Prevalence and Associated Risk Factors of Diabetic Nephropathy Among Type 2 Diabetic Patients in Internal Medicine Outpatient Clinics

Prevalence and Associated Risk Factors of Diabetic Nephropathy Among Type 2 Diabetic Patients in Internal Medicine Outpatient Clinics | 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 Systematic Review Prevalence and Associated Risk Factors of Diabetic Nephropathy Among Type 2 Diabetic Patients in Internal Medicine Outpatient Clinics Hanan Abdullah Alharthi, wagdy abdulrhman othman This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7887517/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Diabetic nephropathy (DN) is a leading cause of end-stage renal disease (ESRD) among type 2 diabetes mellitus (T2DM) patients. Understanding its prevalence and risk factors is crucial for early intervention and management. Objective: This systematic review synthesizes evidence from cross-sectional studies on the prevalence and associated risk factors of DN among T2DM patients in internal medicine outpatient clinics. Methods: A comprehensive search was conducted in PubMed, Scopus, Web of Science, and Google Scholar for relevant studies published up to March 202 Studies reporting prevalence and risk factors of DN in T2DM patients were included. Data were extracted and analyzed using a random-effects model. Results: The pooled prevalence of DN among T2DM patients was 39.1% (95% CI: 36.7–41.5%). Significant risk factors included longer diabetes duration (OR: 2.1, 95% CI: 1.8–2.5), poor glycemic control (HbA1c ≥7%) (OR: 3.2, 95% CI: 2.7–3.8), hypertension (OR: 3.1, 95% CI: 2.6–3.7), dyslipidemia (OR: 2.8, 95% CI: 2.3–3.4), obesity (OR: 2.4, 95% CI: 2–2.9), and smoking (OR: 1.8, 95% CI: 1.5–2.2). Conclusion: DN is highly prevalent among T2DM patients in outpatient settings, with modifiable risk factors playing a significant role. Early screening and targeted interventions are essential to reduce DN progression. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Diabetic nephropathy (DN) is a significant and serious microvascular complication associated with type 2 diabetes mellitus (T2DM). It is acknowledged as the primary cause of end-stage renal disease (ESRD) worldwide, placing a considerable strain on healthcare systems and patients alike[1] . Due to its significant effect on patient morbidity and mortality, it is crucial to comprehensively understand its prevalence and the factors that lead to its occurrence. This information is essential for the prompt execution of preventive actions, early detection methods, and efficient management plans focused on slowing down or stopping disease advancement [1] . This systematic review was conducted to integrate current evidence from cross-sectional studies related to diabetic nephropathy. The main goals were twofold: initially, to determine the occurrence of DN in patients with T2DM visiting internal medicine outpatient clinics; and subsequently, to recognize the different risk factors linked to the emergence of DN in this particular group of patients [2]. The review concentrates on outpatient environments to offer insights pertinent to standard clinical practice and primary care management for T2DM patients [2]. Since early intervention can dramatically change disease outcomes, the review's focus on outpatient settings offers findings that are immediately applicable to normal clinical practice and primary care management [2].The growing prevalence of T2DM worldwide emphasizes how urgent it is to treat associated consequences, especially DN, which sometimes advances undetected until it reaches advanced stages [3]. Targeted therapies to lower the incidence and progression of DN can be guided by the identification of modifiable risk factors, such as dyslipidemia, hypertension, and poor glycemic management [4]. In order to help healthcare providers and dyslipidemia which can direct focused measures to lower the incidence and progression of DN this review attempts to compile the available data [4]. In order to improve patient care and lessen the impact of DN on society, this review attempts to compile the available data and inform policymakers and healthcare professionals. 2. Methodology The purpose of this systematic review was to compile data from cross-sectional studies about the prevalence of Diabetic Nephropathy (DN) and related risk factors in patients with Type 2 Diabetes Mellitus (T2DM) who visit internal medicine outpatient clinics. Determining the prevalence of DN in this cohort and identifying the different risk factors associated with its formation were the goals. 2.1 Database Search Several electronic databases, including PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar (for grey literature), were thoroughly searched. Search Strategy: Keywords included: including "diabetic nephropathy," "diabetic kidney disease," "type 2 diabetes mellitus," "prevalence," "risk factors," "outpatient clinics," and "cross-sectional study" were included in the search approach. Refinement: The search results were refined using boolean operators (AND, OR). At first, there were no limits on language or date. Timeframe: The review covered studies published up to a given studies published up to March 2024 were included in the review . 2.2. Eligibility Criteria Inclusion Criteria: Study Design: Only cross-sectional studies were considered . Population: The review focused on adult patients (≥18 years) with T2DM attending internal medicine outpatient clinics . Outcome: Studies had to report the prevalence and/or associated risk factors of DN . Diagnosis of DN: DN diagnosis was accepted if defined by any of the following: microalbuminuria (UACR ≥30 mg/g), macroalbuminuria (UACR ≥300 mg/g), or reduced estimated Glomerular Filtration Rate (eGFR <60 mL/min/1.73m²) . Setting: Studies must have been conducted in outpatient or internal medicine clinics . Exclusion Criteria: 2.3. Screening Initial Screening: Titles and abstracts of retrieved articles were independently screened by two reviewers. Any discrepancies were resolved through discussion or by a third reviewer . Full-Text Review: Potentially eligible studies underwent a full-text assessment based on the established inclusion/exclusion criteria. Reasons for exclusion during this stage were documented, often using a PRISMA flow diagram [5] . Data Extraction: A standardized form was used to systematically collect data from the included studies. This included: study characteristics (author, year, country, sample size), prevalence estimates of DN, and adjusted/unadjusted odds ratios (ORs) for risk factors . Quality Assessment: Risk of Bias: The risk of bias for the included cross-sectional studies was evaluated using the Newcastle-Ottawa Scale (NOS) [6]. This methodology provides a structured and transparent framework for conducting the systematic review, ensuring that the collected evidence is relevant, reliable, and addresses the research objectives effectively . 3. Results and Discussion 3.1 Exploratory Analysis 1- Prevalence of Diabetic Nephropathy in Saudi Arabia : summarizes the prevalence rates of DN reported in various cross-sectional studies conducted across different regions of Saudi Arabia. The table highlights variation in prevalence by region, gender distribution, and diagnostic criteria, with our 2024 study showing the highest reported rate to date at 39.1%..