The Effect of Dietary Fiber Intake on Blood Pressure Control among Type 2 Diabetic Patients in Selected Hospitals of Addis Ababa, Ethiopia: A Multi-Facility Cross-Sectional Study

The Effect of Dietary Fiber Intake on Blood Pressure Control among Type 2 Diabetic Patients in Selected Hospitals of Addis Ababa, Ethiopia: A Multi-Facility Cross-Sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The Effect of Dietary Fiber Intake on Blood Pressure Control among Type 2 Diabetic Patients in Selected Hospitals of Addis Ababa, Ethiopia: A Multi-Facility Cross-Sectional Study Feven Hailu, Jemal Haidar Ali, Yakob Desalegn Nigatu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7227814/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Background Consuming dietary fiber can contribute to a healthy diet and potentially safeguard the cardiovascular system. However, contextual data on this relationship are limited. Therefore, this study examined the role of dietary fiber intake on blood pressure control among Type 2 diabetic patients in selected facilities. Methods An institutional-based cross-sectional study design was conducted from March to April 2024. A total of 287 Type 2 DM patients were selected from health facilities in Addis Ababa using the multistage sampling. Data on blood pressure, fasting blood glucose, and other important variables were collected from all participants via the KOBO Collect mobile app. Dietary data were obtained through a repeated multiple-pass 24-hour recall, with portion sizes estimated and analyzed into nutrients using Nutri survey 2007. Data analysis was performed using SPSS version 27. Result A significant proportion (79.4%) of respondents exhibited poor blood pressure control, while over half (56.7%) demonstrated poor glycemic control. Additionally, 10.3% of participants were classified as obese, and 39% had stage 2 hypertension. The mean dietary fiber intake was 32.5 ± 20 g/day. An inverse correlation was observed between dietary fiber intake and blood pressure (BP), body mass index (BMI), and HbA1c levels. Furthermore, exercise and dietary fiber intake were significantly associated with better blood pressure control (p < 0.005). Conclusion Our findings illuminated the significant benefits of dietary fiber intake in managing blood pressure and glycemic control among individuals with multiple comorbidities. These results underscore the urgent need for targeted public health initiatives to promote healthy diets as a key strategy in preventing cardiovascular diseases. Health sciences/Diseases Health sciences/Endocrinology Health sciences/Health care Health sciences/Medical research Health sciences/Risk factors Dietary fiber intake hypertension glycemic control diabetes mellitus Addis Ababa Figures Figure 1 Figure 2 Figure 3 Introduction Cardiovascular diseases (CVDs) encompass a range of disorders affecting the heart and blood vessels, including coronary heart disease, cerebrovascular disease, and congenital heart defects ( 1 ). They are the leading cause of death globally, with approximately 17.9 million deaths reported in 2019, escalating to around 20.5 million by 2021, and accounted for nearly one-third of all fatalities ( 2 ). Risk factors for CVDs are classified as non-modifiable factors like age, gender, and family history, and modifiable factors such as sedentary lifestyles and poor dietary practices. This highlights the urgent need for targeted public health initiatives to address these risk factors, particularly emphasizing the importance of promoting a healthy diet that includes dietary fiber as a key strategy in preventing cardiovascular diseases ( 1 ). Among the various parameters, the key physiological indicator used to evaluate cardiovascular health is blood pressure ( 3 ).This measure reflects the force exerted by circulating blood on the walls of arteries during the heart's contraction (systolic blood pressure, SBP) and relaxation (diastolic blood pressure, DBP) phases. Maintaining optimal BP levels is crucial for effective organ perfusion, oxygen delivery, nutrient transport to tissues, and the removal of waste products ( 4 ). Numerous global, regional, and national hypertension guidelines emphasize that lifestyle changes are the most effective strategy for lowering BP. Among these adjustments, nutrition plays a significant role in managing hypertension ( 5 ). Dietary fiber (DF) is simple component of diet, which is polymer of carbohydrates that the body's enzymes are unable to break down. Based on its capacity to form gels, solubility in water, viscosity, and fermentation by gut microbes, it is divided into soluble and insoluble fiber. Water-soluble fibers create viscous gels and are highly fermentable, whereas insoluble fibers are neither soluble in water nor fermentable by gut microbes ( 6 ).The majority of natural foods include DF, of which around one-third is soluble and the remainder is insoluble fiber ( 7 ). Cereals, legumes, fruits, and vegetables are good sources of DF ( 4 , 6 ). A recent global study found that dietary fiber can significantly lower blood pressure, reducing systolic blood pressure (SBP) by about 2.8 mmHg and diastolic blood pressure (DBP) by approximately 2.1 mmHg. This effect is linked to the fermentation of fiber in the colon, which produces short-chain fatty acids (SCFAs) that enhance blood vessel elasticity( 10 ). Additionally, increased fiber intake boosts nitric oxide levels, aiding in blood pressure regulation. The study also highlights that fiber improves insulin sensitivity, which further contributes to lower BP levels( 11 ). In view of this and the paucity of information in this regard, we examined the effect of fiber on blood pressure control and advocated for the incorporation of DF as among the key lifestyle modifications to manage elevated blood pressure and other allied comorbidities. Methods and materials Study design, period and participants An Institutional based cross sectional study was conducted among Type 2 DM patients, who had at least three month follow up at general government Hospitals in Addis Ababa, Ethiopia from March to April, 2024. The study was conducted in four general government Hospitals which have chronic disease follow up Clinic namely; Zewditu Memorial Hospital (ZMH), Yekatit 12 Hospital and Medical College, Tirunesh Bejing Hospital and Ras Desta Dametew (RDD) Hospital. The inclusion criteria in the study were Type 2 DM patients aged 18 and above with at least a three-month follow-up in general government hospitals. Excluded were clients in acute medical distress, pregnant or lactating women, those with critical illnesses like advanced malignancy or compensated liver cirrhosis, and patients under renal replacement therapy. Sample size and sampling technique The sample size (SS) for each specific objective was calculated individually. For the first objective, the calculation was determined using a single population formula based on the most consumed food items and their fiber proportions, specifically sunflower with a fiber proportion of 21.7% ( 12 ). Taking into account a 95% confidence level, 5% level of significance, 5% margin of error, and a 10% non-response rate, a sample size of 287 participants was determined. For the second objective, which aimed to estimate fiber intake in Type 2 diabetics, a single mean formula was used. The sample size calculation considered a mean of 19.27 ± 7.07( 13 ), 5% level of significance, a margin of error equal to 5% of the mean, and a 10% non-response rate, resulting in a sample size of 228. Since the sample size estimated for the first objective covered all requirements, the final working sample size remained at 287 participants. These participants were selected using a systematic sampling technique until the predetermined sample size was achieved. The allocation of clients for each hospital was 107, 70, 70, and 40 for ZMH, Yekatit 12, RDD, and Tirunesh-Beijing hospital, respectively. Data collection procedures and measurements Data collection was carried out over a month at specific government hospitals, led by a team of four trained public health officers(BSc) and two nutrition supervisors(BSc in nutrition), employing the KOBO toolbox. Prior to data collection, the principal investigator provided a two-day training session focused on the study’s goals, data collection techniques, 24-hour recall interview methods, and the operation of the KOBO toolbox. The study utilized a structured tool to obtain data on respondents’ socio demographic information, health behaviors, and clinical profiles. The socio demographic section included inquiries about age, sex, marital status, family size, and occupation, education, and income levels. Health behaviors were assessed through questions regarding cigarette smoking, alcohol use, Chat chewing, and physical activity. Clinical details covered aspects like disease duration, treatment types, presence of comorbidities, family history of diabetes mellitus, and current medications being taken. Weight and height were recorded using a balanced digital scale accurate to 0.1 kg, with participants wearing light clothing and no shoes. Height was measured to the nearest 0.1 cm while participants stood straight, ensuring their heads, backs, and buttocks were aligned. Body Mass Index (BMI) was calculated by dividing weight in kilograms by the square of height in meters (kg/m²), following standard protocols during interviews. Blood pressure was assessed using a digital electronic sphygmomanometer after ensuring respondents rested for at least five minutes. Two readings were taken with a two- to three-minute interval to ensure accuracy; the average of these was recorded. If the readings differed by more than 10 mmHg, a third measurement was taken, and the average of all three was used to determine blood pressure status. Dietary intake was assessed using a multiple-pass 24-hour recall method, where respondents provided detailed information about their food consumption, including items, portion sizes, eating times, and locations. This involved a four-step probing technique: listing consumed foods, quantifying amounts, collecting recipes, and reviewing the recall. Various estimation methods were used for portion sizes, such as standard unit sizes, rice, play dough, water, and maize flour, to enhance accuracy. A follow-up 24-hour recall was completed for 29 respondents representing 10% of the sample, and due to a strong correlation (correlation coefficient of 0.728, p < 0.01), the first recall was deemed sufficient. For portion size estimation, we used play dough for high-viscosity foods like fruits and bread, while liquids were measured with water. Rice served for medium-viscosity items like stew. Standardized portion sizes were applied for foods such as Injera(Local pancake made from teff), which was set at 310 grams based on an Ethiopian Public Health Institute survey. Nutritional information came from the Ethiopian Food Composition Table, with additional sources used when necessary, including tables from Kenya, West Africa, and the USDA. Food items