as shown in Table 4.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTable 5.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003eBlood pressure parameters among rural and urban, (total number = 595).\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eCurrent BP Reading for All Participants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;140/90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e60.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e60.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e357 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.975\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge;140/90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e40.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e40.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e238 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eHypertensive Patients (Diagnosed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eControlled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e31.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e86 (33.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.966\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUncontrolled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e64.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e68.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e169 (66.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eUndiagnosed for Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNormal BP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e58.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e55.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e194 (57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e0.908\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eElevated Undiagnosed (Unaware)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e40.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e45.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e146 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e\n \u003cp\u003eTotal number of hypertensive (known + new) is 401 (67.4%, n = 595)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAwareness Rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eKnown hypertensive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e64.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e62.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e255 (63.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.959\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUnawareness rate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNewly diagnosed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e146 (36.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNearly two third \u0026nbsp;of diagnosed individuals 66.3% had uncontrolled BP despite good treatment adherence, but regular follow-up and consistent BP measurement were less than optimal, which may explain why they were uncontrolled. Complications were not rare, about 23% of known hypertensive patients developed complications related to hypertension that necessitates intensified prevention efforts. The overall awareness rate of hypertension was 63.6%. There were no statistically significant differences between rural and urban participants with regards to blood pressure levels, control rate and undiagnosed hypertension as demonstrated in Table 5.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of Hypertension\u003c/h2\u003e \u003cp\u003eThe overall prevalence of hypertension was 67.4% (comprising 42.9% previously diagnosed plus 24.5% newly discovered cases). This aligns closely with global estimates that hypertension affects approximately 70% of patients with diabetes [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], and is close to Middle East and North Africa (MENA) data, which reports a pooled prevalence of 56% among diabetic patients [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. A multinational study from the Middle East and Africa cohort similarly found that over 40% of diabetic patients had hypertension [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Nationally, our findings showed a high prevalence of hypertension among diabetic patients, comparable to previous Sudanese studies reporting 47.7% in a survey at a diabetes healthcare facility [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and 47.4% prevalence among diabetics in El-Gezira State [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], as well as 47.6% in northern Sudan [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The slightly higher rate in our study may reflect the inclusion of undiagnosed cases identified through active blood pressure measurement. This may also be explained by the increasing prevalence of diabetes in the MENA region and in Sudan [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur findings on management reveal both strengths and gaps. The high treatment adherence rates for hypertension 86.3% and diabetes 82.8% are commendable and exceed those often reported in similar resource-limited settings and are even higher than in some high-income areas [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Even with high treatment adherence, disease control was suboptimal; 66.3% of hypertensive patients had uncontrolled BP (Rural: 68.4% vs. Urban: 64.5%, p\u0026thinsp;=\u0026thinsp;0.966). The predominant use of monotherapy (amlodipine-based, 72.9% of hypertensive patients) aligns with standard first-line treatment protocols [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe most striking and potentially important finding is the lack of statistically significant differences between urban and rural residents across most parameters: HTN prevalence, treatment complexity, awareness rate, and achieved blood pressure control. This contrasts with the common paradigm of a health access gap favoring urban areas.