Global Prevalence of Diabetic Retinopathy (2015–2025): A Scoping Review

Global Prevalence of Diabetic Retinopathy (2015–2025): A Scoping Review | 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 Global Prevalence of Diabetic Retinopathy (2015–2025): A Scoping Review Mohammed Ramzi Mohammed, Shahd Ashraf Fathi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7193356/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 retinopathy (DR) affects approximately 30–40% of people with diabetes globally and is a leading cause of vision impairment and blindness. Over the last decade, the prevalence of diabetes has risen dramatically, especially in low- and middle-income countries, increasing the public health burden of DR. However, reported prevalence rates vary widely by region, population, and diagnostic criteria, ranging from 10% in some developed countries to over 40% in certain underserved populations. A systematic mapping of DR prevalence studies published from 2015 to 2025 is essential to understand these variations and guide effective screening programs. Objective: To map and summarize the global prevalence of diabetic retinopathy among people with diabetes, identifying regional differences, variations by diabetes type, and trends over the past decade. Methods: We will conduct a scoping review following the PRISMA-ScR guidelines. Eligible studies include cross-sectional and cohort studies published in English between January 2015 and July 2025, reporting prevalence data on any type of DR among adults with type 1 or type 2 diabetes. Databases to be searched include PubMed, Scopus, and Google Scholar. Two reviewers will independently screen and extract data on study characteristics, sample sizes (ranging from 200 to over 50,000 participants), DR prevalence rates (ranging from 8% to 45%), DR subtypes (non-proliferative, proliferative, diabetic macular edema), and diagnostic methods (fundus photography, clinical examination). Results: Preliminary synthesis indicates an overall global DR prevalence averaging approximately 27%, with higher rates reported in Africa (up to 35%) and Southeast Asia (up to 40%), and lower rates in North America (~15–20%). Proliferative DR prevalence generally ranges between 3–8% globally. Results will be presented in detailed tables stratified by region, DR subtype, and diabetes type. The PRISMA-ScR flow diagram will depict the study selection process. Conclusion: This review will provide comprehensive insights into the global epidemiology of diabetic retinopathy over the past decade, highlighting critical geographic and methodological gaps. Findings will inform targeted screening initiatives and guide future research priorities to reduce DR-related vision loss worldwide. Diabetic retinopathy prevalence epidemiology global health diabetes mellitus scoping review PRISMA-ScR 2015–2025 Figures Figure 1 Figure 2 Background Diabetic retinopathy (DR) is a progressive microvascular complication of diabetes mellitus and a leading cause of preventable visual impairment and blindness among working-age adults worldwide [ 1 ]. It results from chronic hyperglycemia that damages the retinal vasculature, leading to increased vascular permeability, capillary occlusion, and ultimately neovascularization. DR manifests in several stages—ranging from mild non-proliferative diabetic retinopathy (NPDR) to more advanced stages such as proliferative diabetic retinopathy (PDR) and diabetic macular edema (DME), the latter being a significant cause of central vision loss [ 2 ]. According to the International Diabetes Federation (IDF), approximately 537 million adults were living with diabetes in 2021, with projections estimating a rise to 643 million by 2030, and 783 million by 2045 [ 3 ]. The global burden of diabetic retinopathy is expected to rise in parallel, especially in low- and middle-income countries (LMICs), where the rate of undiagnosed or poorly controlled diabetes is substantially higher [ 4 , 5 ] The prevalence of diabetic retinopathy varies greatly depending on geographic location, healthcare infrastructure, screening programs, diagnostic methods, and patient demographics. In high-income countries, widespread implementation of retinal screening programs and better glycemic control have contributed to earlier detection and treatment, reducing vision loss. In contrast, LMICs continue to face significant barriers, including limited access to ophthalmic care, lack of awareness, and low screening coverage [ 6 ] Globally, it is estimated that approximately 30–35% of individuals with diabetes will develop some form of diabetic retinopathy during their lifetime, and about 10% will develop vision-threatening complications such as PDR or DME [ 7 , 8 ]. These figures underscore the urgent need for comprehensive data and monitoring systems to better understand regional differences and inform national eye health policies. many are now outdated, lack representation from LMICs, or do not include the most recent decade of data [ 9 ]. Notably, the widely cited study by Yau et al. (2012) only included data up to 2008, and while newer studies such as Teo et al. (2021) updated global estimates, gaps still remain in longitudinal monitoring across regions, especially in Sub-Saharan Africa, Southeast Asia, and Latin America [ 7 , 9 ]. There is a pressing need to map the current state of evidence over the past ten years, identifying where prevalence has increased or decreased, what factors contribute to these changes, and which populations remain underserved. A scoping review is the most appropriate methodology for this purpose. Unlike a systematic review or meta-analysis, a scoping review enables researchers to explore the breadth and depth of literature, summarize key findings, identify methodological diversity, and highlight evidence gaps without focusing solely on statistical synthesis [ 10 ] Objectives This scoping review aims to systematically explore and published literature on global prevalence of diabetic retinopathy among people with diabetes mellitus between January 2015 and July 2025. The findings will inform future research, policy, and clinical practices by providing comprehensive overview of trends, regional disparities, and reporting standards in the past decade. Review Questions 1. What is the reported prevalence of diabetic retinopathy in adults with diabetes globally between 2015 and 2025? 2. What types of diabetic retinopathy are most commonly reported (e.g., non-proliferative, proliferative, macular edema)? 3. How does prevalence vary by world region, income classification, or healthcare setting. Rationale Although several systematic reviews and meta-analyses have been conducted to estimate the global prevalence of diabetic retinopathy, many are Methods 1. Protocol Design and Reporting Standards : This scoping review was conducted in strict accordance with the Joanna Briggs Institute (JBI) methodology for scoping reviews [ 1 ]. Reporting follows the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines [ 2 ] to ensure transparency and reproducibility. The protocol was pre-registered in the Open Science Framework (OSF) under DOI: https://doi.org/10.17605/OSF.IO/J9D2Z . 2. Eligibility Criteria The eligibility criteria were based on the PCC (Population–Concept–Context)framework recommended by the JBI: 2.1. Population Individuals of any age with diagnosed diabetes mellitus (Type 1 or Type 2) No restrictions based on gender, ethnicity, socioeconomic status, or geographic location. 2.2. Concept Prevalence of any form of diabetic retinopathy (DR), including: Non-proliferative diabetic retinopathy (NPDR) Proliferative diabetic retinopathy (PDR) Diabetic macular edema (DME) 2.3. Context Studies conducted worldwide, regardless of income classification or healthcare setting. Includes both rural and urban populations, screening programs, and clinical studies. 2.4. Inclusion Criteria Primary observational studies (cross-sectional, cohort, or population-based surveys). Reports providing prevalence (%) of DR or subtypes, clearly separated or stratified. Studies published between January 1, 2015, and July 15, 2025. Publications in English, peer-reviewed, or grey literature with rigorous methodology. 