absent from these resources were estimated through proportional methods. Fasting blood glucose (FBG) levels and hemoglobin A1C data were obtained from patient records, with the latest HbA1C readings taken one to three months before data extraction. Operational definitions Blood pressure was classified as normal with a reading of 120/80 mm Hg, elevated when it fell between 120–129/80 mm Hg, Stage 1 hypertension when systolic BP ranged from 130–139 mm Hg or diastolic BP was 80–89 mm Hg, and Stage 2 hypertension when systolic BP exceeded 140 mm Hg or diastolic BP reached 90 mm Hg or higher, regardless of anti-hypertensive medication use ( 18 ). Good blood pressure was categorized below < 120/80 and above that were included as poor blood pressure control ( 14 ) . Good glycemic control was indicated by an HbA1c level below 7% and a fasting blood sugar level between 100 and 125 mg/dL, whereas poor glycemic control was characterized by an HbA1c above 7% and a fasting blood sugar level of 70 mg/dL or more( 15 ). For individuals aged 18 to 64, adequate physical activity was considered to be a minimum of 150 to 300 minutes of moderate-intensity aerobic exercise per week ( 16 ). Body weight classifications were established based on BMI: participants were categorized as underweight if their BMI was below 18.5 kg/m², normal weight if their BMI was below 25 kg/m², overweight if their BMI was between 25 and 29.9 kg/m², and obese if their BMI was 30 kg/m² or higher ( 17 ). At the time of the study, a person was classified as a smoker if they smoked at least one cigarette daily. Patients who consumed more than two units of alcohol per day for male patients and more than one unit of alcohol per day for female patients were classified as alcohol consumers ( 19 ) . Data entry and processing Day-to-day communication was maintained between the data collectors and the principal investigator (PI) regarding the collected and entered data. The assigned supervisor regularly shared the data with the PI to check for any missing information in a timely manner and to ensure data quality. In addition to site-based supervision, phone calls were made to data collectors to address any issues that arose during the data collection process. Once the data were collected, it was cleaned and coded before being exported to SPSS version 27 for both descriptive and inferential statistics. A binary logistic regression model was employed to evaluate the determinants of glycemic control (the outcome variable). Factors with a p-value of less than 0.25 in bi variable analysis was then included in the multivariable binary regression analysis. For all statistical significance tests, adjusted odds ratios (AOR) with a 95% confidence interval (CI) and a p-value of less than 0.05 were utilized. The results of the logistic regression indicated that the selected model had a good fit, as evidenced by the Hosmer-Lemeshow goodness-of-fit statistic of 0.712, which was greater than 0.05. Ethical approval and informed consent Permissions were granted by the health facilities involved. Ethical clearance was secured from the SPH Review Board (Reference No: SRH/296/2024). All participants provided oral informed consent, which detailed the study's objectives, as well as information on data privacy and confidentiality. Participants who did not receive services in line with the standard treatment guidelines were counseled to address the discrepancies. All data collection procedures were performed in accordance with standard protocol. Result Socio-demographic characteristics of respondents Of the 287 sampled participants, 282 (98.2%) of them had complete set of data. Less than half ((44.3%) were between the ages of 50 and 65. The majority of them (72.3%) were orthodox Christians. Males made up about half (51.4%) of them. Over three-quarters (78.7%) of the respondents were married, and about half (50.4%) of them were part of households with four to six family members. About 38.3% had completed university education or higher. Regarding occupation, 38 (13.5%) were employed by non-governmental organizations, and over half (58.5%) of them made more than 5,000 birr (Table 1 ). Table 1 Socio-demographic characteristic of respondents Variable Frequency (N) Percent (%) Sex Male 145 51.4 Female 137 48.6 Age in years 18–24 2 0.7 25–34 11 3.9 35–49 74 26.2 50–65 125 44.3 Above 65 70 24.8 Religion Orthodox 204 72.3 Protestant 37 13.1 Muslim 35 12.4 Others 6 2.2 Educational status No formal education 46 16.3 Primary school completed 21 7.4 Secondary school completed 61 21.6 Preparatory school completed 46 16.3 College or University above 62 38.3 Marital status Married 222 78.7 Divorced 38 13.5 Widowed 22 7.8 Family size members 1–3 104 36.9 4–6 142 50.4 Above 7 36 12.7 Occupation Self-employed 86 30.5 Retired 63 22.3 Government employed 40 14.2 Non-government employed 38 13.5 House wife 33 11.7 Non employed 22 7.8 Salary (birr) Less than 1500 39 13.8 1500–5000 78 27.7 Above 5000 165 58.5 Other*catholic Behavioral factors affecting blood pressure control As displayed in Fig. 1 , the proportion of respondents who have smoked cigarettes within one year, consumed chat, alcohol, and had the habit of doing physical exercise for more than 30 minutes on most days of the week were 10.6%, 13.1%, 32.6%, and 79.8%, respectively. Clinical characteristic of the respondents A total of two hundred twenty-four (79.4%) of respondents had hypertension. The proportion of respondents with desirable hemoglobin A1C and normal BMI was 43.3% and 55.7%, respectively. (Fig. 2 ) Health profile of respondents As shown in Table 2 , approximately two-thirds (64.9%) of participants had been living with the disease for over five years, and more than half (56.4%) of these individuals experienced comorbidities. The most prevalent comorbidity was hypertension, affecting 99 participants (61.1%), followed by hyperlipidemia in 42 participants (25.9%) and cardiovascular disease (CVD) (7.4%). The majority of respondents were on multi-therapy for hypertension, and one-third reported a family history of the condition. Most (90.1%) made dietary modifications upon being diagnosed with both HTN and DM. Additionally, nearly half (46.1%) had a history of hospital admissions, with approximately 41.5% of these admissions attributed to complications related to HTN and DM. Table 2 Health profile of the respondents Variables Frequency (n = 282) Percent Duration of diabetes (years) Less than 5 99 35.1 5–10 99 35.1 More than 10 84 29.8 Comorbidity disease Yes 162 56.4 No 125 43.6 Type of comorbidity (n = 162) Hypertension 99 61.1 Hyperlipidemia 42 25.9 Cardiovascular diseases 12 7.4 Asthma 9 5.6 Method of DM control Insulin 50 17.7 Tablet 100 35.5 Both 132 46.8 Duration of HTN follow up (years) Less than 2 84 29.8 3–5 88 31.2 More than 5 110 39.0 Methods of control of HTN Mono-therapy (1 medication) 21 7.4 Multi -therapy (more than one) 262 92.6 Family history of HTN Yes 66 23.5 No 216 76.5 Dietary modification since follow up Yes 254 90.1 No 28 9.9 Admission history Yes 130 46.0 No 152 54.0 Complications related to HTN&DM Yes 117 41.5 No 165 58.5 Calorie intake of respondents Calorie intakes of respondents were analyzed using multi pass 24-hour dietary assessment method. The estimated mean energy intake based on the 24 hr. recall assessment was 1673.95 ± 743.1. Carbohydrate accounted for 73.1% of the total energy consumed, and fat contributed 14.5% and the rest 12.3% of the total energy was from protein (Table 3 ). Table 3 Calorie intake of respondents Vs recommended Energy sources Calorie (Mean + SD ) Percent contribution to total calorie (100%) Recommended daily allowance (RDA) Energy (kcal) 1673.95 ± 743.1 100 2000–3000 kcal/day Carbohydrate(g/day) 295.86 ± 124.9 73.1 50–60( % of total energy) Protein (g/day) 50 ± 24.9 12.3 10–15% ( % of total energy) Fat(g/day) 28.12 ± 26 14.5 25–30%( % of total energy) Fiber intake and major sources of fiber The mean dietary fiber intake was 32.5 ± 20g/d. From the foods, six groups of food type were identified as the major source dietary fiber. From these, the leading sources of fiber for the study participants were cereal which accounted 79.5% of the total fiber intake, followed by vegetables 7%. Legumes and pulses accounted 6.2%, and nut and seed contributed near 4.5% of the total fiber. (Fig. 3 ) Correlation between fiber intake and various health indicators We utilized the Pearson correlation coefficient to investigate the association between dietary fiber intake and various health indicators. The results showed a significant inverse correlation between dietary fiber intake and both blood pressure (coefficient: -0.551, p-value < 0.001) as well as body mass index (coefficient: -0.605, p-value < 0.001). This suggests that higher dietary fiber intake was linked to lower levels of blood pressure and body mass index. Additionally, the analysis also revealed a significant inverse correlation between dietary fiber intake and hemoglobin A1c (coefficient: -0.341, p-value < 0.001), indicating that increased dietary fiber intake is associated with lower hemoglobin A1c levels. (Table 4 ) Table 4 Correlation between fiber intake and various health indicators among respondents Correlations dietary fiber ( g) Body mass index Blood pressure hemoglobinA1Cnew dietary fiber ( g) Pearson Correlation 1 − .605 ** − .551 ** − .341 ** P value .000 .000 .000 N 282 282 282 268 **. Correlation is significant at the 0.01 level (2-tailed). Determinants of blood pressure control among respondents Binary logistic regression was employed to identify the determinants of blood pressure control. The variables exercise, dietary fiber, energy, protein, and diabetic control were considered candidate variables (p-value < 0.25) and were subsequently analyzed using multivariable analysis. Only dietary fiber and exercise maintained their significance in relation to poor BP control, with a p-value < 0.05. Exercise and dietary fiber demonstrated an inverse association with BP control. The odds of poor blood pressure control were three times greater (AOR: 3.346; 95% CI: 1.211, 9.243) among patients who did not engage in physical exercise compared to those who exercised for more than 30 minutes at least 3–5 times a week. When all other variables were held constant, a one-unit increase in dietary fiber intake among Type 2 diabetes mellitus patients was associated with a 6% decrease in the odds of poor blood pressure control (AOR: 0.936; 95% CI: 0.913, 0.959 ).