Prevalence and Predictive Factors of Diabetic Retinopathy in Patients with Type 2 Diabetes Mellitus in U Thong District, Suphanburi Province
DOI:
https://doi.org/10.64767/trcn.2026.281535Keywords:
diabetic retinopathy, type 2 diabetes mellitus, prevalence, predictiveAbstract
Background: Diabetic retinopathy (DR) is a major complication of type 2 diabetes mellitus (T2DM) and an important cause of permanent visual impairment and blindness. Identifying the prevalence and predictive factors of DR is essential in developing effective screening and risk-stratification strategies among patients with T2DM.
Objective: To determine the prevalence and predictive factors of diabetic retinopathy among patients with type 2 diabetes mellitus in U Thong District, Suphan Buri Province, Thailand.
Methods: A retrospective study was conducted among 1,140 patients with T2DM who received DR screening at U Thong Hospital between June and December 2025. Data were collected from medical records using a structured data-recording form covering personal and clinical characteristics. The instrument was reviewed for content validity by three experts. Data were analyzed using descriptive statistics and multivariable logistic regression analysis.
Results: The prevalence of diabetic retinopathy was 24.7% (95% CI: 22.3-27.3), with mild non-proliferative diabetic retinopathy being the most common severity level (18.9%). The multivariable logistic regression model demonstrated good model fit (Hosmer–Lemeshow test: χ² = 5.72, df = 8, p = 0.68) and correctly classified 77.90% of cases. Smoking was the strongest predictive factor for diabetic retinopathy (adjusted OR = 3.53, p < 0.001), followed by duration of diabetes (adjusted OR = 1.90, p < 0.001), visual acuity (adjusted OR = 1.80, p < 0.001), systolic blood pressure (adjusted OR = 1.72, p = 0.001), and glycated hemoglobin (HbA1c) level (adjusted OR = 1.60, p < 0.001). The predictors jointly explained 27% of the variance in diabetic retinopathy (Nagelkerke R² = 0.27).
Conclusion: The prevalence of diabetic retinopathy among patients with T2DM in U Thong District was substantial and warrants continued surveillance. Smoking, longer duration of diabetes, visual acuity, systolic blood pressure, and HbA1c level were important predictive factors. Healthcare teams should strengthen smoking cessation interventions, glycemic control, and regular retinal screening at least annually. These predictive factors may also be incorporated into risk-based screening systems to facilitate early identification and management of patients at increased risk of diabetic retinopathy.
Downloads
References
Mohammed RM, Fathi SA. Global prevalence of diabetic retinopathy over the last decade (2015–2025): a scoping review. medRxiv [preprint]. 2025 [cited 2025 May 22]. DOI: https://doi.org/10.1101/2025.07.24.25332019
Marathe PH, Gao HX, Close KL. American Diabetes Association standards of medical care in diabetes 2017. J Diabetes Res 2017;9(4):320-24. DOI: https://doi.org/10.1111/1753-0407.12562
Teo ZL, Tham YC, Yu M, Chee ML, Rim TH, Cheung N, et al. Global prevalence of diabetic retinopathy and projection of burden through 2045: systematic review and meta-analysis. Ophthalmology 2021;128(11):1580-91.
Health Data Center. Report on diabetic patients with eye complications [Internet]. 2023 [cited 2026 Mar 28]. Available from: https://hdc.moph.go.th/center/public/main
Boonsaen T, Choksakunwong S, Lertwattanarak R. Prevalence of and factors associated with diabetic retinopathy in patients with diabetes mellitus at Siriraj Hospital - Thailand's largest national tertiary referral center. Diabetes Metab Syndr Obes 2021;14:4945-57. DOI: https://doi.org/10.2147/DMSO.S346719
Euswas N, Phonnopparat N, Morasert K, Thakhampaeng P, Kaewsanit A, Mungthin M, et al. National trends in the prevalence of diabetic retinopathy among Thai patients with type 2 diabetes and its associated factors from 2014 to 2018. PLoS One 2021;16(1):e0245801. DOI: https://doi.org/10.1371/journal.pone.0245801
Yau JW, Rogers SL, Kawasaki R, Lamoureux EL, Kowalski JW, Bek T, et al.; Meta-Analysis for Diabetes Study Group. Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care 2012;35(3):556-64. DOI: https://doi.org/10.2337/dc11-1909
Jitsopit K. Prevalence of diabetic retinopathy and relation of Hemoglobin A1c level with occurrence of diabetic retinopathy in diabetic patients at Sanpatong hospital, Chiangmai province: none. Journal of Disease Prevention and Control : DPC2 Phitsanulok 2023;10(2):15-25. (in Thai)
Zhang D, Jia Z, Geng A, Zhang Z, Pan X, Zhong X. Association analysis and exploratory mediation study of the stress-induced hyperglycaemia ratio and glycaemic ratio indices with diabetic retinopathy in patients with type 2 diabetes. Front Nutr 2026;13:1798444. DOI: https://doi.org/10.3389/fnut.2026.1798444
Chaisongkram W. Prevalence and risk factors of diabetic retinopathy in patients with type 2 diabetes. J Health Sci Thai 2016;25(1):37-45. (in Thai)
Abuhay HW, Tesfie TK, Alemayehu MA, Agimas MC, Yismaw GA, Alemu GG, et al. Prevalence of diabetic retinopathy and its associated factors among adults in East African countries: a systematic review and meta-analysis. PLoS One. 2025;20(1):e0316160. DOI: https://doi.org/10.1371/journal.pone.0316160
Bumrungsena K. Prevalence and risk score to predict diabetic retinopathy in diabetic patients, Singhanakorn Hospital, Songkhla Province, Thailand. Wkly Epidemiological Surveillance Report, Thailand 2018;49(38):593-8. (in Thai).