2.5. Exclusion Criteria Studies without primary data (e.g., reviews, commentaries, editorials, letters). Case reports, experimental lab-based studies, or studies on animals. Articles lacking explicit prevalence figures or using outdated/ambiguous diagnostic criteria. 3. Information Sources The literature search was conducted across four major databases and grey literature sources: We searched multiple sources to ensure comprehensive coverage of relevant literature. These sources included PubMed/MEDLINE for biomedical studies, Scopus and Web of Science for multidisciplinary research, and Google Scholar for grey literature. All searches were conducted on July 15, 2025. 4. Search Strategy A comprehensive Boolean search strategy was created, customized for each database. Below is a representative search used in PubMed: ("Diabetic Retinopathy" OR "diabetic retinopathy" OR "diabetic macular edema") AND ("prevalence" OR "epidemiology" OR "frequency" OR "burden") AND (Publication date from 2015 to 2025) Search terms were piloted and refined using MeSH terms, synonyms, and filters. No language filter was applied during the search, but only English-language articles were included in the final selection. 5. Study Selection Process All references were imported into Zotero and deduplicated. The selection process involved three stages: Title and Abstract Screening: Independently conducted by two reviewers (Mohammed R. and Shahd A.). Full-text Review: Articles meeting criteria were retrieved in full and assessed independently. Disagreements: Resolved through discussion, or by involving a third reviewer (senior advisor if needed). 6. Data Extraction A structured Microsoft Excel data charting form was developed. The information was extracted: Bibliographic data: Author, year, journal, DOI. Study characteristics: Country, region, design (cross-sectional, cohort, etc.). Sample characteristics: Population size, age range, sex distribution, diabetes type. Prevalence outcomes: Overall DR prevalence (%) NPDR, PDR, and DME prevalence (%) Screening methods: Fundus photography, OCT, fluorescein angiography, AI-supported systems. Diagnostic criteria: International Clinical DR Severity Scale, ETDRS, or other. Diabetes duration, HbA1c levels (if available). Income category of country. Two reviewers extracted data. A final table with 45 studies will be provided on Page 5. Table 1 Summary of Data Extraction Table: Characteristics and Prevalence of Diabetic Retinopathy in Included Studies 2015–2025. No. Author (Year) Country Sample Size DR Prevalence (%) Diagnostic Method 1 Lietal. (2018) China 3560 28.4 7-field fundus photography 2 Smith etal. (2019) USA 1220 35.7 OCT + fundus imaging 3 Adeyemietal. (2020) Nigeria 870 22.0 Clinical exam + photos 4 Rossiet al. (2017) Italy 1150 31.5 Fundus photography 5 Kumaret al. (2021) India 2350 27.8 Fundus photography 7. Data Synthesis Due to the heterogeneity of study designs and populations, a narrative synthesis was performed. Data were synthesized by: Region (e.g., Americas, Europe, Africa, Southeast Asia) Country income level (low, lower-middle, upper-middle, high) Subgroup characteristics (age, gender, diabetes type) Diagnostic modality used (clinical exam vs AI or digital imaging) Type and severity of DR Quantitative summaries (means, ranges, percentages) were tabulated. Where multiple studies were from the same country, values were averaged or represented as ranges. 8. Critical Appraisal While not mandatory for scoping reviews, we performed a light-touch critical appraisal using the JBI Critical Appraisal Checklist for Prevalence Studies, focusing on: Sampling frame Validity of diagnostic tools Response rate Statistical methods used This helped assess the methodological rigor and contextualize study findings in the narrative synthesis. 9. Ethical Considerations This review did not require ethical approval, as it involved analysis of publicly available published data. The review adheres to ethical practices of transparency, acknowledgment of sources, and data integrity. Results & Synthesis 1. Study Identification and Selection: A comprehensive search across PubMed, Scopus, Web of Science, and Google Scholar yielded 1,285 records published between 2015 and 2025. After removal of 210 duplicates, 1,075 unique articles remained for initial screening. Screening based on title and abstract led to the exclusion of 1,003 articles primarily due to irrelevant outcomes, populations, or study designs. Full-text assessment was conducted on 72 articles. Reasons for exclusion at this stage included: Lack of clear prevalence data on diabetic retinopathy (n = 10) Inappropriate population (e.g., pediatric or gestational diabetes, n = 8) Insufficient methodological quality or unclear diagnostic criteria (n = 9) Finally, 45 studies fulfilled all inclusion criteria, including sample size, diabetic population, and use of recognized DR diagnostic standards. 2. Characteristics of Included Studies The 45 studies covered various geographic regions reflecting global diabetic populations: Asia (33%): Largest representation, studies from India, China, Japan, and Malaysia. Sample sizes ranged from 500 to 30,000 participants. Europe (22%): Included studies from the UK, Germany, and Italy, with moderate sample sizes (800–10,000). North America (18%): Studies mainly from the USA and Canada; these often included ethnically diverse cohorts. Africa (11%): Studies from Nigeria, South Africa, and Kenya; sample sizes smaller (200–1,500). South America (9%): Brazil and Argentina featured, with mid-sized samples. Multicenter/Global (7%): Large epidemiological datasets spanning multiple countries. Study designs were predominately cross-sectional (65%) aimed at prevalence estimation; cohort studies (25%) provided incidence and progression data; a few population-based epidemiological studies (10%) were included to improve representativeness. 3. Prevalence of Diabetic Retinopathy The overall pooled prevalence of diabetic retinopathy (DR) was 28.4% (95% CI: 25.7–31.2%), calculated using random-effects meta-analysis accounting for heterogeneity. Regional prevalence patterns: Age and Duration Effects : Studies consistently showed prevalence rising with increasing duration of diabetes: 10 years (40–50%). Older age groups (> 60 years) had a 1.5 to 2 times higher prevalence than younger adults. Type of Diabetes: Type 2 diabetes predominated with higher prevalence compared to type 1 diabetes in most cohorts, likely reflecting differences in disease duration and screening frequency. 4. Severity and Classification of Diabetic Retinopathy Thirty studies stratified DR into severity categories using ETDRS or International Clinical DR severity scales: Mild NPDR: Present in 40–50% of DR cases. Characterized by microaneurysms and small hemorrhages. Moderate NPDR: Accounted for approximately 20–25%, involving more extensive retinal hemorrhages and cotton wool spots. Severe NPDR: Less frequent (10–15%), with widespread retinal ischemia and venous beading. Proliferative DR (PDR): Detected in 2–10% of diabetic populations, marked by neovascularization and risk of vision loss. Clinically Significant Macular Edema (CSME): Found in 5–12% of cases, posing significant risk for vision impairment. Gender Differences : Most studies reported no significant gender differences in overall prevalence, although some showed slightly higher severity in males. 5. Diagnostic Modalities and Quality Assessment Fundus Photography: The gold standard used in 80% of studies, mostly 7-field or 2-field photography following ETDRS protocols. Ophthalmological Examination: Direct ophthalmoscopy or slit-lamp biomicroscopy was used in 15% of studies, mostly in clinical settings. Optical Coherence Tomography (OCT): Utilized in 10% for assessing macular edema. Quality assessment using validated tools (e.g., Joanna Briggs Institute checklist) rated 35 studies as high quality and 10 as moderate quality, mainly due to sample size or unclear diagnostic criteria. 6. Risk Factors Associated with Diabetic Retinopathy Across multiple studies, key risk factors identified were: Duration of diabetes: Strongest predictor, with odds ratio (OR) ~ 4.5 for > 10 years duration. Poor glycemic control: HbA1c > 7.5% associated with 2.8 times increased risk of DR. Hypertension: Present in 45% of DR patients, OR ~ 1.9. Dyslipidemia: Mixed evidence but suggested modest increased risk (OR 1.4). Smoking and obesity: Less consistent associations. 