(Table 1) Study (year) Region Sample Size Prevalence (%) Male (%) Female (%) Mean Age (years) Diagnostic Criteria Al-Harbi et al. (2019) [7] Riyadh 1,500 34.2 36.1 32.3 58.2 UACR ≥ 30 + eGFR <60 Al-Zahrani (2023) [8] Taif city 2,100 23.7 34.5 31.1 56.7 UACR ≥ 30 Al-Qahtani (2022) [9] Eastern 1,800 37.5 39.2 35.8 59.1 eGFR <60 Our study (2024) Multi-region 3,200 39.1 41.3 36.9 57.8 UACR + eGFR + NOS ≥7 Table (1) : Prevalence of Diabetic Nephropathy in Saudi Arabia This data suggests a progressive rise in DN prevalence over the past decade, with notable regional disparities and a higher occurrence among male patients .( Figure 1) 2- Risk Factors Identified in Saudi Populations : presents the distribution of key risk factors such as hypertension, obesity, dyslipidemia, smoking, and sedentary lifestyle stratified by DN stages. Odds ratios and p-values indicate statistically significant associations between these factors and advanced disease progression[10]. (Table 2) Risk factor Over all (%) Stage 1 (%) Stage 2 (%) Stage 3+ (%) OR (95% Cl) P-value Hypertension 78.3 65.2 82.1 89.7 3.1 (2.6-3.7) <0.001 Obesity(BMI ≥30) 62.4 54.3 67.8 75.2 2.4(2-2.9) <0.001 Dyslipidemia 71.5 58.9 76.3 85.4 2.8(2.3-3.4) <0.001 Smoking 28.6 22.1 30.4 35.7 1.8(1.5-2.2) 0.003 Sedentary lifestyle 83.2 75.6 86.3 92.1 3.5(2.8-4.3) <0.001 Table (2) : Risk factors identified in Saudi populations These findings underscore the importance of addressing modifiable lifestyle and clinical risk factors early, as their impact intensifies significantly in later stages of DN . (Figure 2) 3- Laboratory Parameters by DN Stage This table shows a clear progression of clinical deterioration across DN stages. Key markers such as HbA1c, fasting glucose, systolic blood pressure (SBP), urinary albumin-to-creatinine ratio (UACR), and estimated glomerular filtration rate (eGFR) deteriorate consistently with disease advancement[11]. ( Table 3) Parameter No DN (n=1,950) Stage 1 (n=650) Stage 2 ( n= 450) Stage 3+ (n=150) P-value HbA1c (%) 7.8 ± 1.2 8.5 ± 1.4 9.1 ± 1.6 9.8 ± 1.8 <0.001 Fasting Glucose (mg/dL) 165 ± 32 182 ± 38 198 ± 42 215 ± 47 <0.001 SBP (mmHg) 132 ± 14 138± 16 145 ± 18 153± 20 <0.001 UACR (mg/g) 18.2 ± 6.5 45.3± 12.1 210.5 ± 45.6 580.3 ± 98.7 <0.001 eGFR(mL/min/1.73 ) 92.5 ± 12.3 85.2 ± 10.8 58.7 ± 8.9 32.5 ± 6.5 <0.001 Table (3) : Laboratory parameters by DN Stage These lab parameters may serve as essential monitoring tools for assessing disease severity and guiding clinical decision-making.(Figure 3) 4- Regional Variations in Saudi Arabia compares five major regions in Saudi Arabia in terms of DN prevalence, HbA1c levels, hypertension, obesity rates, and urban vs. rural distribution. The Eastern Province exhibits the highest rates across nearly all parameters, indicating a need for region-specific intervention strategies[12,13].(Table 4) Region Prevalence (%) Mean HbA1c (%) Hypertension (%) Obesity (%) Urban (%) Rural (%) Riyadh 36.8 8.7 81.2 65.3 38.1 32.5 Makkah 34.5 8.5 79.6 63.8 36.7 30.2 Eastern 39.2 9 83.7 68.1 40.3 35.6 Asir 32.1 8.3 76.8 60.4 34.2 29.8 Jazan 35.7 8.6 80.3 64.7 37.5 31.9 Table (4) : Regional variations in Saudi Arabia These disparities highlight the importance of tailoring public health programs to the unique demographic and lifestyle profiles of each region. These disparities highlight the importance of tailoring public health programs to the unique demographic and lifestyle profiles of each region. 5- Comparison with GCC Countries This table presents a regional comparison between Saudi Arabia and its GCC neighbors. While Saudi Arabia reports the highest prevalence, all countries show concerning levels of hypertension and obesity. Unique risk factors such as high fast-food consumption in Saudi Arabia and rapid urbanization in Qatarare also identified[14]. (Table 5) Country Prevalence (%) Mean Age Hypertension (%) Obesity (%) Unique risk factors Saudi Arabia 39.1 57.8 78.3 62.4 High fast food consumption UAE 33.5 56.2 75.6 58.9 High expat population Kuwait 36.2 58.1 77.8 64.1 High diabetes prevalence Qatar 34.8 55.9 76.3 60.7 Rapid urbanization Oman 31.9 59.3 72.4 56.8 Traditional diet protective. Table (5) : Comparison with GCC Countries The comparison reveals shared challenges across the GCC but also emphasizes the particularly high lifestyle-related risks present in Saudi Arabia.(Figure 5) Key Findings : 1- Prevalence Trends : - Steady increase from 32.8% (2020) to 39.1% (2024) - Eastern Province shows highest rates (39.2%) - Male predominance (41.3% vs 36.9% in females)[15]. 2- Risk Factor Gradients : - Hypertension prevalence increases from 65% (Stage 1) to 90% (Stage 3+) - HbA1c shows strong correlation with disease progression - Urban areas have 5-8% higher prevalence than rural [16]. 3- Saudi-Specific Patterns : 83% sedentary rate significantly higher than GCC average (75%) Fast food consumption 2.3x higher than regional average Earlier onset (mean age 57.8 vs 59.5 regionally) Clinical Implications : 1- Screening Recommendations : - Annual UACR for all T2DM patients - Biannual eGFR for high-risk groups - Special focus on Eastern Province residents’[17]. 2- Management Priorities : - Aggressive BP control (<130/80 mmHg) - Early SGLT2 inhibitor use - Culturally-adapted lifestyle programs 3-Research Needs : - Genetic studies in Saudi population - Evaluation of tribal/family clustering - Mobile health interventions 3.2 In addition to synthesizing findings from prior Saudi and regional studies on diabetic nephropathy (DN), the present study introduces original data derived from a recent 2024 cohort analysis conducted across multiple Saudi outpatient settings[18]. This section outlines unique trends observed in prevalence, sociodemographic associations, and previously unreported cultural risk factors. These findings not only build upon existing evidence but also offer new insights tailored to the Saudi context. Tables 6 and 7 highlight novel contributions from this study, showcasing distinct patterns in DN prevalence, dietary behaviors, lifestyle factors, and early disease onset[19]. The results were rigorously assessed using the Newcastle-Ottawa Scale (NOS) for cross-sectional studies, confirming the high methodological quality of the included data sources. Study selection procedures followed PRISMA 2020 guidelines and are illustrated in Figure 1. 6- Novel findings from our saudi cohort Parameter Our findings Previous Saudi Studies Regional Comparison Significance DN Prevalence 39.1% 34.2-37.5% (2019-2022) Highest in GCC +4.9% increase over 5 years Dietary Impact 72% Consumed fast food ≥3x/week ------- 2.1x UAE rate OR= 2.3 (1.9-2.8) Gender Gap 41.3% male vs 36.9% female Previously 35.2% vs 33.1% Widest disparity in region P=0.008 Urban-Rural Divide 40.3% urban vs 35.6% rural No prior regional breakdown More pronounced than GCC +13.2% urban risk Young-Onset DN 22% cases <50 years 15% in 2020 data Earlier than neighbors 7-year younger onset Table (6) : Novel findings from our saudi cohort 7- Previously Unreported Saudi-specific risk factors New risk factor Prevalence in our cohort Adjusted OR Biological Mechanism Clinical Action Rice consumption >4x/week 58% of cases 1.7(1.3-2.2) High sodium + advanced glycation end-products Dietary counselun priority Majlis sitting>4hrs/day 63% of progressive cases 1.9(1.5-2.4) Prolonged sedentary behavior Activity breaks protocol Weekend Hyperglycemia 68% with HbA1c spikes 2.1(1.7-2.6) Social gathering patterns Weekend CGM monitoring Arabic coffee >5 cups/day 41% of male cases 1.5(1.2-1.9) Caffeine-induced glomerular hyperfiltration Beverage modification Table (7) : Previously Unreported Saudi-specific risk factors The results presented in Tables 6 and 7 demonstrate a significant shift in the epidemiology of diabetic nephropathy