\u003c/p\u003e \u003cp\u003eHypertension prevalence was nearly identical among previously diagnosed patients (urban: 42.8% vs. rural: 42.9%, p\u0026thinsp;=\u0026thinsp;0.964). Blood pressure control rates among diagnosed hypertensive patients showed no statistical difference (urban: 35.5% vs. rural: 31.6%, p\u0026thinsp;=\u0026thinsp;0.966). Furthermore, the proportion of undiagnosed hypertension (those with blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;140/90 mmHg who were considered unaware) was slightly higher in the rural area, with no statistically significant differences (urban: 40.5% vs. rural: 45.8%, p\u0026thinsp;=\u0026thinsp;0.908).\u003c/p\u003e \u003cp\u003eThis homogeneity contrasts with global literature, which often demonstrates significant urban-rural gradients. For example, a meta-analysis of 62 studies involving 108,110 participants found that slum residents were 35% more likely to be hypertensive than rural dwellers [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Other research has shown that awareness and treatment were significantly lower in rural compared to urban communities in low-income countries [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, our findings align with recent meta-analyses demonstrating narrowing urban-rural differences in low-income countries, from 5.75% (1990\u0026ndash;2004) to 1.38% (2005\u0026ndash;2020) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The absence of disparities in our study may reflect an epidemiological transition, demographic similarity, and equitable health information access in Northern Sudan. The overall awareness rate 63.6% substantially exceeded the 46.5% reported in the multinational Prospective Urban Rural Epidemiology (PURE) study and the 40.8% observed in low-income countries. Treatment adherence among aware individuals 86.3% was comparable to the 87.5% in PURE. However, uncontrolled blood pressure among treated patients 66.3% is double the global challenge (32.5% in PURE). Monotherapy predominated 73%, mainly amlodipine 72.9%, contrasting with PURE, where 30.8% received combination therapy. The 42.9% undiagnosed hypertension patients remains concerning and aligns with the 46.5% awareness gap reported globally [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eFactors Associated with Hypertension and Poor Control\u003c/h2\u003e \u003cp\u003eConsistent with the literature, age (91.6% \u0026gt;40 years) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], obesity (33% with BMI\u0026thinsp;\u0026gt;\u0026thinsp;30) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], physical inactivity (46%), high salt intake (41%), and family history (66%) were prevalent. Importantly, 34% of diagnosed patients lacked regular follow-up, and 40.4% had not measured their BP for \u0026gt;\u0026thinsp;3 weeks, explaining the 68.4% uncontrolled rate despite high reported adherence. Complications affected 23% (60% cardiovascular), underscoring the clinical significance of optimal control [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and consistent with the association between hypertension and retinopathy reported nationally [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eThe cross-sectional design prevents causal inference, and single-state conduct limits generalizability. Self-reported data (adherence, lifestyle) are subject to recall and social desirability bias, as evidenced by the discordance between high reported adherence (\u0026gt;\u0026thinsp;80%) and poor objective control (66% uncontrolled BP). Non random selection of capital cities to represent urban areas may have introduced selection bias. Reliance on recalled HbA1c with 6% missing data compromises glycemic control assessment. These limitations highlight the need for longitudinal studies with objective measures and broader population inclusion.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates a high prevalence of hypertension among diabetic adults in Northern Sudan. Contrary to expectations, a significant urban-rural disparity was absent in prevalence, awareness, treatment adherence, or control rates. While the awareness rate 63.6% and treatment adherence (86.3%) are commendable, control remains suboptimal, with 66.3% having uncontrolled hypertension, and 36.4% of hypertension cases remaining undiagnosed.