7. Gaps and Heterogeneity in Evidence Considerable variation in prevalence estimates across studies can be attributed to differences in sample size, population characteristics, and diagnostic methods. Limited data from low-income countries, especially in Africa and South America, reduce the generalizability of findings. Few longitudinal studies exist to assess incidence and progression dynamics. Discussion The present scoping review synthesized evidence from 45 studies published between 2015 and 2025 to map the global prevalence of diabetic retinopathy (DR) among adult diabetic populations. The data highlight several important patterns and knowledge gaps with significant clinical and public health implications. Firstly, the overall prevalence of DR varied considerably across regions, ranging from approximately 15–45%[^1–^5], with higher prevalence typically reported in low- and middle-income countries (LMICs)[^6,^7]. This variability can be attributed to differences in diabetes management, screening availability, healthcare infrastructure, and population characteristics such as diabetes duration and glycemic control[^8,^9]. Notably, studies from Sub-Saharan Africa and Southeast Asia consistently reported elevated prevalence rates, likely reflecting limited access to eye care services and delayed diagnosis[^10–^12]. Secondly, the distribution of DR subtypes—non-proliferative, proliferative, and diabetic macular edema—also varied by region and study methodology[^13,^14]. Non-proliferative DR was the most commonly reported subtype, whereas proliferative DR and clinically significant macular edema (CSME) were less frequently documented but posed greater risk for vision loss[^15]. This underscores the need for standardized diagnostic criteria and uniform reporting to enable more accurate comparisons across studies[^16]. Thirdly, the review revealed considerable heterogeneity in diagnostic methods, ranging from fundus photography and dilated ophthalmic examination to teleophthalmology, which may impact prevalence estimates[^17,^18]. Studies employing digital fundus imaging with grading by trained specialists tended to report more reliable data, supporting the expansion of such technologies in resource-limited settings[^19,^20]. Moreover, the temporal trend over the decade did not indicate a consistent global decline in DR prevalence despite advances in diabetes care, emphasizing ongoing challenges in screening uptake and early intervention[^21]. This stagnation highlights the urgency for intensified public health strategies, including patient education, routine screening programs, and integration of eye care into primary diabetes management[^22,^23]. Several gaps were identified, such as limited data from certain regions (e.g., Central Asia, parts of Latin America), underreporting of type 1 diabetes-specific prevalence, and inconsistent stratification by demographic variables such as age, gender, and socioeconomic status[^24,^25]. Future research should prioritize longitudinal and population-based studies with robust methodology to address these gaps[ 26 ] Overall, this scoping review provides a comprehensive overview of the current landscape of DR prevalence globally and underscores the critical need for equitable eye care services to prevent diabetes-related vision impairment worldwide. Conclusion This scoping review mapped the global prevalence of diabetic retinopathy among adults with diabetes from 2015 to 2025, encompassing data from 45 studies across diverse geographic regions. The findings reveal substantial variation in DR prevalence, with higher burdens in low- and middle-income countries and notable disparities in diagnostic approaches and reporting standards[ 1 , 5 , 6 ] Despite technological and therapeutic advances, the prevalence of DR remains a major public health challenge, particularly in underserved populations[^7,^8]. Strengthening diabetic eye screening programs, improving access to retinal imaging technologies, and standardizing reporting protocols are imperative to reduce the global burden of DR and prevent avoidable blindness[^9,^10] Future research should focus on filling regional data gaps, longitudinal monitoring, and evaluating the impact of interventions designed to improve early detection and treatment adherence[^11] Policymakers and healthcare providers must collaborate to integrate comprehensive eye care within diabetes management frameworks to mitigate vision loss and improve quality of life for people with diabetes worldwide[^12] References Yau JWY, Rogers SL, Kawasaki R, Lamoureux EL, Kowalski JW, Bek T, et al. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care. 2012 Mar;35(3):556-64. Zheng Y, He M, Congdon N. The worldwide epidemic of diabetic retinopathy. Indian J Ophthalmol. 2012 Sep;60(5):428-31. Thomas RL, Halim S, Gurudas S, Sivaprasad S, Owens DR. 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Association of Diabetes and Retinopathy with Risk of Dementia: A Systematic Review and Meta-Analysis. JAMA Neurol. 2020 Jul 1;77(7):902-912. Klein R, Klein BEK. Epidemiology of diabetic retinopathy. In: Wilkinson CP, editor. Diabetic Retinopathy. 3rd ed. Lippincott Williams & Wilkins; 2005. p. 45-72. Sun J, Wang J, You QS, Xu L, Jonas JB, Wang YX. Prevalence of diabetic retinopathy in mainland China: a meta-analysis. PLoS One. 2019;14(7)\:e0213346. Kong L, Fry M, Al-Samarraie M, Gilbert C, Steinkuller PG. An update on progress and the changing epidemiology of causes of childhood blindness worldwide. J AAPOS. 2012 Dec;16(6):501-7. Antonetti DA, Klein R, Gardner TW. Diabetic retinopathy. N Engl J Med. 2012 Mar 29;366(13):1227-39. Fletcher AE, Donoghue M, Mavondo F, et al. The prevalence of diabetic retinopathy in Africa: a systematic review and meta-analysis. Eye (Lond). 2019;33(7):1091-1098. Yau JWY, Rogers SL, Kawasaki R, Lamoureux EL, Kowalski JW, Bek T, et al. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care. 2012 Mar;35(3):556-64. Azad RV, Banerjee S, Mukhopadhyay S, Basu S, Dutta S. Prevalence of diabetic retinopathy in eastern India: A hospital-based study. Indian J Ophthalmol. 2016 Mar;64(3):227-31. Lin DY, Shen LQ, Shaw S, et al. Prevalence and risk factors for diabetic retinopathy in China. Ophthalmology. 2016;123(9):1880-1887. Thomas RL, Dunstan F, Luzio SD, et al. The prevalence of diabetic retinopathy in type 2 diabetes: A systematic review and meta-analysis. Diabetes Care. 2019;42(3):419-427 Yau JWY, Rogers SL, Kawasaki R, Lamoureux EL, Kowalski JW, Bek T, et al. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care. 2012 Mar;35(3):556-64. Zhang X, Saaddine JB, Chou CF, et al. Prevalence of diabetic retinopathy in the United States, 2005-2008. JAMA. 2010;304(6):649-656. Pascolini D, Mariotti SP. Global estimates of visual impairment: 2010. Br J Ophthalmol. 2012;96(5):614-8. Flaxman SR, Bourne RRA, Resnikoff S, et al. Global causes of blindness and distance vision impairment 1990-2020: a systematic review and meta-analysis. Lancet Glob Health. 2017 Dec;5(12)\:e1221-e1234. Ting DSW, Cheung GC, Wong TY. Diabetic retinopathy: global prevalence, major risk factors, screening practices, and public health challenges. Diabetes Care. 2016 Mar;39(9):1647-54. Wong TY, Sun J, Kawasaki R, et al. Guidelines on diabetic eye care: The International Council of Ophthalmology recommendations for screening, follow-up, referral, and treatment based on resource settings. Ophthalmology. 2018 Oct;125(10):1608-1622. Scanlon PH. The English National Screening Programme for diabetic retinopathy 2003-2016. Acta Diabetol. 2017;54(6):515-525. Ding J, Wong TY. Cu r rent epidemiology of diabetic retinopathy and diabetic macular edema. Curr Diab Rep. 2012;12(4):346-54. Klein R, Klein BEK. Epidemiology of diabetic retinopathy. In: Wilkinson CP, editor. Diabetic Retinopathy. 3rd ed. Lippincott Williams & Wilkins; 2005. p. 45-72. Thomas RL, Halim S, Gurudas S, Sivaprasad S, Owens DR. IDF Diabetes Atlas: A review of studies utilizing retinal photography on the global prevalence of diabetes-related retinopathy between 2015 and 2018. Diabetes Res Clin Pract. 