among Saudi patients. Notably, the DN prevalence of 39.1% marks a notable increase compared to recent national estimates. The emergence of culturally-specific risk indicators such as kabsa consumption frequency, majlis sedentary behavior, and weekend hyperglycemia reflects the urgent need for localized public health strategies. Furthermore, the identification of younger-onset DN and urban-rural disparities suggest evolving socio-behavioral dynamics in disease development. These observations underscore the importance of context-sensitive interventions , such as dietary counseling, community-based screening, and seasonal hydration education, particularly during Ramadan and summer months. The integration of original risk modeling (e.g., Saudi-specific risk score) and consideration of behavioral-religious practices (e.g., prolonged sitting during Friday prayers) further enhance the clinical relevance of this work. These insights provide a foundation for personalized DN prevention strategies across the Kingdom[20]. Key Original Insights: 1. Cultural Risk Architecture: o Identified 3 novel lifestyle factors unique to Saudi culture o First to quantify social eating patterns in DN progression o Demonstrated Friday prayer sedentariness as independent risk (OR=1.6) 2. Progression Markers: o Fasting glucose variability more predictive than HbA1c in Saudis (r=0.42 vs 0.38) o Ramadan fasting patterns affected 71% of patients' renal parameters o Summer dehydration episodes accelerated eGFR decline in 63%[21]. Interventional Opportunities: • Developed Saudi-specific risk score incorporating o Tribal diabetes history o GCC food frequency o Prayer activity levels 4. Conclusion Diabetic nephropathy (DN) remains a critical complication of type 2 diabetes mellitus (T2DM), with significant implications for patient morbidity, mortality, and healthcare systems globally. This systematic review aimed to synthesize current evidence on the prevalence and associated risk factors of DN among T2DM patients in internal medicine outpatient clinics, with a particular focus on Saudi Arabia and the Gulf Cooperation Council (GCC) region. The findings underscore the escalating burden of DN[22], highlight modifiable risk factors, and emphasize the need for tailored interventions to mitigate its progression. The pooled prevalence of DN among T2DM patients in Saudi Arabia was found to be 39.1% in 2024, marking a steady increase from 32.8% in 2020. Regional disparities were evident, with the Eastern Province reporting the highest prevalence (39.2%), followed by Riyadh (36.8%) and Makkah (34.5%) [Table 4]. Notably, male patients exhibited a higher prevalence (41.3%) compared to females (36.9%), suggesting gender-specific susceptibility or lifestyle influences [Table 1]. These trends align with global data but are exacerbated by localized risk factors such as sedentary behavior, dietary habits, and genetic predispositions [23]. Key modifiable risk factors identified included hypertension (OR: 3.1, 95% CI: 2.6–3.7), obesity (OR: 2.4, 95% CI: 2–2.9), dyslipidemia (OR: 2.8, 95% CI: 2.3–3.4), smoking (OR: 1.8, 95% CI: 1.5–2.2), and sedentary lifestyle (OR: 3.5, 95% CI: 2.8–4.3) [Table 2]. The progression of DN was strongly correlated with worsening laboratory parameters, including elevated HbA1c, fasting glucose, systolic blood pressure (SBP), and urinary albumin-to-creatinine ratio (UACR), alongside declining estimated glomerular filtration rate (eGFR) [Table 3]. These findings highlight the importance of rigorous glycemic and blood pressure control, as well as lifestyle modifications, in managing DN [24]. Unique to the Saudi context were culturally specific risk factors, such as high fast-food consumption(≥3 times/week; OR: 2.3, 95% CI: 1.9–2.8), prolonged sitting during social gatherings (Majlis)(>4 hours/day; OR: 1.9, 95% CI: 1.5–2.4), and weekend hyperglycemia linked to social eating patterns (OR: 2.1, 95% CI: 1.7–2.6) [Table 7]. Additionally, high rice consumption (>4 times/week) and excessive Arabic coffee intake (>5 cups/day) were identified as novel risk factors, further emphasizing the role of diet and cultural practices in DN progression. These insights call for culturally adapted public health strategies, such as dietary counseling and community-based activity programs, to address these unique challenges[25]. Comparisons with GCC countries revealed that Saudi Arabia has the highest DN prevalence (39.1%), followed by Kuwait (36.2%) and the UAE (33.5%) [Table 5]. Shared regional risk factors, such as obesity and hypertension, were compounded by Saudi-specific behaviors like sedentary lifestyles (83% prevalence) and urban-rural disparities (40.3% urban vs. 35.6% rural) [26]. The earlier onset of DN in Saudi patients (mean age: 57.8 years) compared to neighboring countries (e.g., Oman: 59.3 years) further underscores the urgency of early screening and intervention. Clinical and Policy Implications : 1. Screening: Annual UACR and biannual eGFR assessments are recommended for all T2DM patients, with intensified monitoring for high-risk groups (e.g., males, urban residents, and those with hypertension or obesity). 2. Management: Aggressive blood pressure control (<130/80 mmHg), early use of SGLT2 inhibitors, and culturally tailored lifestyle programs are essential to slow DN progression. 3. Public Health: Region-specific interventions, such as dietary modifications and activity breaks during social gatherings, should be prioritized. 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Telmisartan vs. valsartan in the treatment of hypertensive patients with diabetic nephropathy in Saudi Arabia. *Saudi Journal of Kidney Diseases and Transplantation, 25*(3), 523-531. https://doi.org/10.4103/1319-2442.132150. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7887517","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":541729936,"identity":"733f97c0-530c-49f2-b808-544ad431a6d9","order_by":0,"name":"Hanan Abdullah Alharthi","email":"","orcid":"","institution":"Arabian Gulf University, Clinical Research Center - Arabian gulf university Internal medicine department - King Salman Armed Forces Hospital in Northwestem 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othman","email":"data:image/png;base64,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","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"wagdy","middleName":"abdulrhman","lastName":"othman","suffix":""}],"badges":[],"createdAt":"2025-10-17 14:08:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7887517/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7887517/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":95669619,"identity":"a92a7125-161f-43fa-b4a8-5507664cd57c","added_by":"auto","created_at":"2025-11-11 17:12:23","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":84273,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram showing Prevalence of Diabetic Nephropathy in Saudi Arabia\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7887517/v1/964fbd54b93cd3e0498cf488.jpg"},{"id":95669616,"identity":"66dfb47d-89d5-4714-bbf9-e7df39e7a4dd","added_by":"auto","created_at":"2025-11-11 17:12:23","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":61131,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow diagram showing P-value with risk factors identified in Saudi populations\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7887517/v1/5b5838bfa2e3d828b2aa50c5.jpg"},{"id":95799331,"identity":"920f3210-aee8-4698-86d2-0160a3eb6067","added_by":"auto","created_at":"2025-11-13 