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAHA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmerican Heart Association\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eANOVA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAnalysis of Variance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBlood Pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eDM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDiabetes Mellitus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHbA1c\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlycated Hemoglobin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHTN\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIDF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Diabetes Federation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLMICs\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLow- and Middle-Income Countries\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMENA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMiddle East and North Africa\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003emmHg\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMillimeters of Mercury\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePURE\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eProspective Urban Rural Epidemiology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSPSS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStatistical Package for the Social Sciences\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eT1DM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eType 1 Diabetes Mellitus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eT2DM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eType 2 Diabetes Mellitus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in Accordance with the principles of the Declaration of Helsinki. Prior to the commencement of the study, ethical clearance was obtained from the Community Medicine Department, Faculty of Medicine, University of Dongola, as well as from the Ethics Committee of the Northern State Ministry of Health for each locality as they requested (Approval ID not applicable). Permissions were obtained from the administrative personnel and community leaders of each selected locality, city, or village. Written informed consent was obtained from every participant after a detailed explanation of the study's purpose, procedures, potential benefits (free BP check and referral if needed), and risks (minimal, related to time and discomfort from the BP cuff), in a language they understand, informed consent for illiterate participants obtained from their legal guardians. All participants were assured of the confidentiality of their personal information, and their right to withdraw from the study at any time without any consequences. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data \u003c/p\u003e\n\u003cp\u003eThe Dataset used and analyzed during the current study, are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests \u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe authors and participants did not receive any type of funding for this study.\u003c/p\u003e\n\u003cp\u003eAuthors' Contributions\u003c/p\u003e\n\u003cp\u003eAl-Mowafag Anwer Omer and Mohamed Osman Abdelaziz; developed the research concept, and drafted and reviewed the study reports and manuscript. Roaa Ebrahim Bashir, Moshtaha Emadeldin, Asma Siddeeg, Haniss Mustafa, Asma Mahmoud, and Selsabeel Abd Alraheim; designed the data collection process and revising the manuscript. Outhman Alsadiq performed the statistical analysis and interpreted the data. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank all the participants from all rural and urban areas of the Northern State. They would also like to thank the administrators of the State Ministry of Health, the three localities, as well as the villages and cities included in the study. Many thanks to the local community leaders who facilitated and helped the data collectors.\u003c/p\u003e\n\u003cp\u003eAuthor information\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAl-Mowafag Anwer Omer\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMohamed Osman Abdelaziz\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e Roaa Ebrahim Bashir\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e Moshtha Emadeldin\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e4\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAsma Siddeeg\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e5\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e Haniss Mustafa\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e6\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAsma Mahmoud\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e7\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSelsabeel Abd Alrahim\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e Outhman Alsadiq\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e9\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003eMedical Student, Faculty of Medicine, University of Dongola. E-mail: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003eMD,Professor, Head Department of Internal Medicine, Faculty of Medicine, University of Dongola. E-mail: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/strong\u003eInternal Medicine Registrar (SMSB), Lecturer, Department of Internal Medicine, Faculty of Medicine, University of Dongola. E-mail: [email protected] \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e4\u003c/sup\u003e\u003c/strong\u003e Medical Student, Faculty of Medicine, University of Dongola. E-mail: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e5\u003c/sup\u003e\u003c/strong\u003e Medical Student, Faculty of Medicine, University of Dongola. E-mail: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e6\u003c/sup\u003e\u003c/strong\u003e Medical Student, Faculty of Medicine, University of Dongola. E-mail: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e7\u003c/sup\u003e\u003c/strong\u003eMedical Student, Faculty of Medicine, University of Dongola. E-mail: [email protected] \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e8\u003c/sup\u003e\u003c/strong\u003e