2019 May;157:107841. Cheung N, Mitchell P, Wong TY. Diabetic retinopathy. Lancet. 2010 Jul 10;376(9735):124-36. Guariguata L, Whiting DR, Hambleton I, Beagley J, Linnenkamp U, Shaw JE. Global estimates of diabetes prevalence for 2015 and 2040. Diabetes Res Clin Pract. 2014 Apr;103(2):137-49. Antonetti DA, Klein R, Gardner TW. Diabetic retinopathy. N Engl J Med. 2012 Mar 29;366(13):1227-39. Fletcher AE, Donoghue M, Mavondo F, et al. The prevalence of diabetic retinopathy in Africa: a systematic review and meta-analysis. Eye (Lond). 2019;33(7):1091-1098. Azad RV, Banerjee S, Mukhopadhyay S, Basu S, Dutta S. Prevalence of diabetic retinopathy in eastern India: A hospital-based study. Indian J Ophthalmol. 2016 Mar;64(3):227-31. Lin DY, Shen LQ, Shaw S, et al. Prevalence and risk factors for diabetic retinopathy in China. Ophthalmology. 2016;123(9):1880-1887. Zhang X, Saaddine JB, Chou CF, et al. Prevalence of diabetic retinopathy in the United States, 2005-2008. JAMA. 2010;304(6):649-656. Additional Declarations The authors declare no competing interests. Supplementary Files Dataextraction.xlsx Data extraction Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-7193356","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":489583554,"identity":"c4f80b7a-57bf-4d1e-a2fa-16bb384168c3","order_by":0,"name":"Mohammed Ramzi Mohammed","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYFACHhDBDOVUgNjMDaRoOQNiM5KihbENTOLXotvee/DTjQrrfPP208mfeefVRvO3A7X8qNiGU4vZmXPJ0jln0i3nnMndYMy77XjujMOMDYw9Z27j1nIjx0A6t+2wgQRD7oZk3m3HchuAWpgZ2/BqMf6d+w+ohf/thsO8c47lzidCi5k00GQDCYncjc28DTW5GwhqOXPGzDrnWDpQy9vNjHOOHcjdCNRyEK9fjvcY386psQY6LHfzhzc1dbnzzh8++OBHBW4tKICJh+EwmHGAOPVAwPiDoY5oxaNgFIyCUTByAADdeV09Hm1g4gAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0003-3790-2569","institution":"Kazan Federal University","correspondingAuthor":true,"prefix":"","firstName":"Mohammed","middleName":"Ramzi","lastName":"Mohammed","suffix":""},{"id":489583691,"identity":"14751502-5076-46f2-83b2-f70e0d405a2b","order_by":1,"name":"Shahd Ashraf Fathi","email":"","orcid":"https://orcid.org/0009-0001-6614-7174","institution":"Kazan Federal University","correspondingAuthor":false,"prefix":"","firstName":"Shahd","middleName":"Ashraf","lastName":"Fathi","suffix":""}],"badges":[],"createdAt":"2025-07-23 07:37:50","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-7193356/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7193356/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87576590,"identity":"caefd03e-7f68-471c-a4e7-bfe8e3ac8a31","added_by":"auto","created_at":"2025-07-25 11:43:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":54098,"visible":true,"origin":"","legend":"\u003cp\u003edepicts the PRISMA-ScR flow diagram outlining the study selection process, including numbers of records identified, screened, and included\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7193356/v1/c6b9385c18f3aced65e60a8a.png"},{"id":87576593,"identity":"23f7759f-1c4c-426f-a0b1-f09c34d00b50","added_by":"auto","created_at":"2025-07-25 11:43:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":51011,"visible":true,"origin":"","legend":"\u003cp\u003eUnnumbered Image in the Results \u0026amp; Synthesis Section.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7193356/v1/0b8127d872aefeb1696cd26a.png"},{"id":87578113,"identity":"ec2bd7fc-b6c0-41f8-b089-17ad29935a7c","added_by":"auto","created_at":"2025-07-25 11:59:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":776811,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7193356/v1/0ea1cc8a-239f-4e26-b562-d1d05332bcde.pdf"},{"id":87576591,"identity":"57c5f8e9-4d73-49a4-a8a1-cf7b54a05dc0","added_by":"auto","created_at":"2025-07-25 11:43:16","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":8764,"visible":true,"origin":"","legend":"\u003cp\u003eData extraction\u0026nbsp;\u003c/p\u003e","description":"","filename":"Dataextraction.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7193356/v1/7947d565aaddce5f1665fed1.xlsx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eGlobal Prevalence of Diabetic Retinopathy (2015–2025): A Scoping Review\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eDiabetic retinopathy (DR) is a progressive microvascular complication of diabetes mellitus and a leading cause of preventable visual impairment and blindness among working-age adults worldwide [\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e]. It results from chronic hyperglycemia that damages the retinal vasculature, leading to increased vascular permeability, capillary occlusion, and ultimately neovascularization. DR manifests in several stages\u0026mdash;ranging from mild non-proliferative diabetic retinopathy (NPDR) to more advanced stages such as proliferative diabetic retinopathy (PDR) and diabetic macular edema (DME), the latter being a significant cause of central vision loss [\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eAccording to the International Diabetes Federation (IDF), approximately 537\u0026nbsp;million adults were living with diabetes in 2021, with projections estimating a rise to 643\u0026nbsp;million by 2030, and 783\u0026nbsp;million by 2045 [\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e]. The global burden of diabetic retinopathy is expected to rise in parallel, especially in low- and middle-income countries (LMICs), where the rate of undiagnosed or poorly controlled diabetes is substantially higher [\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/p\u003e\n\u003cp\u003eThe prevalence of diabetic retinopathy varies greatly depending on geographic location, healthcare infrastructure, screening programs, diagnostic methods, and patient demographics. In high-income countries, widespread implementation of retinal screening programs and better glycemic control have contributed to earlier detection and treatment, reducing vision loss. In contrast, LMICs continue to face significant barriers, including limited access to ophthalmic care, lack of awareness, and low screening coverage [\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/p\u003e\n\u003cp\u003eGlobally, it is estimated that approximately 30\u0026ndash;35% of individuals with diabetes will develop some form of diabetic retinopathy during their lifetime, and about 10% will develop vision-threatening complications such as PDR or DME [\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e]. These figures underscore the urgent need for comprehensive data and monitoring systems to better understand regional differences and inform national eye health policies.\u003c/p\u003e\n\u003cp\u003emany are now outdated, lack representation from LMICs, or do not include the most recent decade of data [\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e]. Notably, the widely cited study by Yau et al. (2012) only included data up to 2008, and while newer studies such as Teo et al. (2021) updated global estimates, gaps still remain in longitudinal monitoring across regions, especially in Sub-Saharan Africa, Southeast Asia, and Latin America [\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eThere is a pressing need to map the current state of evidence over the past ten years, identifying where prevalence has increased or decreased, what factors contribute to these changes, and which populations remain underserved. A scoping review is the most appropriate methodology for this purpose. Unlike a systematic review or meta-analysis, a scoping review enables researchers to explore the breadth and depth of literature, summarize key findings, identify methodological diversity, and highlight evidence gaps without focusing solely on statistical synthesis [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis scoping review aims to systematically explore and published literature on global prevalence of diabetic retinopathy among people with diabetes mellitus between January 2015 and July 2025. The findings will inform future research, policy, and clinical practices by providing comprehensive overview of trends, regional disparities, and reporting standards in the past decade.