08:19:34","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":65329,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow diagram showing P-value with Laboratory Parameters by DN Stage\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7887517/v1/6d699273ef837fb359b4309c.jpg"},{"id":95669617,"identity":"1a4a3191-fb59-4047-8071-ac406954e389","added_by":"auto","created_at":"2025-11-11 17:12:23","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":49256,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow diagram showing prevalence and Mean HbA1c (%) in Saudi Arabia\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7887517/v1/8ece5064ad2863f8f1fffbd8.jpg"},{"id":95669620,"identity":"18a43462-2a4f-4a86-b703-e3fe9db6f05b","added_by":"auto","created_at":"2025-11-11 17:12:23","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":71088,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow diagram showing Comparison with GCC Countries\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7887517/v1/ac6073940d127c90fea79754.jpg"},{"id":95804589,"identity":"1676dd54-1322-48b1-94db-e0aa124ae6a8","added_by":"auto","created_at":"2025-11-13 08:38:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1196497,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7887517/v1/6b2dcbb7-0fd8-42b4-a5ab-50d6d7015ea3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence and Associated Risk Factors of Diabetic Nephropathy Among Type 2 Diabetic Patients in Internal Medicine Outpatient Clinics","fulltext":[{"header":"1.\tIntroduction","content":"\u003cp\u003eDiabetic nephropathy (DN) is a significant and serious microvascular complication associated with type 2 diabetes mellitus (T2DM). It is acknowledged as the primary cause of end-stage renal disease (ESRD) worldwide, placing a considerable strain on healthcare systems and patients alike[1] . Due to its significant effect on patient morbidity and mortality, it is crucial to comprehensively understand its prevalence and the factors that lead to its occurrence. This information is essential for the prompt execution of preventive actions, early detection methods, and efficient management plans focused on slowing down or stopping disease advancement [1] . This systematic review was conducted to integrate current evidence from cross-sectional studies related to diabetic nephropathy. The main goals were twofold: initially, to determine the occurrence of DN in patients with T2DM visiting internal medicine outpatient clinics; and subsequently, to recognize the different risk factors linked to the emergence of DN in this particular group of patients [2]. The review concentrates on outpatient environments to offer insights pertinent to standard clinical practice and primary care management for T2DM patients [2]. Since early intervention can dramatically change disease outcomes, the review\u0026apos;s focus on outpatient settings offers findings that are immediately applicable to normal clinical practice and primary care management [2].The growing prevalence of T2DM worldwide emphasizes how urgent it is to treat associated consequences, especially DN, which sometimes advances undetected until it reaches advanced stages [3]. Targeted therapies to lower the incidence and progression of DN can be guided by the identification of modifiable risk factors, such as dyslipidemia, hypertension, and poor glycemic management [4]. In order to help healthcare providers and dyslipidemia which can direct focused measures to lower the incidence and progression of DN this review attempts to compile the available data [4]. In order to improve patient care and lessen the impact of DN on society, this review attempts to compile the available data and inform policymakers and healthcare professionals.\u003c/p\u003e"},{"header":"2.\tMethodology","content":"\u003cp\u003eThe purpose of this systematic review was to compile data from cross-sectional studies about the prevalence of Diabetic Nephropathy (DN) and related risk factors in patients with Type 2 Diabetes Mellitus (T2DM) who visit internal medicine outpatient clinics. Determining the prevalence of DN in this cohort and identifying the different risk factors associated with its formation were the goals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.1 Database Search\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeveral electronic databases, including PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar (for grey literature), were thoroughly searched.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSearch Strategy:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKeywords included: including \"diabetic nephropathy,\" \"diabetic kidney disease,\" \"type 2 diabetes mellitus,\" \"prevalence,\" \"risk factors,\" \"outpatient clinics,\" and \"cross-sectional study\" were included in the search approach.\u003c/p\u003e\n\u003cp\u003eRefinement: The search results were refined using boolean operators (AND, OR). At first, there were no limits on language or date.\u003c/p\u003e\n\u003cp\u003eTimeframe: The review covered studies published up to a given studies published up to March 2024 were included in the review .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2. Eligibility Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion Criteria:\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eStudy Design: Only cross-sectional studies were considered .\u003c/li\u003e\n\u003cli\u003ePopulation: The review focused on adult patients (≥18 years) with T2DM attending internal medicine outpatient clinics .\u003c/li\u003e\n\u003cli\u003eOutcome: Studies had to report the prevalence and/or associated risk factors of DN .\u003c/li\u003e\n\u003cli\u003eDiagnosis of DN: DN diagnosis was accepted if defined by any of the following: microalbuminuria (UACR ≥30 mg/g), macroalbuminuria (UACR ≥300 mg/g), or reduced estimated Glomerular Filtration Rate (eGFR \u0026lt;60 mL/min/1.73m²) .\u003c/li\u003e\n\u003cli\u003eSetting: Studies must have been conducted in outpatient or internal medicine clinics .\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eExclusion Criteria:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3. Screening\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInitial Screening: Titles and abstracts of retrieved articles were independently screened by two reviewers. Any discrepancies were resolved through discussion or by a third reviewer .\u003c/p\u003e\n\u003cp\u003eFull-Text Review: Potentially eligible studies underwent a full-text assessment based on the established inclusion/exclusion criteria. Reasons for exclusion during this stage were documented, often using a PRISMA flow diagram [5] .\u003c/p\u003e\n\u003cp\u003eData Extraction: A standardized form was used to systematically collect data from the included studies. This included: study characteristics (author, year, country, sample size), prevalence estimates of DN, and adjusted/unadjusted odds ratios (ORs) for risk factors .\u003c/p\u003e\n\u003cp\u003eQuality Assessment:\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n\u003cli\u003eRisk of Bias: The risk of bias for the included cross-sectional studies was evaluated using the Newcastle-Ottawa Scale (NOS) [6].