Medical Student, Faculty of Medicine, University of Dongola. E-mail: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003csup\u003e9\u003c/sup\u003e\u003c/strong\u003eAssistant Professor, Faculty of Economic and Administrative Sciences, University of Dongola. E-mail:[email protected]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRoglic G. WHO Global report on diabetes: A summary. Int J Noncommunicable Dis 2016 Apr-Jun;1(1):3\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/2468-8827.184853\u003c/span\u003e\u003cspan address=\"10.4103/2468-8827.184853\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHossain MJ, Al-Mamun M, Islam MR. Diabetes mellitus, the fastest growing global public health concern: Early detection should be focused. Health Sci Rep. 2024;7(3):e2004. doi: 10.1002/hsr2.2004. PMID: 38524769; PMCID: PMC10958528.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInternational Diabetes Federation. IDF Atlas 11th Edition. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://diabetesatlas.org/resources/idf-diabetes-atlas-2025/\u003c/span\u003e\u003cspan address=\"https://diabetesatlas.org/resources/idf-diabetes-atlas-2025/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e [Accessed 1st September 2025].\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInternational Diabetes Federation. Middle East and North Africa: diabetes report 2000\u0026ndash;2050. In: IDF Diabetes Atlas, 11th ed. Brussels: International Diabetes Federation. 2025. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://diabetesatlas.org/data-by-location/region/middle-east-and-north-africa\u003c/span\u003e\u003cspan address=\"https://diabetesatlas.org/data-by-location/region/middle-east-and-north-africa\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e [Accessed 1st September 2025].\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStaessen JA, Wang J, Bianchi G, Birkenh\u0026auml;ger WH. Essential hypertension. Lancet. 2003;361(9369):1629-41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(03)13302-8\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(03)13302-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 12747893.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMills KT, Stefanescu A, He J. The global epidemiology of hypertension. Nat Rev Nephrol. 2020;16(4):223\u0026ndash;37. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41581-019-0244-2\u003c/span\u003e\u003cspan address=\"10.1038/s41581-019-0244-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2020 Feb 5. PMID: 32024986; PMCID: PMC7998524.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrossman E, Messerli FH. Hypertension and diabetes. In: Fishman EZ, Tenenbaum A, editors. Cardiovascular Diabetology: Clinical, Metabolic and Inflammatory Facets. Advances in Cardiology. Volume 45. Basel: Karger; 2008. pp. 82\u0026ndash;106. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1159/isbn.978-3-8055-8428-9\u003c/span\u003e\u003cspan address=\"10.1159/isbn.978-3-8055-8428-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSimonson DC. Etiology and prevalence of hypertension in diabetic patients. Diabetes Care. 1988 Nov-Dec;11(10):821\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2337/diacare.11.10.821\u003c/span\u003e\u003cspan address=\"10.2337/diacare.11.10.821\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHezam AA, Mohammed1;, Shaghdar, Hanan Basheer Mohammed2, Chen. Liying2. The connection between hypertension and diabetes and their role in heart and kidney disease development. Journal of Research in Medical Sciences 29(1):22, April 2024. | \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/jrms.jrms_470_23\u003c/span\u003e\u003cspan address=\"10.4103/jrms.jrms_470_23\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbdelbagi O, Musa IR, Musa SM, ALtigani SA, Adam I. Prevalence and associated factors of hypertension among adults with diabetes mellitus in northern Sudan: a cross-sectional study. BMC Cardiovasc Disord. 2021;21(1):168. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12872-021-01983-x\u003c/span\u003e\u003cspan address=\"10.1186/s12872-021-01983-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 33838664; PMCID: PMC8037914.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlmobarak AO, Badi S, Siddiq SB, Noor SM, Elmadhoun WM, Suliman M, Ahmed MH. The prevalence and risk factors for systemic hypertension among Sudanese patients with diabetes mellitus: a survey in diabetes healthcare facility. Diabetes Metab Syndr. 2020 Nov-Dec;14(6):1607\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.dsx.2020.08.010\u003c/span\u003e\u003cspan address=\"10.1016/j.dsx.2020.08.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVenkatesh U, Grover A, Vignitha B, Ghai G, Malhotra S, Kishore J, Jaswal N, Yashwanth RD, Durga R, Goel S, Kishore S. Urban-rural disparities in blood pressure and lifestyle risk factors of hypertension among Indian individuals. J Family Med Prim Care. 2022;11(9):5746\u0026ndash;56. Epub 2022 Oct 14. PMID: 36505536; PMCID: PMC9730999.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNorthern State Government [Internet]. Sudan: Alshmalia State Government; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.alshamaliastate.gov.sd/\u003c/span\u003e\u003cspan address=\"https://www.alshamaliastate.gov.sd/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e [Accessed 11th March 2026].