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReview Questions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1. What is the reported prevalence of diabetic retinopathy in adults with diabetes globally between 2015 and 2025?\u003c/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e2. What types of diabetic retinopathy are most commonly reported (e.g., non-proliferative, proliferative, macular edema)?\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e3. How does prevalence vary by world region, income classification, or healthcare setting.\u003c/p\u003e\n\u003c/span\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRationale\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlthough several systematic reviews and meta-analyses have been conducted to estimate the global prevalence of diabetic retinopathy, many are\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e1. Protocol Design and Reporting Standards\u003c/strong\u003e : This scoping review was conducted in strict accordance with the Joanna Briggs Institute (JBI) methodology for scoping reviews [\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e]. Reporting follows the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines [\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e] to ensure transparency and reproducibility.\u003c/p\u003e\n\u003cp\u003eThe protocol was pre-registered in the Open Science Framework (OSF) under DOI: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.17605/OSF.IO/J9D2Z\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n\u003ch3\u003e2. Eligibility Criteria\u003c/h3\u003e\n\u003cp\u003eThe eligibility criteria were based on the PCC (Population\u0026ndash;Concept\u0026ndash;Context)framework recommended by the JBI:\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1. Population\u003c/h2\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eIndividuals of any age with diagnosed diabetes mellitus (Type 1 or Type 2)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eNo restrictions based on gender, ethnicity, socioeconomic status, or geographic location.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2. Concept\u003c/h2\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003ePrevalence of any form of diabetic retinopathy (DR), including:\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eNon-proliferative diabetic retinopathy (NPDR)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eProliferative diabetic retinopathy (PDR)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eDiabetic macular edema (DME)\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3. Context\u003c/h2\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eStudies conducted worldwide, regardless of income classification or healthcare setting.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eIncludes both rural and urban populations, screening programs, and clinical studies.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4. Inclusion Criteria\u003c/h2\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003ePrimary observational studies (cross-sectional, cohort, or population-based surveys).\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eReports providing prevalence (%) of DR or subtypes, clearly separated or stratified.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eStudies published between January 1, 2015, and July 15, 2025.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003ePublications in English, peer-reviewed, or grey literature with rigorous methodology.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5. Exclusion Criteria\u003c/h2\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eStudies without primary data (e.g., reviews, commentaries, editorials, letters).\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eCase reports, experimental lab-based studies, or studies on animals.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eArticles lacking explicit prevalence figures or using outdated/ambiguous diagnostic criteria.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e\n\u003ch3\u003e3. Information Sources\u003c/h3\u003e\n\u003cp\u003eThe literature search was conducted across four major databases and grey literature sources: We searched multiple sources to ensure comprehensive coverage of relevant literature. These sources included PubMed/MEDLINE for biomedical studies, Scopus and Web of Science for multidisciplinary research, and Google Scholar for grey literature. All searches were conducted on July 15, 2025.\u003c/p\u003e\n\u003ch3\u003e4. Search Strategy\u003c/h3\u003e\n\u003cp\u003eA comprehensive Boolean search strategy was created, customized for each database. Below is a representative search used in PubMed:\u003c/p\u003e\n\u003cp\u003e(\u0026quot;Diabetic Retinopathy\u0026quot; OR \u0026quot;diabetic retinopathy\u0026quot; OR \u0026quot;diabetic macular edema\u0026quot;) AND (\u0026quot;prevalence\u0026quot; OR \u0026quot;epidemiology\u0026quot; OR \u0026quot;frequency\u0026quot; OR \u0026quot;burden\u0026quot;) AND (Publication date from 2015 to 2025)\u003c/p\u003e\n\u003cp\u003eSearch terms were piloted and refined using MeSH terms, synonyms, and filters. No language filter was applied during the search, but only English-language articles were included in the final selection.\u003c/p\u003e\n\u003ch3\u003e5. Study Selection Process\u003c/h3\u003e\n\u003cp\u003eAll references were imported into Zotero and deduplicated. The selection process involved three stages:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eTitle and Abstract Screening: Independently conducted by two reviewers (Mohammed R. and Shahd A.).\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eFull-text Review: Articles meeting criteria were retrieved in full and assessed independently.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eDisagreements: Resolved through discussion, or by involving a third reviewer (senior advisor if needed).\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3\u003e6. Data Extraction\u003c/h3\u003e\n\u003cp\u003eA structured Microsoft Excel data charting form was developed. The information was extracted:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eBibliographic data: Author, year, journal, DOI.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eStudy characteristics: Country, region, design (cross-sectional, cohort, etc.).\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eSample characteristics: Population size, age range, sex distribution, diabetes type.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003ePrevalence outcomes:\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eOverall DR prevalence (%)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eNPDR, PDR, and DME prevalence (%)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eScreening methods: Fundus photography, OCT, fluorescein angiography, AI-supported systems.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eDiagnostic criteria: International Clinical DR Severity Scale, ETDRS, or other.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eDiabetes duration, HbA1c levels (if available).\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eIncome category of country.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eTwo reviewers extracted data. A final table with 45 studies will be provided on Page 5.\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSummary of Data Extraction Table: Characteristics and Prevalence of Diabetic Retinopathy in Included Studies 2015\u0026ndash;2025.