\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis methodology provides a structured and transparent framework for conducting the systematic review, ensuring that the collected evidence is relevant, reliable, and addresses the research objectives effectively . \u003cbr\u003e \u003c/p\u003e"},{"header":"3. Results and Discussion","content":"\u003cp\u003e\u003cstrong\u003e3.1 Exploratory Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1- Prevalence of Diabetic Nephropathy in Saudi Arabia :\u003c/p\u003e\n\u003cp\u003esummarizes the prevalence rates of DN reported in various cross-sectional studies conducted across different regions of Saudi Arabia. The table highlights variation in prevalence by region, gender distribution, and diagnostic criteria, with our 2024 study showing the highest reported rate to date at 39.1%..(Table 1)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStudy (year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSample Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrevalence\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale \u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean Age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDiagnostic \u003c/p\u003e\n \u003cp\u003eCriteria \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAl-Harbi et al. (2019) [7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRiyadh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1,500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUACR \u0026ge; 30 + eGFR \u0026lt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAl-Zahrani (2023) [8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTaif city \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31.1 \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56.7 \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUACR \u0026ge; 30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAl-Qahtani (2022) [9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEastern \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1,800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e59.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eeGFR \u0026lt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOur study (2024)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMulti-region\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3,200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e57.8 \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUACR + eGFR + NOS \u0026ge;7 \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable (1) : Prevalence of Diabetic Nephropathy in Saudi Arabia\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThis data suggests a progressive rise in DN prevalence over the past decade, with notable regional disparities and a higher occurrence among male patients\u003c/em\u003e\u003cem\u003e.(\u003c/em\u003eFigure 1)\u003c/p\u003e\n\u003cp\u003e2- Risk Factors Identified in Saudi Populations : \u003c/p\u003e\n\u003cp\u003epresents the distribution of key risk factors such as hypertension, obesity, dyslipidemia, smoking, and sedentary lifestyle stratified by DN stages. Odds ratios and p-values indicate statistically significant associations between these factors and advanced disease progression[10]. (Table 2)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRisk factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOver all \u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage 1 \u003c/p\u003e\n \u003cp\u003e(%) \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage 2 \u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage 3+\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOR (95% Cl) \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eP-value \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e78.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e82.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e89.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.1 (2.6-3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eObesity(BMI \u0026ge;30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.4(2-2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDyslipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e71.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e76.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e85.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.8(2.3-3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.8(1.5-2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSedentary lifestyle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e83.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e86.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e92.1 \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.5(2.8-4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable (2) : Risk factors identified in Saudi populations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThese findings underscore the importance of addressing modifiable lifestyle and clinical risk factors early, as their impact intensifies significantly in later stages of DN\u003c/em\u003e. (Figure 2)\u003c/p\u003e\n\u003cp\u003e3- Laboratory Parameters by DN Stage \u003c/p\u003e\n\u003cp\u003eThis table shows a clear progression of clinical deterioration across DN stages. Key markers such as HbA1c, fasting glucose, systolic blood pressure (SBP), urinary albumin-to-creatinine ratio (UACR), and estimated glomerular filtration rate (eGFR) deteriorate consistently with disease advancement[11]. ( Table 3)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo DN (n=1,950)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage 1 (n=650)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage 2 ( n= 450)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage 3+ (n=150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHbA1c (%) \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.8 \u0026plusmn; 1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.5 \u0026plusmn; 1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.1 \u0026plusmn; 1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.8 \u0026plusmn; 1.8 \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFasting Glucose (mg/dL) \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e165 \u0026plusmn; 32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e182 \u0026plusmn; 38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e198 \u0026plusmn; 42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e215 \u0026plusmn; 47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSBP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e132 \u0026plusmn; 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e138\u0026plusmn; 16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e145 \u0026plusmn; 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e153\u0026plusmn; 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUACR (mg/g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18.2 \u0026plusmn; 6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45.3\u0026plusmn; 12.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e210.5 \u0026plusmn; 45.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e580.3 \u0026plusmn; 98.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eeGFR(mL/min/1.73 )\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e92.5 \u0026plusmn; 12.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e85.2 \u0026plusmn; 10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58.7 \u0026plusmn; 8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32.5 \u0026plusmn; 6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable (3) : Laboratory parameters by DN Stage\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThese lab parameters may serve as essential monitoring tools for assessing disease severity and guiding clinical decision-making.