(Table 5 ) Table 5 Bi variable and Multi-variable analysis for determining predictors of poor BP control respondents Variable Blood pressure control 95%CI COR 95%CI AOR P value Poor BP control Good BP control Diabetic control Tablet 36(16.1%) 14(24.1%) 0.380(0.171,0.846 ) 0.689(0.258,1.839) 0.449 Insulin 73(32.6%) 27(46.6%) 0.400(0.204,0.784) 0.514( 0.238,1.109) 0.090 Both 115(51.3%) 17(29.3%) 1 1 Exercise No 51(22.8%) 6(10.3%) 2.555(1.038,6.290) 3.346(1.211,9.243)* 0.020 Yes 173(77.2%) 52(89.7%) 1 1 Energy 0.999(0.998,0.999) 1.000(0.999,1.001) 0.561 Dietary fiber 0.937(0.919,0.954) 0.936(0.913,0.959)* 0.001 Protein 0.972(0.961,0.984) 0.989(0.965,1.013) 0.369 1 = indicate the reference category * significance association at P value < 0.005 *Adjusted for energy, type of diabetic control, protein, dietary fiber and exercise. Discussion The points discussed in this article are all potentially informative but may suffer from some limitations due the nature of the study design employed in which we are unable to confirm causality relationships and thus needs to be interpreted cautiously in terms of generalization. A notable figure in this study did not achieve the target blood pressure control (79.4%) with an inverse relationship between total dietary fiber intake and blood pressure, body mass index (BMI), and hemoglobin A1C levels. Interestingly, low dietary fiber intake and physical activity were also significantly linked to inadequate blood pressure control. Lifestyle modification is a cornerstone of adjunct therapy for managing hypertension, with the DASH (Dietary Approaches to Stop Hypertension) diet being a particularly effective strategy. This flexible and balanced eating plan encourages the consumption of fruits, vegetables, low-fat dairy foods, as well as foods high in fiber and low in saturated fat, total fat, and cholesterol. The DASH diet aligns closely with other dietary patterns aimed at enhancing cardiovascular health ( 20 ). Likewise, our findings revealed that respondents in this setting had similar dietary patterns with cereal being the predominant source of dietary fiber in the majorities. Dietary fiber in addition to its role in managing blood pressure, it also plays a vital role in blood sugar control. Those patients who consumed an average of 32.5 ± 20 g/day of DF, aligning with the recommended intake of 20–35 g/day had better control of their blood sugar and blood pressure in our study. This amount compared with other African countries, our finding was higher. For instance DF consumption was 23.2 ± 8.0 g/day in Uganda( 21 ), 19.73 ± 8.82 g/day for South Africa ( 22 ), and 6.75 ± 2.83 g/day) in Sudan ( 23 ). In contrast DF intake was slightly lower than the Kenyan patients (37.9 g/day) ( 24 ). The higher fiber consumption in Ethiopia may be attributed to the traditional diet, which includes a variety of whole grains, legumes, and vegetables. Cultural practices and food availability also contribute to this increased intake. Conversely, the lower fiber intake compared to Kenya could result from differences in culinary traditions and agricultural practices. When compared to the East Mediterranean region (21.8 g/day) (35) and Mexico among similar patients (13.83 ± 0.4 g/day) (51), Japan (8.7–21.6 g/day) (54), and Thailand (8 ± 4 g/day) (56), our findings reflect a richer dietary fiber intake due to its emphasis on whole grains like teff (Eragrostis teff), the staple food for most of our respondents highlighting the significance of DF use in achieving better health outcomes for Type 2 diabetes patients in our settings compared to other countries. The prevalence of inadequate blood pressure control among respondents in this study was alarmingly high with over 39% of them classified as having stage two hypertension. In contrast, a cross-sectional study conducted in the UK reported a hypertension prevalence of only 55.8% ( 25 ), highlighting a significant disparity (55.8% vs. 79.4%) probably attributed to comorbidities such as diabetes in our study. Close to our findings, some previous studies also documented higher proportion of hypertension among urban population with the highest hit in Addis Ababa ( 24 , 25 ) suggesting that individuals in this setting face additional challenges due to comorbidities that included diabetes and other cardiovascular diseases (CVDs). It is therefore crucial to emphasize the use of DF and adherence to nutritional guidelines as adjuvant approach particularly for those with multiple comorbidities. Interestingly, our findings showed a significant correlation between blood pressure control and dietary fiber intake (p < 0.001). As dietary fiber intake increases, blood pressure control has improved i.e. for every unit increase in dietary fiber consumption, there was a 6% improvement in the odds of poor blood pressure control ( AOR: 0.936; 95% CI: 0.913, 0.959) implying that adequate dietary fiber intake positively influences blood pressure regulation. Our finding aligns with the meta-analyses of clinical trials which demonstrated that DF intake to improve blood pressure, glycemic control, reduce insulin resistance, and promote weight loss ( 28 ). These effects were attributed to the hypolipidemic effect of fibers which improves the elasticity of blood vessels in addition to the impact of fiber on arterial blood pressure, DF enhances insulin sensitivity and improves vascular endothelial function, both of which are crucial for regulating blood pressure ( 11 ). Another important finding of our study was the link of physical activity intake with poor blood pressure control, and observed to be consistent with the meta-analysis that documented performing physical activity reduces blood pressure among adults with hypertension. This is likely because physical activity decreases blood pressure through a reduction in systemic vascular resistance, involving both the sympathetic nervous system and the renin-angiotensin system, while also favorably affecting concomitant cardiovascular risk factors ( 29 ). In addition, regular physical activity is shown to reduce blood pressure by decreasing sympathetic nerve activity in individuals with hypertension since it leads to a decreased release of norepinephrine, which is responsible for vasoconstriction, thereby lowering vascular resistance. Furthermore, physical activity enhances insulin sensitivity and diminishes insulin-related sympathetic activity. It also lessens the vascular response to endothelin-1, another vasoconstrictor affecting those with hypertensionand cpromote vascular remodeling, which includes the formation of new arteries, an increase in the cross-sectional area, and the enlargement of existing veins and arteries. These structural changes ultimately contribute to reduced peripheral resistance and results in reducing blood pressure ( 30 , 31 ). The study presents several strengths, notably its innovative approach to estimating fiber intake in Type 2 diabetes patients through proxy indicators, such as portion size estimation methods. It also employed the KOBO Collect tool for electronic data collection, effectively mitigating issues with missing data and ensuring that the information gathered was both thorough and precise. However, there are some limitations to consider. The emphasis on participants with both diabetes and hypertension may limit the generalizability of the findings to those with hypertension alone. Moreover, challenges arose from the Nutri Survey 2007 dataset, which had a user-unfriendly format that complicated data analysis and required more time and effort. Additionally, collecting food recipes for the 24-hour recall proved to be inconvenient. The timing of data collection coincided with fasting seasons, which could affect dietary habits. Lastly, there was a concern about social desirability bias, as the lack of private and comfortable environments hindered open discussions about eating habits. Conclusion Our study highlights a significant concern regarding the health of diabetic patients, with over three-fourths of respondents exhibiting poor blood pressure control and more than half struggling with glycemic management. The promising results associated with dietary fiber intake indicate a negative correlation with blood pressure, BMI, and glycemic control, suggesting that lifestyle modifications particularly increased dietary fiber consumption and physical activity, to play a crucial role in improving health outcomes for individuals with type 2 diabetes. It is essential to prioritize intensive care and targeted interventions for patients with multiple comorbidities to enhance their overall well-being and manage these interconnected health issues effectively through a comprehensive approach to lifestyle changes mentioned above. Abbreviations AAU: Addis Ababa University; ADA: American Diabetes Association; BMI: Body Mass Index; BP: Blood Pressure; CVD: Cardio Vascular Diseases; DM: Diabetes Mellitus; DF: Dietary Fiber; Diastolic Blood Pressure: DBP; FBS: Fasting Blood Sugar; HbA1C: Hemoglobin A1C; NCD: Non Communicable Disease; PSEM: Portion Size Estimation Method; PPG: Postprandial Glucose; RDA: Recommended Daily Allowance; SPSS: Statistical Product and Service Solutions; SS: Sample size; Systolic Blood Pressure: SBP WHO: World Health Organization Declarations Data availability The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request. Acknowledgment The authors thank all the patients who participated in the study. In addition, the authors express their deepest gratitude to Addis Ababa University, College of Health Science, School of public health and Department of Nutrition and Dietetics for providing me the opportunity. The hospital administration and chronic OPD health professionals of each hospital, data collectors and Ethiopian Public Health Institute (EPHI) staff are acknowledged for their kind cooperation, willingness and unconditional support during the study. Author information Authors and Affiliations Department of Nutrition and Dietetics, School of Public Health, Addis Ababa University Feven Hailu 1 (BSc, MPH), Jemal Haidar Ali 1 (MD, MSc, CRM, CME, HD, Professor), Yakob Desalegn Nigatu 1 * (MD, MPH) Authors’ contribution FH: Conceptualization, methodology, Data collection, data validation, formal analysis, writing—original draft, and supervision. JH: Methodology review, validation, writing—review and editing. YD: Data validation, writing—review and editing. All authors have read, critically revised and approved the final manuscript. Funding statement This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Ethics declarations Competing interests The authors declare no competing interests. Ethical considerations Ethical clearance was obtained from the Ethical Review Committee of the School of Public Health, College of Health Sciences, Addis Ababa University, and the Addis Ababa Health Bureau (Reference Number: SRH/296/2024). A legal permission letter was issued to the selected government hospitals. During data collection, oral informed consent was obtained from the study participants, and measures were taken to ensure the confidentiality of their information. 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Blood pressure control status and associated factors among adult hypertensive patients on outpatient follow-up at University of Gondar Referral Hospital, northwest Ethiopia: a retrospective follow-up study. Integr Blood Press Control. 