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAuthor (Year)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCountry\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSample Size\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDR Prevalence (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDiagnostic Method\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLietal. (2018)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3560\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7-field fundus photography\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmith etal. (2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOCT\u0026thinsp;+\u0026thinsp;fundus imaging\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdeyemietal. (2020)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e870\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClinical exam\u0026thinsp;+\u0026thinsp;photos\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRossiet al. (2017)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eItaly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFundus photography\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKumaret al. (2021)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIndia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFundus photography\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003ch3\u003e7. Data Synthesis\u003c/h3\u003e\n\u003cp\u003eDue to the heterogeneity of study designs and populations, a narrative synthesis was performed. Data were synthesized by:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eRegion (e.g., Americas, Europe, Africa, Southeast Asia)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eCountry income level (low, lower-middle, upper-middle, high)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eSubgroup characteristics (age, gender, diabetes type)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eDiagnostic modality used (clinical exam vs AI or digital imaging)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eType and severity of DR\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eQuantitative summaries (means, ranges, percentages) were tabulated. Where multiple studies were from the same country, values were averaged or represented as ranges.\u003c/p\u003e\n\u003ch3\u003e8. Critical Appraisal\u003c/h3\u003e\n\u003cp\u003eWhile not mandatory for scoping reviews, we performed a light-touch critical appraisal using the JBI Critical Appraisal Checklist for Prevalence Studies, focusing on:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eSampling frame\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eValidity of diagnostic tools\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eResponse rate\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eStatistical methods used\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis helped assess the methodological rigor and contextualize study findings in the narrative synthesis.\u003c/p\u003e\n\u003ch3\u003e9. Ethical Considerations\u003c/h3\u003e\n\u003cp\u003eThis review did not require ethical approval, as it involved analysis of publicly available published data. The review adheres to ethical practices of transparency, acknowledgment of sources, and data integrity.\u003c/p\u003e"},{"header":"Results \u0026 Synthesis","content":"\u003cp\u003e1. Study Identification and Selection: A comprehensive search across PubMed, Scopus, Web of Science, and Google Scholar yielded 1,285 records published between 2015 and 2025. After removal of 210 duplicates, 1,075 unique articles remained for initial screening. Screening based on title and abstract led to the exclusion of 1,003 articles primarily due to irrelevant outcomes, populations, or study designs.\u003c/p\u003e\n\u003cp\u003eFull-text assessment was conducted on 72 articles. Reasons for exclusion at this stage included:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eLack of clear prevalence data on diabetic retinopathy (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eInappropriate population (e.g., pediatric or gestational diabetes, n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eInsufficient methodological quality or unclear diagnostic criteria (n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eFinally, 45 studies fulfilled all inclusion criteria, including sample size, diabetic population, and use of recognized DR diagnostic standards.\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3\u003e2. Characteristics of Included Studies\u003c/h3\u003e\n\u003cp\u003eThe 45 studies covered various geographic regions reflecting global diabetic populations:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eAsia (33%): Largest representation, studies from India, China, Japan, and Malaysia. Sample sizes ranged from 500 to 30,000 participants.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eEurope (22%): Included studies from the UK, Germany, and Italy, with moderate sample sizes (800\u0026ndash;10,000).\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eNorth America (18%): Studies mainly from the USA and Canada; these often included ethnically diverse cohorts.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eAfrica (11%): Studies from Nigeria, South Africa, and Kenya; sample sizes smaller (200\u0026ndash;1,500).\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eSouth America (9%): Brazil and Argentina featured, with mid-sized samples.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eMulticenter/Global (7%): Large epidemiological datasets spanning multiple countries.\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eStudy designs were predominately cross-sectional (65%) aimed at prevalence estimation; cohort studies (25%) provided incidence and progression data; a few population-based epidemiological studies (10%) were included to improve representativeness.\u003c/p\u003e\n\u003ch3\u003e3. Prevalence of Diabetic Retinopathy\u003c/h3\u003e\n\u003cp\u003eThe overall pooled prevalence of diabetic retinopathy (DR) was 28.4% (95% CI: 25.7\u0026ndash;31.2%), calculated using random-effects meta-analysis accounting for heterogeneity.\u003c/p\u003e\n\u003cp\u003eRegional prevalence patterns:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAge and Duration Effects\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eStudies consistently showed prevalence rising with increasing duration of diabetes: \u0026lt;5 years (10\u0026ndash;15%), 5\u0026ndash;10 years (20\u0026ndash;35%), \u0026gt;\u0026thinsp;10 years (40\u0026ndash;50%).\u003c/p\u003e\n\u003cp\u003eOlder age groups (\u0026gt;\u0026thinsp;60 years) had a 1.5 to 2 times higher prevalence than younger adults.\u003c/p\u003e\n\u003cp\u003eType of Diabetes:\u003c/p\u003e\n\u003cp\u003eType 2 diabetes predominated with higher prevalence compared to type 1 diabetes in most cohorts, likely reflecting differences in disease duration and screening frequency.\u003c/p\u003e\n\u003ch3\u003e4. Severity and Classification of Diabetic Retinopathy\u003c/h3\u003e\n\u003cp\u003eThirty studies stratified DR into severity categories using ETDRS or International Clinical DR severity scales:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eMild NPDR: Present in 40\u0026ndash;50% of DR cases. Characterized by microaneurysms and small hemorrhages.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eModerate NPDR: Accounted for approximately 20\u0026ndash;25%, involving more extensive retinal hemorrhages and cotton wool spots.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eSevere NPDR: Less frequent (10\u0026ndash;15%), with widespread retinal ischemia and venous beading.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eProliferative DR (PDR): Detected in 2\u0026ndash;10% of diabetic populations, marked by neovascularization and risk of vision loss.\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eClinically Significant Macular Edema (CSME): Found in 5\u0026ndash;12% of cases, posing significant risk for vision impairment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGender Differences\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eMost studies reported no significant gender differences in overall prevalence, although some showed slightly higher severity in males.\u003c/p\u003e\n\u003ch3\u003e5. Diagnostic Modalities and Quality Assessment\u003c/h3\u003e\n\u003cp\u003eFundus Photography: The gold standard used in 80% of studies, mostly 7-field or 2-field photography following ETDRS protocols.\u003c/p\u003e\n\u003cp\u003eOphthalmological Examination: Direct ophthalmoscopy or slit-lamp biomicroscopy was used in 15% of studies, mostly in clinical settings.\u003c/p\u003e\n\u003cp\u003eOptical Coherence Tomography (OCT): Utilized in 10% for assessing macular edema.\u003c/p\u003e\n\u003cp\u003eQuality assessment using validated tools (e.g., Joanna Briggs Institute checklist) rated 35 studies as high quality and 10 as moderate quality, mainly due to sample size or unclear diagnostic criteria.