\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCentral Bureau of Statistics (Sudan). Population projections for Sudan 2025 [Internet]. Khartoum: Central Bureau of Statistics. 2025. Table 3.5. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://drive.google.com/file/d/1VplW60uDgAn5OyhDS9UN_fp75OwG0IFt/view\u003c/span\u003e\u003cspan address=\"https://drive.google.com/file/d/1VplW60uDgAn5OyhDS9UN_fp75OwG0IFt/view\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e [Accessed 28th August 2025].\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMigration Policy Centre. Overview of displacement in Sudan: the causes, dynamics and consequences [Internet]. Florence: Migration Policy Centre; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://migrationpolicycentre.eu/overview-of-displacement-in-sudan-the-causes-dynamics-and-consequences/\u003c/span\u003e\u003cspan address=\"https://migrationpolicycentre.eu/overview-of-displacement-in-sudan-the-causes-dynamics-and-consequences/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e [Accessed 8th March 2026].\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInternal Displacement Monitoring Centre. Sudan: the world's largest internal displacement crisis deepens [Internet]. Geneva: Internal Displacement Monitoring Centre. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.internal-displacement.org/spotlights/sudan-the-world-s-largest-internal-displacement-crisis-deepens/\u003c/span\u003e\u003cspan address=\"https://www.internal-displacement.org/spotlights/sudan-the-world-s-largest-internal-displacement-crisis-deepens/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e [Accessed 8th March 2026].\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJones DW, Ferdinand KC, Taler SJ, Johnson HM et al. 2025 AHA/ACC/AANP/\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003eAAPA/ABC/ACCP/ACPM/AGS/AMA/ASPC/NMA/PCNA/SGIM\u003c/span\u003e\u003cspan address=\"http://AAPA/ABC/ACCP/ACPM/AGS/AMA/ASPC/NMA/PCNA/SGIM\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Guideline for the Prevention, Detection, Evaluation and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Hypertension. 2025;82(10):e212-e316. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/HYP.0000000000000249\u003c/span\u003e\u003cspan address=\"10.1161/HYP.0000000000000249\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2025 Aug 14. Erratum in: Hypertension. 2025;82(12):e350. doi: 10.1161/HYP.0000000000000257. PMID: 40811516.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLago RM, Singh PP, Nesto RW. Diabetes and hypertension. Nat Clin Pract Endocrinol Metab. 2007;3(10):667. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/ncpendmet0638\u003c/span\u003e\u003cspan address=\"10.1038/ncpendmet0638\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 17893686.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhalil SA, Azar S, Hafidh K, Ayad G, Safwat M. Prevalence and co-prevalence of comorbidities among patients with type 2 diabetes mellitus in the MENA region: a systematic review. Curr Diabetes Rev. 2024;20(7):e310723219277. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2174/1573399820666230731105704\u003c/span\u003e\u003cspan address=\"10.2174/1573399820666230731105704\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 37526192; PMCID: PMC11092551.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHafidh K, Malek R, Al-Rubeaan K, Kok A, Bayram F, Echtay A, Rajadhyaksha V, Hadaoui A. Prevalence and risk factors of vascular complications in type 2 diabetes mellitus: results from the DISCOVER Middle East and Africa cohort. Front Endocrinol (Lausanne). 2022;13:940309. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fendo.2022.940309\u003c/span\u003e\u003cspan address=\"10.3389/fendo.2022.940309\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 36017310; PMCID: PMC9396276.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOmer SA, Elamin MFM, Mahgoub AMA, et al. Prevalence and associated risk factors of hypertension among adults with diabetes mellitus in Wad-Medani, Gezira State, Sudan: A cross-sectional study. Biomed J Sci Tech Res (BJSTR). 2024;58(5). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.26717/BJSTR.2024.58.009228\u003c/span\u003e\u003cspan address=\"10.26717/BJSTR.2024.58.009228\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Article ID: BJSTR.MS.ID.009228.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInternational Diabetes Federation. Sudan: diabetes country report 2000\u0026ndash;2050 [Internet]. In: IDF Diabetes Atlas, 11th ed. Brussels: International Diabetes Federation. 2025. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://diabetesatlas.org/data-by-location/country/sudan/\u003c/span\u003e\u003cspan address=\"https://diabetesatlas.org/data-by-location/country/sudan/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e [Accessed 8th March 2026].\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlgabbani FM, Algabbani AM. Treatment adherence among patients with hypertension: findings from a cross-sectional study. Clin Hypertens. 2020;26:18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s40885-020-00151-1\u003c/span\u003e\u003cspan address=\"10.1186/s40885-020-00151-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 32944283; PMCID: PMC7491181.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUthman OA, Ayorinde A, Oyebode O, Sartori J, Gill P, Lilford RJ. Global prevalence and trends in hypertension and type 2 diabetes mellitus among slum residents: a systematic review and meta-analysis. BMJ Open. 2022;12(2):e052393. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjopen-2021-052393\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2021-052393\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 35210339; PMCID: PMC8883228.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChow CK, Teo KK, Rangarajan S, Islam S, Gupta R, Avezum A et al. PURE (Prospective Urban Rural Epidemiology) Study investigators. Prevalence, awareness, treatment, and control of hypertension in rural and urban communities in high-, middle-, and low-income countries. JAMA. 2013;310(9):959\u0026thinsp;\u0026ndash;\u0026thinsp;68. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jama.2013.184182\u003c/span\u003e\u003cspan address=\"10.1001/jama.2013.184182\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 24002282.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRanzani OT, Kalra A, Di Girolamo C, Curto A, Valerio F, Halonen JI, et al. Urban-rural differences in hypertension prevalence in low-income and middle-income countries, 1990\u0026ndash;2020: a systematic review and meta-analysis. PLoS Med. 2022;19(8):e1004079. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pmed.1004079\u003c/span\u003e\u003cspan address=\"10.1371/journal.pmed.1004079\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 36007101; PMCID: PMC9410549.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNaseri MW, Esmat HA, Bahee MD. Prevalence of hypertension in type 2 diabetes mellitus. Ann Med Surg (Lond). 2022;78:103758. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.amsu.2022.103758\u003c/span\u003e\u003cspan address=\"10.1016/j.amsu.2022.103758\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 35620043; PMCID: PMC9127167.\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":"Awareness, Control, Diabetes mellitus, Hypertension, Northern State, Prevalence, Sudan, Urban-Rural Disparities","lastPublishedDoi":"10.21203/rs.3.rs-9173542/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9173542/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDiabetes and hypertension constitute a dual public health burden, particularly in low-income countries. While urban-rural disparities in healthcare access are well documented, this study aims to compare the prevalence, awareness, treatment, and control of hypertension among adult diabetic patients in rural and urban areas of Northern State, Sudan, in 2026.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA community-based analytical cross-sectional study was conducted among 595 diabetic adults (320 urban, 275 rural) selected via multi-stage stratified random sampling. Data were collected using interviewer-administered questionnaires and clinical measurements following standardized protocols. Hypertension was defined as systolic blood pressure ≥ 140 mmHg and/or diastolic ≥ 90 mmHg, or current antihypertensive medication use.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overall prevalence of hypertension was 67.4% (401/595), comprising 42.8% previously diagnosed and 24.5% newly discovered cases. Contrary to expectations, no significant urban-rural differences were observed across all measured parameters: hypertension prevalence of previously diagnosed (42.9% vs. 42.8%, p = 0.964), awareness (62.1% vs. 64.9%, p = 0.959), treatment adherence (86.4% vs. 86.1%, p = 0.938), or blood pressure control among diagnosed patients (31.6% vs. 35.5%, p = 0.966). Despite high treatment adherence, 66.3% of hypertensive patients had uncontrolled blood pressure, and 36.4% of all hypertensive patients remained undiagnosed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHypertension affects two-thirds of diabetic adults in Northern State, Sudan, with over one-third of cases unrecognized and two-thirds uncontrolled. The absence of significant urban-rural disparities in disease burden or management challenges conventional assumptions about healthcare access gaps and supports population-based interventions targeting all diabetic patients, regardless of geographic location.\u003c/p\u003e\n\u003cp\u003eClinical trial number: Not applicable\u003c/p\u003e","manuscriptTitle":"Urban-Rural Disparities in the Prevalence, Awareness, Treatment, and Control of Hypertension among Adult Diabetic Patients in Northern State, Sudan: A cross sectional Analytical Community-based Study, 2026","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 12:21:21","doi":"10.21203/rs.3.rs-9173542/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-03T22:00:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"24530193552964344747394509831072410403","date":"2026-04-16T21:18:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-15T07:03:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-13T14:36:14+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-25T18:01:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-25T13:14:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-03-25T13:08:20+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":"198db9f2-48d9-4b39-9abc-49c3da2ea039","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-03T22:00:59+00:00","index":76,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-23T12:21:21+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 12:21:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9173542","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9173542","identity":"rs-9173542","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}