2018 Apr;Volume 11:37–46. ElSayed NA, Aleppo G, Aroda VR, Bannuru RR, Brown FM, Bruemmer D, et al. Glycemic Targets: Standards of Care in Diabetes—2023 . Diabetes Care. 2023 Jan 1;46(Supplement_1):S97–110. WHO Guidelines on physical activity and sedentary behaviour, 2020https://iris.who.int/bitstream/handle/10665/337001/9789240014886-eng. Weir CB, Jan A. BMI Classification Percentile And Cut Off Points. [Updated 2023 Jun 26]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK541070/. Whelton, P. K., Carey, R. M., Aronow, W. S., Casey, D. E., Jr, Collins, K. J., Dennison Himmelfarb, C., DePalma, S. M., Gidding, S., Jamerson, K. A., Jones, D. W., MacLaughlin, E. J., Muntner, P., Ovbiagele, B., Smith, S. C., Jr, Spencer, C. C., Stafford, R. S., Taler, S. J., Thomas, R. J., Williams, K. A., Sr, Williamson, J. D., … Wright, J. T., Jr (2018). 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension (Dallas, Tex. : 1979), 71(6), 1269–1324. https://doi.org/10.1161/HYP.0000000000000066. Animut Y, Assefa AT, Lemma D. Blood pressure control status and associated factors among adult hypertensive patients on outpatient follow-up at University of Gondar Referral Hospital, northwest Ethiopia: a retrospective follow-up study. Integr Blood Press Control. 2018 Apr;Volume 11:37–46. Challa HJ, Ameer MA, Uppaluri KR. DASH Diet To Stop Hypertension. [Updated 2023 Jan 23]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK482514/. Mohammed ESE. Nutritional status and Food consumption Pattern of Type 2 Diabetic Patients in Aboudah Health Center, Kerri Locality, Khartoum State, Sudan. 2019;2. Duvenage, H., Gericke, G. J., & Muchiri, J. W. (2022). Diet quality of adults with poorly controlled type 2 diabetes mellitus at a tertiary hospital outpatient clinic in Tshwane District, South Africa. South African Journal of Clinical Nutrition, 36(3), 93–99. https://doi.org/10.1080/16070658.2022.2114406. Mohammed ESE. Nutritional status and Food consumption Pattern of Type 2 Diabetic Patients in Aboudah Health Center, Kerri Locality, Khartoum State, Sudan. 2019;2. Mugo IM. Compliance to recommended dietary practices among patients with type 2 diabetes mellitus attending selected hospitals in Nakuru county. Tapela N, Collister J, Clifton L, et alPrevalence and determinants of hypertension control among almost 100 000 treated adults in the UKOpen Heart 2021;8:e001461. doi: 10.1136/openhrt-2020-001461. Kibret, K.T., Mesfin, Y.M. Prevalence of hypertension in Ethiopia: a systematic meta-analysis. Public Health Rev 36, 14 (2015). https://doi.org/10.1186/s40985-015-0014-z. Tesfaye, F., Byass, P. & Wall, S. Population based prevalence of high blood pressure among adults in Addis Ababa: uncovering a silent epidemic. BMC Cardiovasc Disord 9, 39 (2009). https://doi.org/10.1186/1471-2261-9-39. David G. Harrison,David M. Patrick,Immune Mechanisms in Hypertension, Hypertension, 81, 8, (1659-1674), (2024). /doi/10.1161/HYPERTENSIONAHA.124.21355. Shariful Islam, M., Fardousi, A., Sizear, M.I. et al. Effect of leisure-time physical activity on blood pressure in people with hypertension: a systematic review and meta-analysis. Sci Rep 13, 10639 (2023). https://doi.org/10.1038/s41598-023-37149-2. Laughlin MH, Korthuis RJ, Duncker DJ, Bache RJ. Control of blood flow to cardiac and skeletal muscle during exercise. Comprehensive Physiology. 2010 Jun:705-69. Islam FMA, Islam MA, Hosen MA, Lambert EA, Maddison R, et al. (2023) Associations of physical activity levels, and attitudes towards physical activity with blood pressure among adults with high blood pressure in Bangladesh. PLOS ONE 18(2): e0280879. https://doi.org/10.1371/journal.pone.0280879. Additional Declarations No competing interests reported. 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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-7227814","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":504505561,"identity":"14e2bb8b-9687-499b-b430-4e572b953362","order_by":0,"name":"Feven Hailu","email":"","orcid":"","institution":"Addis Ababa University","correspondingAuthor":false,"prefix":"","firstName":"Feven","middleName":"","lastName":"Hailu","suffix":""},{"id":504505562,"identity":"ec510fd9-3cb1-435c-b457-a4d807a0c604","order_by":1,"name":"Jemal Haidar Ali","email":"","orcid":"","institution":"Addis Ababa University","correspondingAuthor":false,"prefix":"","firstName":"Jemal","middleName":"Haidar","lastName":"Ali","suffix":""},{"id":504505563,"identity":"8bc14e71-5228-4835-81aa-e0ff4f126137","order_by":2,"name":"Yakob Desalegn Nigatu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIiWNgGAWjYFACNgZmIGZgYAfzbICYsfEAcVqYwbw0kJYGkrQcBpN4tRgcP5b4uKDMxp6/mfnw64KK83Zr2w8Dbamxicap5UzaYeMZ59ISZxxmS7OeceZ28rYziUAtx9JyG3BpOZDeJs3bdjiB4TCPmTFv2+1kswNALYwNh3FrOf8cpOW/vfxh/m/GvP/OJZudf0hAy420Y0AtBxg3HOZhfszbcMDO7AYBWyRvPEsG+iU5ceNhNjNmnmPJCWY3gLYk4PEL3/k0Q2CI2dnLHW9+/Jmnxs7e7Hz6wwcfamxwalE4gGCzSQCJRLDKBBzKQUAeySzmD0DCHo/iUTAKRsEoGKEAAGz9ZXmWP8ODAAAAAElFTkSuQmCC","orcid":"","institution":"Addis Ababa University","correspondingAuthor":true,"prefix":"","firstName":"Yakob","middleName":"Desalegn","lastName":"Nigatu","suffix":""}],"badges":[],"createdAt":"2025-07-27 18:08:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7227814/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7227814/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-24579-3","type":"published","date":"2025-11-19T15:58:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89987841,"identity":"ee098c27-0199-4085-9225-3105cb7bf077","added_by":"auto","created_at":"2025-08-27 07:01:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":9829,"visible":true,"origin":"","legend":"\u003cp\u003eBehavioral factors affecting blood pressure control among respondents\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7227814/v1/4078b143193364240603fad8.png"},{"id":89987845,"identity":"58829350-3274-4fc4-8ba7-aa20368c2aa7","added_by":"auto","created_at":"2025-08-27 07:01:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":6323,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eClinical characteristic of the respondents\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7227814/v1/7639d7e1ea4dad5cd4809dfc.png"},{"id":89990027,"identity":"5bfc4e12-dc85-4b41-b044-cea95f2579eb","added_by":"auto","created_at":"2025-08-27 07:09:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":19196,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003emajor fiber contribution of food sources among meal consumed by respondents\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7227814/v1/f4e6ced84dd23657f9374a8d.png"},{"id":96650148,"identity":"e0d885f3-946b-4cf8-ad60-a4e38c4dbb7b","added_by":"auto","created_at":"2025-11-24 16:08:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1386194,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7227814/v1/1aa562cb-0cb5-4f73-8c9b-26c019c738fd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Effect of Dietary Fiber Intake on Blood Pressure Control among Type 2 Diabetic Patients in Selected Hospitals of Addis Ababa, Ethiopia: A Multi-Facility Cross-Sectional Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCardiovascular diseases (CVDs) encompass a range of disorders affecting the heart and blood vessels, including coronary heart disease, cerebrovascular disease, and congenital heart defects (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). They are the leading cause of death globally, with approximately 17.9\u0026nbsp;million deaths reported in 2019, escalating to around 20.5\u0026nbsp;million by 2021, and accounted for nearly one-third of all fatalities (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Risk factors for CVDs are classified as non-modifiable factors like age, gender, and family history, and modifiable factors such as sedentary lifestyles and poor dietary practices. This highlights the urgent need for targeted public health initiatives to address these risk factors, particularly emphasizing the importance of promoting a healthy diet that includes dietary fiber as a key strategy in preventing cardiovascular diseases (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAmong the various parameters, the key physiological indicator used to evaluate cardiovascular health is blood pressure (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).This measure reflects the force exerted by circulating blood on the walls of arteries during the heart's contraction (systolic blood pressure, SBP) and relaxation (diastolic blood pressure, DBP) phases. Maintaining optimal BP levels is crucial for effective organ perfusion, oxygen delivery, nutrient transport to tissues, and the removal of waste products (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Numerous global, regional, and national hypertension guidelines emphasize that lifestyle changes are the most effective strategy for lowering BP. Among these adjustments, nutrition plays a significant role in managing hypertension (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDietary fiber (DF) is simple component of diet, which is polymer of carbohydrates that the body's enzymes are unable to break down. Based on its capacity to form gels, solubility in water, viscosity, and fermentation by gut microbes, it is divided into soluble and insoluble fiber. Water-soluble fibers create viscous gels and are highly fermentable, whereas insoluble fibers are neither soluble in water nor fermentable by gut microbes (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).The majority of natural foods include DF, of which around one-third is soluble and the remainder is insoluble fiber (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Cereals, legumes, fruits, and vegetables are good sources of DF (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA recent global study found that dietary fiber can significantly lower blood pressure, reducing systolic blood pressure (SBP) by about 2.8 mmHg and diastolic blood pressure (DBP) by approximately 2.1 mmHg. This effect is linked to the fermentation of fiber in the colon, which produces short-chain fatty acids (SCFAs) that enhance blood vessel elasticity(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Additionally, increased fiber intake boosts nitric oxide levels, aiding in blood pressure regulation. The study also highlights that fiber improves insulin sensitivity, which further contributes to lower BP levels(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). In view of this and the paucity of information in this regard, we examined the effect of fiber on blood pressure control and advocated for the incorporation of DF as among the key lifestyle modifications to manage elevated blood pressure and other allied comorbidities.\u003c/p\u003e"},{"header":"Methods and materials","content":"\u003cp\u003e\u003cb\u003eStudy design, period and participants\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAn Institutional based cross sectional study was conducted among Type 2 DM patients, who had at least three month follow up at general government Hospitals in Addis Ababa, Ethiopia from March to April, 2024. The study was conducted in four general government Hospitals which have chronic disease follow up Clinic namely; Zewditu Memorial Hospital (ZMH), Yekatit 12 Hospital and Medical College, Tirunesh Bejing Hospital and Ras Desta Dametew (RDD) Hospital. The inclusion criteria in the study were Type 2 DM patients aged 18 and above with at least a three-month follow-up in general government hospitals. Excluded were clients in acute medical distress, pregnant or lactating women, those with critical illnesses like advanced malignancy or compensated liver cirrhosis, and patients under renal replacement therapy.