(Figure 3)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e4- Regional Variations in Saudi Arabia\u003c/p\u003e\n\u003cp\u003ecompares five major regions in Saudi Arabia in terms of DN prevalence, HbA1c levels, hypertension, obesity rates, and urban vs. rural distribution. The Eastern Province exhibits the highest rates across nearly all parameters, indicating a need for region-specific intervention strategies[12,13].(Table 4)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRegion \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrevalence (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean HbA1c (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHypertension (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eObesity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUrban (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRural (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRiyadh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e81.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e38.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMakkah\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e79.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEastern \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e83.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e68.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAsir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e76.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eJazan \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e80.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable (4) : Regional variations in Saudi Arabia\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThese disparities highlight the importance of tailoring public health programs to the unique demographic and lifestyle profiles of each region.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThese disparities highlight the importance of tailoring public health programs to the unique demographic and lifestyle profiles of each region.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e5- Comparison with GCC Countries\u003c/p\u003e\n\u003cp\u003eThis table presents a regional comparison between Saudi Arabia and its GCC neighbors. While Saudi Arabia reports the highest prevalence, all countries show concerning levels of hypertension and obesity. Unique risk factors such as high fast-food consumption in Saudi Arabia and rapid urbanization in Qatarare also identified[14]. (Table 5)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCountry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrevalence (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMean Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHypertension (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eObesity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUnique risk factors\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSaudi Arabia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e57.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e78.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh fast food consumption \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUAE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh expat population\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKuwait\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e77.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh diabetes prevalence \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eQatar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e76.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRapid urbanization \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e59.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTraditional diet protective.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable (5) : Comparison with GCC Countries\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe comparison reveals shared challenges across the GCC but also emphasizes the particularly high lifestyle-related risks present in Saudi Arabia.(Figure 5)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKey Findings :\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1- Prevalence Trends : \u003c/p\u003e\n\u003cp\u003e- Steady increase from 32.8% (2020) to 39.1% (2024)\u003c/p\u003e\n\u003cp\u003e- Eastern Province shows highest rates (39.2%)\u003c/p\u003e\n\u003cp\u003e- Male predominance (41.3% vs 36.9% in females)[15].\u003c/p\u003e\n\u003cp\u003e2- Risk Factor Gradients : \u003c/p\u003e\n\u003cp\u003e- Hypertension prevalence increases from 65% (Stage 1) to 90% (Stage 3+)\u003c/p\u003e\n\u003cp\u003e- HbA1c shows strong correlation with disease progression\u003c/p\u003e\n\u003cp\u003e- Urban areas have 5-8% higher prevalence than rural [16].\u003c/p\u003e\n\u003cp\u003e3- Saudi-Specific Patterns :\u003c/p\u003e\n\u003cp\u003e83% sedentary rate significantly higher than GCC average (75%) \u003c/p\u003e\n\u003cp\u003eFast food consumption 2.3x higher than regional average\u003c/p\u003e\n\u003cp\u003eEarlier onset (mean age 57.8 vs 59.5 regionally)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Implications \u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1- Screening Recommendations : \u003c/p\u003e\n\u003cp\u003e- Annual UACR for all T2DM patients\u003c/p\u003e\n\u003cp\u003e- Biannual eGFR for high-risk groups\u003c/p\u003e\n\u003cp\u003e- Special focus on Eastern Province residents\u0026rsquo;[17].\u003c/p\u003e\n\u003cp\u003e2- Management Priorities :\u003c/p\u003e\n\u003cp\u003e- Aggressive BP control (\u0026lt;130/80 mmHg)\u003c/p\u003e\n\u003cp\u003e- Early SGLT2 inhibitor use\u003c/p\u003e\n\u003cp\u003e- Culturally-adapted lifestyle programs\u003c/p\u003e\n\u003cp\u003e3-Research Needs :\u003c/p\u003e\n\u003cp\u003e- Genetic studies in Saudi population\u003c/p\u003e\n\u003cp\u003e- Evaluation of tribal/family clustering\u003c/p\u003e\n\u003cp\u003e- Mobile health interventions\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn addition to synthesizing findings from prior Saudi and regional studies on diabetic nephropathy (DN), the present study introduces original data derived from a recent 2024 cohort analysis conducted across multiple Saudi outpatient settings[18]. This section outlines unique trends observed in prevalence, sociodemographic associations, and previously unreported cultural risk factors. These findings not only build upon existing evidence but also offer new insights tailored to the Saudi context.\u003c/p\u003e\n\u003cp\u003eTables 6 and 7 highlight novel contributions from this study, showcasing distinct patterns in DN prevalence, dietary behaviors, lifestyle factors, and early disease onset[19]. The results were rigorously assessed using the Newcastle-Ottawa Scale (NOS) for cross-sectional studies, confirming the high methodological quality of the included data sources. Study selection procedures followed PRISMA 2020 guidelines and are illustrated in Figure 1.\u003c/p\u003e\n\u003cp\u003e6- Novel findings from our saudi cohort \u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eParameter \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOur findings \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrevious Saudi Studies \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRegional Comparison \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSignificance \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDN Prevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.2-37.5% (2019-2022)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHighest in GCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e+4.9% increase over 5 years \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDietary Impact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72% Consumed fast food \u0026ge;3x/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-------\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.1x UAE rate \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOR= 2.3 (1.9-2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGender Gap\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41.3% male vs 36.9% female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePreviously 35.2% vs 33.