Trott M, Driscoll R, Pardhan S. Associations between diabetic retinopathy and modifiable risk factors: an umbrella review of meta-analyses. Diabet Med 2022;39(6):e14796. DOI: https://doi.org/10.1111/dme.14796
Li Z, Yuan Y, Qi Q, Wang Q, Feng L. Relationship between dyslipidemia and diabetic retinopathy in patients with type 2 diabetes mellitus: a systematic review and meta-analysis. Syst Rev 2023;12(1):148. DOI: https://doi.org/10.1186/s13643-023-02321-2
Wangrussameeduen P. Prevalence and factors associated with diabetic retinopathy at Namsom District, Udonthani Province [Internet]. 2022 [cited 2026 Jul 5]. Available from: https://healthregion10.moph.go.th/wp-content/uploads/2024/01 (in Thai)
Zhong JB, Yao YF, Zeng GQ, Zhang Y, Ye BK, Dou XY, et al. A closer association between blood urea nitrogen and the probability of diabetic retinopathy in patients with shorter type 2 diabetes duration. Sci Rep. 2023;13(1):9881. DOI: https://doi.org/10.1038/s41598-023-35653-z
Teo ZL, Tham YC, Yu M, Chee ML, Rim TH, Cheung N, et al. Global prevalence of diabetic retinopathy and projection of burden through 2045: systematic review and meta-analysis. Ophthalmology. 2021;128(11):1580-91. DOI: https://doi.org/10.1016/j.ophtha.2021.04.027
Dursun E, Inanc M, Kocer AM, Dursun AGA, Tekin K. Long-term effects of smoking on retinal and choriocapillaris perfusion: an optical coherence tomography angiography study. J Vitreoretin Dis 2026;10(2):223-9. DOI: https://doi.org/10.1177/24741264251383398
Cho Y, Park HS, Seo DH, Ahn SH, Hong S, Suh YJ, et al. The association of smoking status with diabetic microvascular complications in Korean patients with type 2 diabetes. Yonsei Med J 2024 Aug;65(8):427-33. DOI: https://doi.org/10.3349/ymj.2023.0355
Kropp M, Golubnitschaja O, Mazurakova A, Koklesova L, Sargheini N, Vo TKS, et al. Diabetic retinopathy as the leading cause of blindness and early predictor of cascading complications-risks and mitigation. EPMA J. 2023;14(1):21-42. DOI: https://doi.org/10.1007/s13167-023-00314-8
Vision Loss Expert Group of the Global Burden of Disease Study; GBD 2019 Blindness and Vision Impairment Collaborators. Global estimates on the number of people blind or visually impaired by diabetic retinopathy: a meta-analysis from 2000 to 2020. Eye (Lond). 2024;38(11):2047-57.