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSample size and sampling technique\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe sample size (SS) for each specific objective was calculated individually. For the first objective, the calculation was determined using a single population formula based on the most consumed food items and their fiber proportions, specifically sunflower with a fiber proportion of 21.7% (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Taking into account a 95% confidence level, 5% level of significance, 5% margin of error, and a 10% non-response rate, a sample size of 287 participants was determined. For the second objective, which aimed to estimate fiber intake in Type 2 diabetics, a single mean formula was used. The sample size calculation considered a mean of 19.27 ± 7.07(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), 5% level of significance, a margin of error equal to 5% of the mean, and a 10% non-response rate, resulting in a sample size of 228. Since the sample size estimated for the first objective covered all requirements, the final working sample size remained at 287 participants. These participants were selected using a systematic sampling technique until the predetermined sample size was achieved. The allocation of clients for each hospital was 107, 70, 70, and 40 for ZMH, Yekatit 12, RDD, and Tirunesh-Beijing hospital, respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData collection procedures and measurements\u003c/b\u003e\u003c/p\u003e\u003cp\u003eData collection was carried out over a month at specific government hospitals, led by a team of four trained public health officers(BSc) and two nutrition supervisors(BSc in nutrition), employing the KOBO toolbox. Prior to data collection, the principal investigator provided a two-day training session focused on the study’s goals, data collection techniques, 24-hour recall interview methods, and the operation of the KOBO toolbox.\u003c/p\u003e\u003cp\u003eThe study utilized a structured tool to obtain data on respondents’ socio demographic information, health behaviors, and clinical profiles. The socio demographic section included inquiries about age, sex, marital status, family size, and occupation, education, and income levels. Health behaviors were assessed through questions regarding cigarette smoking, alcohol use, Chat chewing, and physical activity. Clinical details covered aspects like disease duration, treatment types, presence of comorbidities, family history of diabetes mellitus, and current medications being taken.\u003c/p\u003e\u003cp\u003eWeight and height were recorded using a balanced digital scale accurate to 0.1 kg, with participants wearing light clothing and no shoes. Height was measured to the nearest 0.1 cm while participants stood straight, ensuring their heads, backs, and buttocks were aligned. Body Mass Index (BMI) was calculated by dividing weight in kilograms by the square of height in meters (kg/m²), following standard protocols during interviews.\u003c/p\u003e\u003cp\u003eBlood pressure was assessed using a digital electronic sphygmomanometer after ensuring respondents rested for at least five minutes. Two readings were taken with a two- to three-minute interval to ensure accuracy; the average of these was recorded. If the readings differed by more than 10 mmHg, a third measurement was taken, and the average of all three was used to determine blood pressure status.\u003c/p\u003e\u003cp\u003eDietary intake was assessed using a multiple-pass 24-hour recall method, where respondents provided detailed information about their food consumption, including items, portion sizes, eating times, and locations. This involved a four-step probing technique: listing consumed foods, quantifying amounts, collecting recipes, and reviewing the recall. Various estimation methods were used for portion sizes, such as standard unit sizes, rice, play dough, water, and maize flour, to enhance accuracy. A follow-up 24-hour recall was completed for 29 respondents representing 10% of the sample, and due to a strong correlation (correlation coefficient of 0.728, p \u0026lt; 0.01), the first recall was deemed sufficient.\u003c/p\u003e\u003cp\u003eFor portion size estimation, we used play dough for high-viscosity foods like fruits and bread, while liquids were measured with water. Rice served for medium-viscosity items like stew. Standardized portion sizes were applied for foods such as Injera(Local pancake made from teff), which was set at 310 grams based on an Ethiopian Public Health Institute survey. Nutritional information came from the Ethiopian Food Composition Table, with additional sources used when necessary, including tables from Kenya, West Africa, and the USDA. Food items absent from these resources were estimated through proportional methods.\u003c/p\u003e\u003cp\u003eFasting blood glucose (FBG) levels and hemoglobin A1C data were obtained from patient records, with the latest HbA1C readings taken one to three months before data extraction.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOperational definitions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBlood pressure was classified as normal with a reading of 120/80 mm Hg, elevated when it fell between 120–129/80 mm Hg, Stage 1 hypertension when systolic BP ranged from 130–139 mm Hg or diastolic BP was 80–89 mm Hg, and Stage 2 hypertension when systolic BP exceeded 140 mm Hg or diastolic BP reached 90 mm Hg or higher, regardless of anti-hypertensive medication use (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Good blood pressure was categorized below \u0026lt; 120/80 and above that were included as poor blood pressure control (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) .\u003c/p\u003e\u003cp\u003eGood glycemic control was indicated by an HbA1c level below 7% and a fasting blood sugar level between 100 and 125 mg/dL, whereas poor glycemic control was characterized by an HbA1c above 7% and a fasting blood sugar level of 70 mg/dL or more(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFor individuals aged 18 to 64, adequate physical activity was considered to be a minimum of 150 to 300 minutes of moderate-intensity aerobic exercise per week (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Body weight classifications were established based on BMI: participants were categorized as underweight if their BMI was below 18.5 kg/m², normal weight if their BMI was below 25 kg/m², overweight if their BMI was between 25 and 29.9 kg/m², and obese if their BMI was 30 kg/m² or higher (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAt the time of the study, a person was classified as a smoker if they smoked at least one cigarette daily. Patients who consumed more than two units of alcohol per day for male patients and more than one unit of alcohol per day for female patients were classified as alcohol consumers (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) .\u003c/p\u003e\u003cp\u003e\u003cb\u003eData entry and processing\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDay-to-day communication was maintained between the data collectors and the principal investigator (PI) regarding the collected and entered data. The assigned supervisor regularly shared the data with the PI to check for any missing information in a timely manner and to ensure data quality. In addition to site-based supervision, phone calls were made to data collectors to address any issues that arose during the data collection process. Once the data were collected, it was cleaned and coded before being exported to SPSS version 27 for both descriptive and inferential statistics. A binary logistic regression model was employed to evaluate the determinants of glycemic control (the outcome variable). Factors with a p-value of less than 0.25 in bi variable analysis was then included in the multivariable binary regression analysis. For all statistical significance tests, adjusted odds ratios (AOR) with a 95% confidence interval (CI) and a p-value of less than 0.05 were utilized. The results of the logistic regression indicated that the selected model had a good fit, as evidenced by the Hosmer-Lemeshow goodness-of-fit statistic of 0.712, which was greater than 0.05.\u003c/p\u003e\u003cp\u003eEthical approval and informed consent\u003c/p\u003e\u003cp\u003ePermissions were granted by the health facilities involved. Ethical clearance was secured from the SPH Review Board (Reference No: SRH/296/2024). All participants provided oral informed consent, which detailed the study's objectives, as well as information on data privacy and confidentiality. Participants who did not receive services in line with the standard treatment guidelines were counseled to address the discrepancies. All data collection procedures were performed in accordance with standard protocol.\u003c/p\u003e"},{"header":"Result","content":"\u003cp\u003e\u003cb\u003eSocio-demographic characteristics of respondents\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOf the 287 sampled participants, 282 (98.2%) of them had complete set of data. Less than half ((44.3%) were between the ages of 50 and 65. The majority of them (72.3%) were orthodox Christians. Males made up about half (51.4%) of them. Over three-quarters (78.7%) of the respondents were married, and about half (50.4%) of them were part of households with four to six family members. About 38.3% had completed university education or higher. Regarding occupation, 38 (13.5%) were employed by non-governmental organizations, and over half (58.5%) of them made more than 5,000 birr (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSocio-demographic characteristic of respondents\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency (N)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercent (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e137\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge in years\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18–24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25–34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e35–49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e50–65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAbove 65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrthodox\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e204\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e72.