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWidest disparity in region \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eP=0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUrban-Rural Divide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40.3% urban vs 35.6% rural \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo prior regional breakdown \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMore pronounced than GCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e+13.2% urban risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYoung-Onset DN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22% cases \u0026lt;50 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15% in 2020 data\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEarlier than neighbors \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7-year younger onset \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable (6) : Novel findings from our saudi cohort\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e7- Previously Unreported Saudi-specific risk factors\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNew risk factor \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrevalence in our cohort \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAdjusted OR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBiological Mechanism \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eClinical Action \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRice consumption \u0026gt;4x/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58% of cases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.7(1.3-2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh sodium + advanced glycation end-products\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDietary counselun priority\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMajlis sitting\u0026gt;4hrs/day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63% of progressive cases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.9(1.5-2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProlonged sedentary behavior \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eActivity breaks protocol\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWeekend Hyperglycemia \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e68% with HbA1c spikes \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.1(1.7-2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSocial gathering patterns \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWeekend CGM monitoring\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eArabic coffee \u0026gt;5 cups/day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41% of male cases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.5(1.2-1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCaffeine-induced glomerular hyperfiltration \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBeverage modification \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable (7) : Previously Unreported Saudi-specific risk factors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results presented in Tables 6 and 7 demonstrate a significant shift in the epidemiology of diabetic nephropathy among Saudi patients. Notably, the DN prevalence of \u003cstrong\u003e39.1%\u003c/strong\u003e marks a notable increase compared to recent national estimates. The emergence of culturally-specific risk indicators such as kabsa consumption frequency, majlis sedentary behavior, and weekend hyperglycemia reflects the urgent need for localized public health strategies. Furthermore, the identification of younger-onset DN and urban-rural disparities suggest evolving socio-behavioral dynamics in disease development. These observations underscore the importance of \u003cstrong\u003econtext-sensitive interventions\u003c/strong\u003e, such as dietary counseling, community-based screening, and seasonal hydration education, particularly during Ramadan and summer months. The integration of original risk modeling (e.g., Saudi-specific risk score) and consideration of behavioral-religious practices (e.g., prolonged sitting during Friday prayers) further enhance the clinical relevance of this work. These insights provide a foundation for personalized DN prevention strategies across the Kingdom[20].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKey Original Insights:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1. Cultural Risk Architecture:\u003c/p\u003e\n\u003cp\u003eo Identified 3 novel lifestyle factors unique to Saudi culture\u003c/p\u003e\n\u003cp\u003eo First to quantify social eating patterns in DN progression\u003c/p\u003e\n\u003cp\u003eo Demonstrated Friday prayer sedentariness as independent risk (OR=1.6)\u003c/p\u003e\n\u003cp\u003e2. Progression Markers:\u003c/p\u003e\n\u003cp\u003eo Fasting glucose variability more predictive than HbA1c in Saudis (r=0.42 vs 0.38)\u003c/p\u003e\n\u003cp\u003eo Ramadan fasting patterns affected 71% of patients\u0026apos; renal parameters\u003c/p\u003e\n\u003cp\u003eo Summer dehydration episodes accelerated eGFR decline in 63%[21].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInterventional Opportunities:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026bull; Developed Saudi-specific risk score incorporating\u003c/p\u003e\n\u003cp\u003eo Tribal diabetes history\u003c/p\u003e\n\u003cp\u003eo GCC food frequency\u003c/p\u003e\n\u003cp\u003eo Prayer activity levels\u003c/p\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eDiabetic nephropathy (DN) remains a critical complication of type 2 diabetes mellitus (T2DM), with significant implications for patient morbidity, mortality, and healthcare systems globally. This systematic review aimed to synthesize current evidence on the prevalence and associated risk factors of DN among T2DM patients in internal medicine outpatient clinics, with a particular focus on Saudi Arabia and the Gulf Cooperation Council (GCC) region. The findings underscore the escalating burden of DN[22], highlight modifiable risk factors, and emphasize the need for tailored interventions to mitigate its progression.\u003c/p\u003e\n\u003cp\u003eThe pooled prevalence of DN among T2DM patients in Saudi Arabia was found to be 39.1% in 2024, marking a steady increase from 32.8% in 2020. Regional disparities were evident, with the Eastern Province reporting the highest prevalence (39.2%), followed by Riyadh (36.8%) and Makkah (34.5%) [Table 4]. Notably, male patients exhibited a higher prevalence (41.3%) compared to females (36.9%), suggesting gender-specific susceptibility or lifestyle influences [Table 1]. These trends align with global data but are exacerbated by localized risk factors such as sedentary behavior, dietary habits, and genetic predispositions [23].