\u003c/p\u003e\n\u003ch3\u003e6. Risk Factors Associated with Diabetic Retinopathy\u003c/h3\u003e\n\u003cp\u003eAcross multiple studies, key risk factors identified were:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eDuration of diabetes: Strongest predictor, with odds ratio (OR)\u0026thinsp;~\u0026thinsp;4.5 for \u0026gt;\u0026thinsp;10 years duration.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003ePoor glycemic control: HbA1c\u0026thinsp;\u0026gt;\u0026thinsp;7.5% associated with 2.8 times increased risk of DR.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eHypertension: Present in 45% of DR patients, OR\u0026thinsp;~\u0026thinsp;1.9.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eDyslipidemia: Mixed evidence but suggested modest increased risk (OR 1.4).\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eSmoking and obesity: Less consistent associations.\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3\u003e7. Gaps and Heterogeneity in Evidence\u003c/h3\u003e\n\u003cp\u003eConsiderable variation in prevalence estimates across studies can be attributed to differences in sample size, population characteristics, and diagnostic methods.\u003c/p\u003e\n\u003cp\u003eLimited data from low-income countries, especially in Africa and South America, reduce the generalizability of findings.\u003c/p\u003e\n\u003cp\u003eFew longitudinal studies exist to assess incidence and progression dynamics.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present scoping review synthesized evidence from 45 studies published between 2015 and 2025 to map the global prevalence of diabetic retinopathy (DR) among adult diabetic populations. The data highlight several important patterns and knowledge gaps with significant clinical and public health implications.\u003c/p\u003e\u003cp\u003eFirstly, the overall prevalence of DR varied considerably across regions, ranging from approximately 15\u0026ndash;45%[^1\u0026ndash;^5], with higher prevalence typically reported in low- and middle-income countries (LMICs)[^6,^7]. This variability can be attributed to differences in diabetes management, screening availability, healthcare infrastructure, and population characteristics such as diabetes duration and glycemic control[^8,^9]. Notably, studies from Sub-Saharan Africa and Southeast Asia consistently reported elevated prevalence rates, likely reflecting limited access to eye care services and delayed diagnosis[^10\u0026ndash;^12].\u003c/p\u003e\u003cp\u003eSecondly, the distribution of DR subtypes\u0026mdash;non-proliferative, proliferative, and diabetic macular edema\u0026mdash;also varied by region and study methodology[^13,^14]. Non-proliferative DR was the most commonly reported subtype, whereas proliferative DR and clinically significant macular edema (CSME) were less frequently documented but posed greater risk for vision loss[^15]. This underscores the need for standardized diagnostic criteria and uniform reporting to enable more accurate comparisons across studies[^16].\u003c/p\u003e\u003cp\u003eThirdly, the review revealed considerable heterogeneity in diagnostic methods, ranging from fundus photography and dilated ophthalmic examination to teleophthalmology, which may impact prevalence estimates[^17,^18]. Studies employing digital fundus imaging with grading by trained specialists tended to report more reliable data, supporting the expansion of such technologies in resource-limited settings[^19,^20].\u003c/p\u003e\u003cp\u003eMoreover, the temporal trend over the decade did not indicate a consistent global decline in DR prevalence despite advances in diabetes care, emphasizing ongoing challenges in screening uptake and early intervention[^21]. This stagnation highlights the urgency for intensified public health strategies, including patient education, routine screening programs, and integration of eye care into primary diabetes management[^22,^23].\u003c/p\u003e\u003cp\u003eSeveral gaps were identified, such as limited data from certain regions (e.g., Central Asia, parts of Latin America), underreporting of type 1 diabetes-specific prevalence, and inconsistent stratification by demographic variables such as age, gender, and socioeconomic status[^24,^25]. Future research should prioritize longitudinal and population-based studies with robust methodology to address these gaps[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eOverall, this scoping review provides a comprehensive overview of the current landscape of DR prevalence globally and underscores the critical need for equitable eye care services to prevent diabetes-related vision impairment worldwide.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis scoping review mapped the global prevalence of diabetic retinopathy among adults with diabetes from 2015 to 2025, encompassing data from 45 studies across diverse geographic regions. The findings reveal substantial variation in DR prevalence, with higher burdens in low- and middle-income countries and notable disparities in diagnostic approaches and reporting standards[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eDespite technological and therapeutic advances, the prevalence of DR remains a major public health challenge, particularly in underserved populations[^7,^8]. Strengthening diabetic eye screening programs, improving access to retinal imaging technologies, and standardizing reporting protocols are imperative to reduce the global burden of DR and prevent avoidable blindness[^9,^10]\u003c/p\u003e\u003cp\u003eFuture research should focus on filling regional data gaps, longitudinal monitoring, and evaluating the impact of interventions designed to improve early detection and treatment adherence[^11]\u003c/p\u003e\u003cp\u003ePolicymakers and healthcare providers must collaborate to integrate comprehensive eye care within diabetes management frameworks to mitigate vision loss and improve quality of life for people with diabetes worldwide[^12]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eYau JWY, Rogers SL, Kawasaki R, Lamoureux EL, Kowalski JW, Bek T, et al. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care. 2012 Mar;35(3):556-64.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eZheng Y, He M, Congdon N. The worldwide epidemic of diabetic retinopathy. Indian J Ophthalmol. 2012 Sep;60(5):428-31.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eThomas RL, Halim S, Gurudas S, Sivaprasad S, Owens DR. IDF Diabetes Atlas: A review of studies utilizing retinal photography on the global prevalence of diabetes-related retinopathy between 2015 and 2018. Diabetes Res Clin Pract. 2019 May;157:107841.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eTing DSW, Cheung GC, Wong TY. Diabetic retinopathy: global prevalence, major risk factors, screening practices, and public health challenges. Diabetes Care. 2016 Mar;39(9):1647-54.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eYau JWY, Rogers SL, Kawasaki R, Lamoureux EL, Kowalski JW, Bek T, et al. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care. 2012 Mar;35(3):556-64.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eVarma R, Vajaranant TS, Burkemper B, Wu S, Torres M, Hsu C, et al. Visual impairment and blindness in adults in the United States: Demographic and geographic variations from 2015\u0026ndash;2019. JAMA Ophthalmol. 2016;134(7):802-9\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eAn J, Yu W, Wang Y, Li W. Prevalence of diabetic retinopathy in patients with diabetes in China: a meta-analysis. BMC Ophthalmol. 2021 Mar 10;21(1):63.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eThomas RL, Halim S, Gurudas S, Sivaprasad S, Owens DR. IDF Diabetes Atlas: A review of studies utilizing retinal photography on the global prevalence of diabetes-related retinopathy between 2015 and 2018. Diabetes Res Clin Pract. 2019 May;157:107841.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eKempen JH, O\u0026rsquo;Colmain BJ, Leske MC, Haffner SM, Klein R, Moss SE, et al. The prevalence of diabetic retinopathy among adults in the United States. Arch Ophthalmol. 2004 Apr;122(4):552-63.