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtestant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMuslim\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducational status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo formal education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary school completed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary school completed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePreparatory school completed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollege or University above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e222\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDivorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFamily size members\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1–3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4–6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e142\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAbove 7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOccupation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-employed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRetired\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGovernment employed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-government employed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHouse wife\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon employed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSalary (birr)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLess than 1500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1500–5000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAbove 5000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003eOther*catholic\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003cstrong\u003eBehavioral factors affecting blood pressure control\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eAs displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the proportion of respondents who have smoked cigarettes within one year, consumed chat, alcohol, and had the habit of doing physical exercise for more than 30 minutes on most days of the week were 10.6%, 13.1%, 32.6%, and 79.8%, respectively.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eClinical characteristic of the respondents\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of two hundred twenty-four (79.4%) of respondents had hypertension. The proportion of respondents with desirable hemoglobin A1C and normal BMI was 43.3% and 55.7%, respectively. (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003cb\u003eHealth profile of respondents\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, approximately two-thirds (64.9%) of participants had been living with the disease for over five years, and more than half (56.4%) of these individuals experienced comorbidities. The most prevalent comorbidity was hypertension, affecting 99 participants (61.1%), followed by hyperlipidemia in 42 participants (25.9%) and cardiovascular disease (CVD) (7.4%). The majority of respondents were on multi-therapy for hypertension, and one-third reported a family history of the condition. Most (90.1%) made dietary modifications upon being diagnosed with both HTN and DM. Additionally, nearly half (46.1%) had a history of hospital admissions, with approximately 41.5% of these admissions attributed to complications related to HTN and DM.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHealth profile of the respondents\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrequency (n = 282)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercent\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eDuration of diabetes\u003c/p\u003e\u003cp\u003e(years)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLess than 5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5–10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMore than 10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eComorbidity disease\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e162\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eType of comorbidity (n = 162)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e61.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHyperlipidemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCardiovascular diseases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAsthma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMethod of DM control\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsulin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTablet\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDuration of HTN follow up\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLess than 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3–5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMore than 5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMethods of control of HTN\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMono-therapy\u003c/p\u003e\u003cp\u003e(1 medication)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMulti -therapy\u003c/p\u003e\u003cp\u003e(more than one)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e262\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e92.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFamily history of HTN\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e216\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDietary modification since\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003efollow up\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e254\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e90.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAdmission history\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e152\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eComplications related to\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eHTN\u0026amp;DM\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003cb\u003eCalorie intake of respondents\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCalorie intakes of respondents were analyzed using multi pass 24-hour dietary assessment method. The estimated mean energy intake based on the 24 hr. recall assessment was 1673.95 ± 743.1. Carbohydrate accounted for 73.1% of the total energy consumed, and fat contributed 14.5% and the rest 12.3% of the total energy was from protein (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"±\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCalorie intake of respondents Vs recommended\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnergy sources\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCalorie (Mean + SD )\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePercent contribution to total calorie (100%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRecommended daily allowance (RDA)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnergy (kcal)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\u003cp\u003e1673.95 ± 743.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2000–3000 kcal/day\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCarbohydrate(g/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\u003cp\u003e295.86 ± 124.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50–60( % of total energy)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtein (g/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\u003cp\u003e50 ± 24.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10–15% ( % of total energy)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFat(g/day)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"±\" colname=\"c2\"\u003e\u003cp\u003e28.12 ± 26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25–30%( % of total energy)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003cb\u003eFiber intake and major sources of fiber\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe mean dietary fiber intake was 32.5 ± 20g/d. From the foods, six groups of food type were identified as the major source dietary fiber. From these, the leading sources of fiber for the study participants were cereal which accounted 79.5% of the total fiber intake, followed by vegetables 7%. Legumes and pulses accounted 6.2%, and nut and seed contributed near 4.5% of the total fiber. (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003cb\u003eCorrelation between fiber intake and various health indicators\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe utilized the Pearson correlation coefficient to investigate the association between dietary fiber intake and various health indicators. The results showed a significant inverse correlation between dietary fiber intake and both blood pressure (coefficient: -0.551, p-value \u0026lt; 0.001) as well as body mass index (coefficient: -0.605, p-value \u0026lt; 0.001). This suggests that higher dietary fiber intake was linked to lower levels of blood pressure and body mass index. Additionally, the analysis also revealed a significant inverse correlation between dietary fiber intake and hemoglobin A1c (coefficient: -0.341, p-value \u0026lt; 0.001), indicating that increased dietary fiber intake is associated with lower hemoglobin A1c levels. (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelation between fiber intake and various health indicators among respondents\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCorrelations\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003edietary fiber ( g)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBody mass index\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eBlood pressure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ehemoglobinA1Cnew\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003edietary fiber ( g)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePearson Correlation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e− .605\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e− .551\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e− .341\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e282\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e282\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e282\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e268\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e**. Correlation is significant at the 0.01 level (2-tailed).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003cb\u003eDeterminants of blood pressure control among respondents\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBinary logistic regression was employed to identify the determinants of blood pressure control. The variables exercise, dietary fiber, energy, protein, and diabetic control were considered candidate variables (p-value \u0026lt; 0.25) and were subsequently analyzed using multivariable analysis. Only dietary fiber and exercise maintained their significance in relation to poor BP control, with a p-value \u0026lt; 0.05.