Liang Y, Zhang X, Mei W, Li Y, Du Z, Wang Y, et al. Predicting vision-threatening diabetic retinopathy in patients with type 2 diabetes mellitus: systematic review, meta-analysis, and prospective validation study. J Glob Health. 2024;14:04192. DOI: https://doi.org/10.7189/jogh.14.04192
Yumnamcha T, Guerra M, Singh LP, Ibrahim AS. Metabolic dysregulation and neurovascular dysfunction in diabetic retinopathy. Antioxidants (Basel). 2020;9(12):1244. DOI: https://doi.org/10.3390/antiox9121244
Centers for Disease Control and Prevention. Principles of epidemiology in public health practice: an introduction to applied epidemiology and biostatistics. 3rd ed. Atlanta (GA): Centers for Disease Control and Prevention; 2012. https://stacks.cdc.gov/view/cdc/13178?utm_source=chatgpt.com
Faul F, Erdfelder E, Buchner A, Lang AG. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods 2009;41(4):1149-60. DOI: https://doi.org/10.3758/BRM.41.4.1149
World Health Organization Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004;363(9403):157-63. DOI: https://doi.org/10.1016/S0140-6736(03)15268-3
American Diabetes Association Professional Practice Committee for Diabetes. 2. Diagnosis and classification of diabetes: standards of care in diabetes-2026. Diabetes Care 2026;49(Suppl 1):S27-S49. DOI: https://doi.org/10.2337/dc26-S002
Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of the third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). JAMA 2001;285(19):2486-97. DOI: https://doi.org/10.1001/jama.285.19.2486
James PA, Oparil S, Carter BL, et al. 2014 evidence-based guideline for the management of high blood pressure in adults: report from the panel members appointed to the eighth Joint National Committee (JNC 8). JAMA 2014;311(5):507–20. DOI: https://doi.org/10.1001/jama.2013.284427
Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2024 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int 2024;105(4S):S117-S314. DOI: https://doi.org/10.1016/j.kint.2023.10.018
World Health Organization. International statistical classification of diseases and related health problems, 11th revision (ICD-11). Geneva: WHO; 2018.
Polit DF, Beck CT, Owen SV. Is the CVI an acceptable indicator of content validity? Appraisal and recommendations. Res Nurs Health 2007;30(4):459-67. DOI: https://doi.org/10.1002/nur.20199
Yin L, Zhang D, Ren Q, Su X, Sun Z. Prevalence and risk factors of diabetic retinopathy in diabetic patients: a community based cross-sectional study. Medicine (Baltimore). 2020;99(9):e19236. DOI: https://doi.org/10.1097/MD.0000000000019236
Sheemar A, Bellala K, Sharma SV, Sharma S, Kaur I, Rani P, et al. Metabolic memory and diabetic retinopathy: legacy of glycemia and possible steps into future. Indian J Ophthalmol 2024;72(6):796-808. DOI: https://doi.org/10.4103/IJO.IJO_2563_23
Kristensen JK, Sandbæk A, Bro F, Lassen JF, Lauritzen T. Routine screening for diabetic eye complications in a population based cohort of 4438 persons with type 2 diabetes in a Danish county. Dan Med Bull 2004;51(1):104-7.
Msanga D, Reist K, Kayange N, Bakalemwa R, Kidenya B, Hau D, et al. Diabetic microvascular complications among children and adolescents in northwestern Tanzania: a cross-sectional study. Ann Glob Health 2020;86(1):43. DOI: https://doi.org/10.5334/aogh.2669
UK Prospective Diabetes Study (UKPDS) Group. Tight blood pressure control and risk of macrovascular and microvascular complications in type 2 diabetes. BMJ 1998;317(7160):703-13. DOI: https://doi.org/10.1136/bmj.317.7160.703
Kaewput W, Thongprayoon C, Rangsin R, Ruangkanchanasetr P, Mao MA, Cheungpasitporn W. Associations of renal function with diabetic retinopathy and visual impairment in type 2 diabetes: a multicenter nationwide cross-sectional study. World J Nephrol 2019;8(2):33-43. DOI: https://doi.org/10.5527/wjn.v8.i2.33
American Diabetes Association Professional Practice Committee. 2. Diagnosis and classification of diabetes: Standards of Care in Diabetes—2025. Diabetes Care 2025;48(Suppl 1):S27-S49. DOI: https://doi.org/10.2337/dc25-S002
Barter PJ, Nicholls S, Rye KA, Anantharamaiah GM, Navab M, Fogelman AM. Antiinflammatory properties of HDL. Circ Res 2004;95(8):764-72. DOI: https://doi.org/10.1161/01.RES.0000146094.59640.13
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Srisavarindhira Thai Red Cross Institute of Nursing
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
เนื้อหาบทความหรือข้อคิดเห็นต่างๆ ในวารสารพยาบาลสภากาชาดไทยนี้ เป็นความคิดเห็นของผู้เขียนบทความ ไม่ใช่ความเห็นของกองบรรณาธิการ หรือสถาบันการพยาบาลศรีสวรินทิรา สภากาชาดไทย