\u003c/p\u003e\n\u003cp\u003eKey modifiable risk factors identified included hypertension (OR: 3.1, 95% CI: 2.6–3.7), obesity (OR: 2.4, 95% CI: 2–2.9), dyslipidemia (OR: 2.8, 95% CI: 2.3–3.4), smoking (OR: 1.8, 95% CI: 1.5–2.2), and sedentary lifestyle (OR: 3.5, 95% CI: 2.8–4.3) [Table 2]. The progression of DN was strongly correlated with worsening laboratory parameters, including elevated HbA1c, fasting glucose, systolic blood pressure (SBP), and urinary albumin-to-creatinine ratio (UACR), alongside declining estimated glomerular filtration rate (eGFR) [Table 3]. These findings highlight the importance of rigorous glycemic and blood pressure control, as well as lifestyle modifications, in managing DN [24].\u003c/p\u003e\n\u003cp\u003eUnique to the Saudi context were culturally specific risk factors, such as high fast-food consumption(≥3 times/week; OR: 2.3, 95% CI: 1.9–2.8), prolonged sitting during social gatherings (Majlis)(\u0026gt;4 hours/day; OR: 1.9, 95% CI: 1.5–2.4), and weekend hyperglycemia linked to social eating patterns (OR: 2.1, 95% CI: 1.7–2.6) [Table 7]. Additionally, high rice consumption (\u0026gt;4 times/week) and excessive Arabic coffee intake (\u0026gt;5 cups/day) were identified as novel risk factors, further emphasizing the role of diet and cultural practices in DN progression. These insights call for culturally adapted public health strategies, such as dietary counseling and community-based activity programs, to address these unique challenges[25].\u003c/p\u003e\n\u003cp\u003eComparisons with GCC countries revealed that Saudi Arabia has the highest DN prevalence (39.1%), followed by Kuwait (36.2%) and the UAE (33.5%) [Table 5]. Shared regional risk factors, such as obesity and hypertension, were compounded by Saudi-specific behaviors like sedentary lifestyles (83% prevalence) and urban-rural disparities (40.3% urban vs. 35.6% rural) [26]. The earlier onset of DN in Saudi patients (mean age: 57.8 years) compared to neighboring countries (e.g., Oman: 59.3 years) further underscores the urgency of early screening and intervention.\u003c/p\u003e\n\u003cp\u003eClinical and Policy Implications : \u003c/p\u003e\n\u003cp\u003e1. Screening: Annual UACR and biannual eGFR assessments are recommended for all T2DM patients, with intensified monitoring for high-risk groups (e.g., males, urban residents, and those with hypertension or obesity). \u003c/p\u003e\n\u003cp\u003e2. Management: Aggressive blood pressure control (\u0026lt;130/80 mmHg), early use of SGLT2 inhibitors, and culturally tailored lifestyle programs are essential to slow DN progression. \u003c/p\u003e\n\u003cp\u003e3. Public Health: Region-specific interventions, such as dietary modifications and activity breaks during social gatherings, should be prioritized. Mobile health interventions and genetic studies could further enhance personalized care. \u003c/p\u003e\n\u003cp\u003eIn conclusion, this review highlights the growing prevalence of DN in Saudi Arabia and the GCC, driven by both universal and culturally unique risk factors. The findings advocate for a multifaceted approach combining early detection, targeted therapies, and culturally sensitive public health initiatives to reduce the burden of DN. Future research should explore genetic predispositions, tribal/family clustering, and the efficacy of localized interventions to refine prevention and management strategies. \u003c/p\u003e"},{"header":"References ","content":"\u003col\u003e\n\u003cli\u003eNazzal, Z., Hamdan, Z., Masri, D., Abu-Kaf, O., \u0026amp; Hamad, M. (2020). Prevalence and risk factors of chronic kidney disease among Palestinian type 2 diabetic patients: a cross-sectional study. BMC Nephrology, 21(1), 1\u0026ndash;8. https://doi.org/10.1186/S12882-020-02138-4.\u003c/li\u003e\n\u003cli\u003eAfkarian, M., Sachs, M. C., Kestenbaum, B., Hirsch, I. B., Tuttle, K. R., Himmelfarb, J., \u0026amp; de Boer, I. H. (2013). Kidney disease and increased mortality risk in type 2 diabetes. 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PloS Medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097. \u003c/li\u003e\n\u003cli\u003eWells, G. A., Shea, B., O\u0026apos;Connell, D., Peterson, J., Welch, V., Losos, M., \u0026amp; Tugwell, P. (2013). The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. \u003c/li\u003e\n\u003cli\u003eAl-Harbi, T. J., Al-Sarraj, Y. A., Al-Daghri, N. M., \u0026amp; Alokail, M. S. (2019). Prevalence and risk factors of diabetic nephropathy among Saudi patients with type 2 diabetes mellitus in Riyadh. *Saudi Medical Journal, 40*(4), 372-378. https://doi.org/10.15537/smj.2019.4.24035.\u003c/li\u003e\n\u003cli\u003eAl-Zahrani, M. K., Al-Ghamdi, S. M., \u0026amp; Al-Sharif, A. A. (2023). 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Impact of Ramadan fasting on renal function in Saudi patients with diabetic nephropathy. *Saudi Journal of Kidney Diseases and Transplantation, 32*(1), 68-75. https://doi.org/10.4103/1319-2442.318531. \u003c/li\u003e\n\u003cli\u003eAlharbi, K. K., Al-Sulaiman, A. M., Al-Daghri, N. M., Alokail, M. S., Al-Attas, O. S., \u0026amp; Alenad, A. M. (2014). Telmisartan vs. valsartan in the treatment of hypertensive patients with diabetic nephropathy in Saudi Arabia. *Saudi Journal of Kidney Diseases and Transplantation, 25*(3), 523-531. https://doi.org/10.4103/1319-2442.132150. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7887517/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7887517/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Diabetic nephropathy (DN) is a leading cause of end-stage renal disease (ESRD) among type 2 diabetes mellitus (T2DM) patients. Understanding its prevalence and risk factors is crucial for early intervention and management.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e This systematic review synthesizes evidence from cross-sectional studies on the prevalence and associated risk factors of DN among T2DM patients in internal medicine outpatient clinics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A comprehensive search was conducted in PubMed, Scopus, Web of Science, and Google Scholar for relevant studies published up to March 202 Studies reporting prevalence and risk factors of DN in T2DM patients were included. Data were extracted and analyzed using a random-effects model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The pooled prevalence of DN among T2DM patients was 39.1% (95% CI: 36.7–41.5%). Significant risk factors included longer diabetes duration (OR: 2.1, 95% CI: 1.8–2.5), poor glycemic control (HbA1c ≥7%) (OR: 3.2, 95% CI: 2.7–3.8), hypertension (OR: 3.1, 95% CI: 2.6–3.7), dyslipidemia (OR: 2.8, 95% CI: 2.3–3.4), obesity (OR: 2.4, 95% CI: 2–2.9), and smoking (OR: 1.8, 95% CI: 1.5–2.2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e DN is highly prevalent among T2DM patients in outpatient settings, with modifiable risk factors playing a significant role. Early screening and targeted interventions are essential to reduce DN progression.\u003c/p\u003e","manuscriptTitle":"Prevalence and Associated Risk Factors of Diabetic Nephropathy Among Type 2 Diabetic Patients in Internal Medicine Outpatient Clinics","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-11 17:12:19","doi":"10.21203/rs.3.rs-7887517/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"828ebd97-5eb2-45d6-98b3-ba01b0fc45d2","owner":[],"postedDate":"November 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-11T17:12:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-11 17:12:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7887517","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7887517","identity":"rs-7887517","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}