\u003c/p\u003e\u003cp\u003eExercise and dietary fiber demonstrated an inverse association with BP control. The odds of poor blood pressure control were three times greater \u003cb\u003e(AOR: 3.346; 95% CI: 1.211, 9.243)\u003c/b\u003e among patients who did not engage in physical exercise compared to those who exercised for more than 30 minutes at least 3–5 times a week. When all other variables were held constant, a one-unit increase in dietary fiber intake among Type 2 diabetes mellitus patients was associated with a 6% decrease in the odds of poor blood pressure control \u003cb\u003e(AOR: 0.936; 95% CI: 0.913, 0.959\u003c/b\u003e).(Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBi variable and Multi-variable analysis for determining predictors of poor BP control respondents\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eBlood pressure control\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e95%CI COR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e95%CI AOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePoor BP control\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGood BP control\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDiabetic control\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTablet\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36(16.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14(24.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.380(0.171,0.846\u003c/b\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.689(0.258,1.839)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.449\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsulin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e73(32.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27(46.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.400(0.204,0.784)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.514( 0.238,1.109)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.090\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e115(51.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17(29.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eExercise\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e51(22.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6(10.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e2.555(1.038,6.290)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e3.346(1.211,9.243)*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e173(77.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52(89.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEnergy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c3\" namest=\"c2\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.999(0.998,0.999)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.000(0.999,1.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.561\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDietary fiber\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.937(0.919,0.954)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.936(0.913,0.959)*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eProtein\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.972(0.961,0.984)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.989(0.965,1.013)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.369\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e1 = indicate the reference category * significance association at P value \u0026lt; 0.005 *Adjusted for energy, type of diabetic control, protein, dietary fiber and exercise.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe points discussed in this article are all potentially informative but may suffer from some limitations due the nature of the study design employed in which we are unable to confirm causality relationships and thus needs to be interpreted cautiously in terms of generalization. A notable figure in this study did not achieve the target blood pressure control (79.4%) with an inverse relationship between total dietary fiber intake and blood pressure, body mass index (BMI), and hemoglobin A1C levels. Interestingly, low dietary fiber intake and physical activity were also significantly linked to inadequate blood pressure control.\u003c/p\u003e\u003cp\u003eLifestyle modification is a cornerstone of adjunct therapy for managing hypertension, with the DASH (Dietary Approaches to Stop Hypertension) diet being a particularly effective strategy. This flexible and balanced eating plan encourages the consumption of fruits, vegetables, low-fat dairy foods, as well as foods high in fiber and low in saturated fat, total fat, and cholesterol. The DASH diet aligns closely with other dietary patterns aimed at enhancing cardiovascular health (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Likewise, our findings revealed that respondents in this setting had similar dietary patterns with cereal being the predominant source of dietary fiber in the majorities.\u003c/p\u003e\u003cp\u003eDietary fiber in addition to its role in managing blood pressure, it also plays a vital role in blood sugar control. Those patients who consumed an average of 32.5\u0026thinsp;\u0026plusmn;\u0026thinsp;20 g/day of DF, aligning with the recommended intake of 20\u0026ndash;35 g/day had better control of their blood sugar and blood pressure in our study. This amount compared with other African countries, our finding was higher. For instance DF consumption was 23.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0 g/day in Uganda(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), 19.73\u0026thinsp;\u0026plusmn;\u0026thinsp;8.82 g/day for South Africa (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), and 6.75\u0026thinsp;\u0026plusmn;\u0026thinsp;2.83 g/day) in Sudan (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). In contrast DF intake was slightly lower than the Kenyan patients (37.9 g/day) (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). The higher fiber consumption in Ethiopia may be attributed to the traditional diet, which includes a variety of whole grains, legumes, and vegetables. Cultural practices and food availability also contribute to this increased intake. Conversely, the lower fiber intake compared to Kenya could result from differences in culinary traditions and agricultural practices. When compared to the East Mediterranean region (21.8 g/day) (35) and Mexico among similar patients (13.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 g/day) (51), Japan (8.7\u0026ndash;21.6 g/day) (54), and Thailand (8\u0026thinsp;\u0026plusmn;\u0026thinsp;4 g/day) (56), our findings reflect a richer dietary fiber intake due to its emphasis on whole grains like teff (Eragrostis teff), the staple food for most of our respondents highlighting the significance of DF use in achieving better health outcomes for Type 2 diabetes patients in our settings compared to other countries.\u003c/p\u003e\u003cp\u003eThe prevalence of inadequate blood pressure control among respondents in this study was alarmingly high with over 39% of them classified as having stage two hypertension. In contrast, a cross-sectional study conducted in the UK reported a hypertension prevalence of only 55.8% (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), highlighting a significant disparity (55.8% vs. 79.4%) probably attributed to comorbidities such as diabetes in our study. Close to our findings, some previous studies also documented higher proportion of hypertension among urban population with the highest hit in Addis Ababa (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) suggesting that individuals in this setting face additional challenges due to comorbidities that included diabetes and other cardiovascular diseases (CVDs). It is therefore crucial to emphasize the use of DF and adherence to nutritional guidelines as adjuvant approach particularly for those with multiple comorbidities.\u003c/p\u003e\u003cp\u003eInterestingly, our findings showed a significant correlation between blood pressure control and dietary fiber intake (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). As dietary fiber intake increases, blood pressure control has improved i.e. for every unit increase in dietary fiber consumption, there was a 6% improvement in the odds of poor blood pressure control (\u003cb\u003eAOR: 0.936; 95% CI: 0.913, 0.959)\u003c/b\u003e implying that adequate dietary fiber intake positively influences blood pressure regulation. Our finding aligns with the meta-analyses of clinical trials which demonstrated that DF intake to improve blood pressure, glycemic control, reduce insulin resistance, and promote weight loss (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). These effects were attributed to the hypolipidemic effect of fibers which improves the elasticity of blood vessels in addition to the impact of fiber on arterial blood pressure, DF enhances insulin sensitivity and improves vascular endothelial function, both of which are crucial for regulating blood pressure (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAnother important finding of our study was the link of physical activity intake with poor blood pressure control, and observed to be consistent with the meta-analysis that documented performing physical activity reduces blood pressure among adults with hypertension. This is likely because physical activity decreases blood pressure through a reduction in systemic vascular resistance, involving both the sympathetic nervous system and the renin-angiotensin system, while also favorably affecting concomitant cardiovascular risk factors (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). In addition, regular physical activity is shown to reduce blood pressure by decreasing sympathetic nerve activity in individuals with hypertension since it leads to a decreased release of norepinephrine, which is responsible for vasoconstriction, thereby lowering vascular resistance. Furthermore, physical activity enhances insulin sensitivity and diminishes insulin-related sympathetic activity. It also lessens the vascular response to endothelin-1, another vasoconstrictor affecting those with hypertensionand cpromote vascular remodeling, which includes the formation of new arteries, an increase in the cross-sectional area, and the enlargement of existing veins and arteries. These structural changes ultimately contribute to reduced peripheral resistance and results in reducing blood pressure (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe study presents several strengths, notably its innovative approach to estimating fiber intake in Type 2 diabetes patients through proxy indicators, such as portion size estimation methods. It also employed the KOBO Collect tool for electronic data collection, effectively mitigating issues with missing data and ensuring that the information gathered was both thorough and precise. However, there are some limitations to consider. The emphasis on participants with both diabetes and hypertension may limit the generalizability of the findings to those with hypertension alone. Moreover, challenges arose from the Nutri Survey 2007 dataset, which had a user-unfriendly format that complicated data analysis and required more time and effort. Additionally, collecting food recipes for the 24-hour recall proved to be inconvenient. The timing of data collection coincided with fasting seasons, which could affect dietary habits. Lastly, there was a concern about social desirability bias, as the lack of private and comfortable environments hindered open discussions about eating habits.