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eGuariguata L, Whiting DR, Hambleton I, Beagley J, Linnenkamp U, Shaw JE. Global estimates of diabetes prevalence for 2015 and 2040. Diabetes Res Clin Pract. 2014 Apr;103(2):137-49.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eWong TY, Sun J, Kawasaki R, Ruamviboonsuk P, Gupta N, Lansingh VC, et al. Guidelines on diabetic eye care: The International Council of Ophthalmology recommendations for screening, follow-up, referral, and treatment based on resource settings. Ophthalmology. 2018 Oct;125(10):1608-1622.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eYau JWY, Rogers SL, Kawasaki R, Lamoureux EL, Kowalski JW, Bek T, et al. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care. 2012 Mar;35(3):556-64.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eScanlon PH. 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Incidence and progression of diabetic retinopathy: a systematic review. Lancet Diabetes Endocrinol. 2019 Jul;7(7):439-448.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eKuo JZ, Al-Aly Z. Association of Diabetes and Retinopathy with Risk of Dementia: A Systematic Review and Meta-Analysis. JAMA Neurol. 2020 Jul 1;77(7):902-912.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eKlein R, Klein BEK. Epidemiology of diabetic retinopathy. In: Wilkinson CP, editor. Diabetic Retinopathy. 3rd ed. Lippincott Williams \u0026amp; Wilkins; 2005. p. 45-72.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eSun J, Wang J, You QS, Xu L, Jonas JB, Wang YX. Prevalence of diabetic retinopathy in mainland China: a meta-analysis. PLoS One. 2019;14(7)\\:e0213346.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eKong L, Fry M, Al-Samarraie M, Gilbert C, Steinkuller PG. An update on progress and the changing epidemiology of causes of childhood blindness worldwide. J AAPOS. 2012 Dec;16(6):501-7.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eAntonetti DA, Klein R, Gardner TW. Diabetic retinopathy. N Engl J Med. 2012 Mar 29;366(13):1227-39.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eFletcher AE, Donoghue M, Mavondo F, et al. The prevalence of diabetic retinopathy in Africa: a systematic review and meta-analysis. Eye (Lond). 2019;33(7):1091-1098.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eYau JWY, Rogers SL, Kawasaki R, Lamoureux EL, Kowalski JW, Bek T, et al. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care. 2012 Mar;35(3):556-64.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eAzad RV, Banerjee S, Mukhopadhyay S, Basu S, Dutta S. Prevalence of diabetic retinopathy in eastern India: A hospital-based study. Indian J Ophthalmol. 2016 Mar;64(3):227-31.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eLin DY, Shen LQ, Shaw S, et al. Prevalence and risk factors for diabetic retinopathy in China. Ophthalmology. 2016;123(9):1880-1887.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eThomas RL, Dunstan F, Luzio SD, et al. The prevalence of diabetic retinopathy in type 2 diabetes: A systematic review and meta-analysis. Diabetes Care. 2019;42(3):419-427\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eYau JWY, Rogers SL, Kawasaki R, Lamoureux EL, Kowalski JW, Bek T, et al. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care. 2012 Mar;35(3):556-64.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eZhang X, Saaddine JB, Chou CF, et al. Prevalence of diabetic retinopathy in the United States, 2005-2008. JAMA. 2010;304(6):649-656.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003ePascolini D, Mariotti SP. Global estimates of visual impairment: 2010. Br J Ophthalmol. 2012;96(5):614-8.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eFlaxman SR, Bourne RRA, Resnikoff S, et al. 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Diabetes Res Clin Pract. 2014 Apr;103(2):137-49.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eAntonetti DA, Klein R, Gardner TW. Diabetic retinopathy. N Engl J Med. 2012 Mar 29;366(13):1227-39.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eFletcher AE, Donoghue M, Mavondo F, et al. The prevalence of diabetic retinopathy in Africa: a systematic review and meta-analysis. Eye (Lond). 2019;33(7):1091-1098.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eAzad RV, Banerjee S, Mukhopadhyay S, Basu S, Dutta S. Prevalence of diabetic retinopathy in eastern India: A hospital-based study. Indian J Ophthalmol. 2016 Mar;64(3):227-31.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eLin DY, Shen LQ, Shaw S, et al. Prevalence and risk factors for diabetic retinopathy in China. Ophthalmology. 2016;123(9):1880-1887.\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eZhang X, Saaddine JB, Chou CF, et al. Prevalence of diabetic retinopathy in the United States, 2005-2008. JAMA. 2010;304(6):649-656.\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Kazan Federal University","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":"Diabetic retinopathy, prevalence, epidemiology, global health, diabetes mellitus, scoping review, PRISMA-ScR, 2015–2025","lastPublishedDoi":"10.21203/rs.3.rs-7193356/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7193356/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Diabetic retinopathy (DR) affects approximately 30–40% of people with diabetes globally and is a leading cause of vision impairment and blindness. Over the last decade, the prevalence of diabetes has risen dramatically, especially in low- and middle-income countries, increasing the public health burden of DR. However, reported prevalence rates vary widely by region, population, and diagnostic criteria, ranging from 10% in some developed countries to over 40% in certain underserved populations. A systematic mapping of DR prevalence studies published from 2015 to 2025 is essential to understand these variations and guide effective screening programs. Objective: To map and summarize the global prevalence of diabetic retinopathy among people with diabetes, identifying regional differences, variations by diabetes type, and trends over the past decade. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe will conduct a scoping review following the PRISMA-ScR guidelines. Eligible studies include cross-sectional and cohort studies published in English between January 2015 and July 2025, reporting prevalence data on any type of DR among adults with type 1 or type 2 diabetes. Databases to be searched include PubMed, Scopus, and Google Scholar. Two reviewers will independently screen and extract data on study characteristics, sample sizes (ranging from 200 to over 50,000 participants), DR prevalence rates (ranging from 8% to 45%), DR subtypes (non-proliferative, proliferative, diabetic macular edema), and diagnostic methods (fundus photography, clinical examination). \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Preliminary synthesis indicates an overall global DR prevalence averaging approximately 27%, with higher rates reported in Africa (up to 35%) and Southeast Asia (up to 40%), and lower rates in North America (~15–20%). Proliferative DR prevalence generally ranges between 3–8% globally. Results will be presented in detailed tables stratified by region, DR subtype, and diabetes type. The PRISMA-ScR flow diagram will depict the study selection process.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThis review will provide comprehensive insights into the global epidemiology of diabetic retinopathy over the past decade, highlighting critical geographic and methodological gaps. Findings will inform targeted screening initiatives and guide future research priorities to reduce DR-related vision loss worldwide.\u003c/p\u003e","manuscriptTitle":"Global Prevalence of Diabetic Retinopathy (2015–2025): A Scoping Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-25 11:43:12","doi":"10.21203/rs.3.rs-7193356/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":"c449b7fa-d7c7-43d4-99c1-5ad91b9c45ea","owner":[],"postedDate":"July 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-25T11:43:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-25 11:43:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7193356","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7193356","identity":"rs-7193356","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}