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study highlights a significant concern regarding the health of diabetic patients, with over three-fourths of respondents exhibiting poor blood pressure control and more than half struggling with glycemic management. The promising results associated with dietary fiber intake indicate a negative correlation with blood pressure, BMI, and glycemic control, suggesting that lifestyle modifications particularly increased dietary fiber consumption and physical activity, to play a crucial role in improving health outcomes for individuals with type 2 diabetes. It is essential to prioritize intensive care and targeted interventions for patients with multiple comorbidities to enhance their overall well-being and manage these interconnected health issues effectively through a comprehensive approach to lifestyle changes mentioned above.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAAU: Addis Ababa University;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eADA: American Diabetes Association;\u003c/p\u003e\n\u003cp\u003eBMI: Body Mass Index;\u003c/p\u003e\n\u003cp\u003eBP: Blood Pressure;\u003c/p\u003e\n\u003cp\u003eCVD: Cardio Vascular Diseases;\u003c/p\u003e\n\u003cp\u003eDM: Diabetes Mellitus;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDF: Dietary Fiber;\u003c/p\u003e\n\u003cp\u003eDiastolic Blood Pressure: DBP;\u003c/p\u003e\n\u003cp\u003eFBS: Fasting Blood Sugar;\u003c/p\u003e\n\u003cp\u003eHbA1C: Hemoglobin A1C;\u003c/p\u003e\n\u003cp\u003eNCD: Non Communicable Disease;\u003c/p\u003e\n\u003cp\u003ePSEM: Portion Size Estimation Method; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePPG: Postprandial Glucose;\u003c/p\u003e\n\u003cp\u003eRDA: \u0026nbsp; Recommended Daily Allowance;\u003c/p\u003e\n\u003cp\u003eSPSS: Statistical Product and Service Solutions;\u003c/p\u003e\n\u003cp\u003eSS: Sample size;\u003c/p\u003e\n\u003cp\u003eSystolic Blood Pressure: SBP \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWHO: World Health Organization\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all the patients who participated in the study. In addition, the authors express their deepest gratitude to Addis Ababa University, College of Health Science, School of public health and Department of Nutrition and Dietetics for providing me the opportunity. \u0026nbsp;The hospital administration and chronic OPD health professionals of each hospital, data collectors and Ethiopian Public Health Institute (EPHI) staff are acknowledged for their kind cooperation, willingness and unconditional support during the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003eDepartment of Nutrition and Dietetics, School of Public Health, Addis Ababa University\u003c/p\u003e\n\u003cp\u003eFeven Hailu \u003csup\u003e1\u003c/sup\u003e(BSc, MPH), Jemal Haidar Ali \u003csup\u003e1\u003c/sup\u003e (MD, MSc, CRM, CME, HD, Professor), Yakob Desalegn Nigatu \u003csup\u003e1\u003c/sup\u003e\u003csup\u003e*\u003c/sup\u003e (MD, MPH)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFH: Conceptualization, methodology, Data collection, data validation, formal analysis, writing\u0026mdash;original draft, and supervision. JH: Methodology review, validation, writing\u0026mdash;review and editing. YD: Data validation, writing\u0026mdash;review and editing. All authors\u0026nbsp;have read, critically revised and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical clearance was obtained from the Ethical Review Committee of the School of Public Health, College of Health Sciences, Addis Ababa University, and the Addis Ababa Health Bureau (Reference Number: SRH/296/2024). A legal permission letter was issued to the selected government hospitals. During data collection, oral informed consent was obtained from the study participants, and measures were taken to ensure the confidentiality of their information. The Study design and implementation were based on the Declaration of Helsinki and good practice (GCP) guidelines.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTesfaye F, Byass P, Wall S. Population based prevalence of high blood pressure among adults in Addis Ababa: uncovering a silent epidemic. BMC Cardiovasc Disord. 2009;9 (39doi:10.1186/1471-2261-9-39). Available at: http://www.biomedcentral.com/1471-2261/9/39. \u003c/li\u003e\n\u003cli\u003eLindstrom, M., DeCleene, N., Dorsey, H., Fuster, V., Johnson, C. O., LeGrand, K. E., Mensah, G. A., Razo, C., Stark, B., Varieur Turco, J., \u0026amp; Roth, G. A. (2022). Global Burden of Cardiovascular Diseases and Risks Collaboration, 1990-2021. 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Compliance to recommended dietary practices among patients with type 2 diabetes mellitus attending selected hospitals in Nakuru county. \u003c/li\u003e\n\u003cli\u003eTapela N, Collister J, Clifton L, et alPrevalence and determinants of hypertension control among almost 100 000 treated adults in the UKOpen Heart 2021;8:e001461. doi: 10.1136/openhrt-2020-001461. \u003c/li\u003e\n\u003cli\u003eKibret, K.T., Mesfin, Y.M. Prevalence of hypertension in Ethiopia: a systematic meta-analysis. Public Health Rev 36, 14 (2015). https://doi.org/10.1186/s40985-015-0014-z. \u003c/li\u003e\n\u003cli\u003eTesfaye, F., Byass, P. \u0026amp; Wall, S. Population based prevalence of high blood pressure among adults in Addis Ababa: uncovering a silent epidemic. BMC Cardiovasc Disord 9, 39 (2009). https://doi.org/10.1186/1471-2261-9-39. \u003c/li\u003e\n\u003cli\u003eDavid G. Harrison,David M. Patrick,Immune Mechanisms in Hypertension, Hypertension, 81, 8, (1659-1674), (2024). /doi/10.1161/HYPERTENSIONAHA.124.21355. \u003c/li\u003e\n\u003cli\u003eShariful Islam, M., Fardousi, A., Sizear, M.I. et al. Effect of leisure-time physical activity on blood pressure in people with hypertension: a systematic review and meta-analysis. Sci Rep 13, 10639 (2023). https://doi.org/10.1038/s41598-023-37149-2. \u003c/li\u003e\n\u003cli\u003eLaughlin MH, Korthuis RJ, Duncker DJ, Bache RJ. Control of blood flow to cardiac and skeletal muscle during exercise. Comprehensive Physiology. 2010 Jun:705-69. \u003c/li\u003e\n\u003cli\u003eIslam FMA, Islam MA, Hosen MA, Lambert EA, Maddison R, et al. (2023) Associations of physical activity levels, and attitudes towards physical activity with blood pressure among adults with high blood pressure in Bangladesh. PLOS ONE 18(2): e0280879. https://doi.org/10.1371/journal.pone.0280879. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Dietary fiber intake, hypertension, glycemic control, diabetes mellitus, Addis Ababa","lastPublishedDoi":"10.21203/rs.3.rs-7227814/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7227814/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eConsuming dietary fiber can contribute to a healthy diet and potentially safeguard the cardiovascular system. However, contextual data on this relationship are limited. Therefore, this study examined the role of dietary fiber intake on blood pressure control among Type 2 diabetic patients in selected facilities.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eAn institutional-based cross-sectional study design was conducted from March to April 2024. A total of 287 Type 2 DM patients were selected from health facilities in Addis Ababa using the multistage sampling. Data on blood pressure, fasting blood glucose, and other important variables were collected from all participants via the KOBO Collect mobile app. Dietary data were obtained through a repeated multiple-pass 24-hour recall, with portion sizes estimated and analyzed into nutrients using Nutri survey 2007. Data analysis was performed using SPSS version 27.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e\u003cp\u003eA significant proportion (79.4%) of respondents exhibited poor blood pressure control, while over half (56.7%) demonstrated poor glycemic control. Additionally, 10.3% of participants were classified as obese, and 39% had stage 2 hypertension. The mean dietary fiber intake was 32.5\u0026thinsp;\u0026plusmn;\u0026thinsp;20 g/day. An inverse correlation was observed between dietary fiber intake and blood pressure (BP), body mass index (BMI), and HbA1c levels. Furthermore, exercise and dietary fiber intake were significantly associated with better blood pressure control (p\u0026thinsp;\u0026lt;\u0026thinsp;0.005).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eOur findings illuminated the significant benefits of dietary fiber intake in managing blood pressure and glycemic control among individuals with multiple comorbidities. These results underscore the urgent need for targeted public health initiatives to promote healthy diets as a key strategy in preventing cardiovascular diseases.\u003c/p\u003e","manuscriptTitle":"The Effect of Dietary Fiber Intake on Blood Pressure Control among Type 2 Diabetic Patients in Selected Hospitals of Addis Ababa, Ethiopia: A Multi-Facility Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-27 07:01:50","doi":"10.21203/rs.3.rs-7227814/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-22T14:09:26+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-21T07:16:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"35939704120376006032495375832144768013","date":"2025-08-21T03:41:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"261821683309779030794454299070515603824","date":"2025-08-18T16:53:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"249066648286044882915305630623554913291","date":"2025-08-18T16:50:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-18T16:43:22+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-31T12:22:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-29T09:40:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-28T14:56:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-07-27T18:02:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"14fb5f8e-69d9-47dd-8763-acfa55a91b52","owner":[],"postedDate":"August 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":53602673,"name":"Health sciences/Diseases"},{"id":53602674,"name":"Health sciences/Endocrinology"},{"id":53602675,"name":"Health sciences/Health care"},{"id":53602676,"name":"Health sciences/Medical research"},{"id":53602677,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2025-11-24T16:02:20+00:00","versionOfRecord":{"articleIdentity":"rs-7227814","link":"https://doi.org/10.1038/s41598-025-24579-3","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-11-19 15:58:00","publishedOnDateReadable":"November 19th, 2025"},"versionCreatedAt":"2025-08-27 07:01:50","video":"","vorDoi":"10.1038/s41598-025-24579-3","vorDoiUrl":"https://doi.org/10.1038/s41598-025-24579-3","workflowStages":[]},"version":"v1","identity":"rs-7227814","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7227814","identity":"rs-7227814","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}