A Study of Prevalence and Risk Factors of Digital Eye Strain among Diabetic and Non-Diabetic Patients
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Abstract
Background: The proliferation of digital devices in modern society has led to a significant increase in the prevalence of Digital Eye Strain (DES), characterized by symptoms such as eye fatigue, dryness, and headaches. This condition poses a particular risk to individuals with systemic conditions, such as diabetes mellitus, which can exacerbate ocular symptoms. Understanding the relationship between DES and diabetes is crucial for developing targeted interventions to alleviate symptoms and improve quality of life.
Objective: This study aims to assess the prevalence and risk factors of Digital Eye Strain among diabetic and non-diabetic individuals, examining the impact of digital device usage patterns, ocular surface health, and visual discomfort symptoms in both groups.
Methods: A cross-sectional study was conducted at the Eye Department of Jeddah National Hospital, involving 150 diabetic and 150 non-diabetic participants, employing purposive sampling. Participants were evaluated for DES symptoms, digital device usage habits, and clinical signs of ocular surface health, including Tear Break Up Time (TBUT), Fluorescein Stains (FS), and Tear Meniscus Height. Data analysis was performed using SPSS version 25, focusing on statistical differences between the two groups.
Results: The mean age of participants was 56 years (SD=10.3) for the diabetic group and 54 years (SD=8) for the non-diabetic group, with a balanced gender distribution across both groups. Diabetic participants demonstrated a significantly lower TBUT (median=5 seconds, IQR=2) compared to non-diabetics (median=7 seconds, IQR=1), P=0.001. DES symptoms, particularly eye fatigue and headaches, were more prevalent among diabetics, with over four hours of computer usage exacerbating symptoms (eye fatigue: 57%, P=0.001; headache: 32.8%, P=0.029). Environmental and behavioral factors, including improper illumination and infrequent breaks, were significantly associated with increased DES symptoms.
Conclusion: Digital Eye Strain is more prevalent and severe among diabetic individuals, with significant implications for ocular and general well-being. The findings underscore the need for targeted digital health interventions and ergonomic practices to mitigate DES symptoms, especially among those with diabetes.
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References
Ahmad AA, Alshehri BF, Almalki AM, Albaradi AM, Almalki MS, Alattas KY. Eyeing computer vision syndrome: Awareness, knowledge, and its impact on sleep quality among health sciences students during the COVID-19 pandemic in Taif, Kingdom of Saudi Arabia. International Journal of Medicine in Developing Countries. 2021;5(9):1647-.
Ahmed MS, Ullah AY, Barman N, Ratan ZA, Mostafa S, Khaleque A, et al. Risk factors associated with elevated intraocular pressure: a population-based study in a rural community of Bangladesh. BMJ Open Ophthalmology. 2023;8(1):e001386.
Althiabi SM, Alnafeesah AA, Al-boqami BAA-h, Alkhulifi BH, Albadi SM, Alfowzan RF. The association between digital eye strain symptoms, especially dry eye and online study during COVID-19 pandemic among Qassim University medical students. International Journal of Medicine in Developing Countries. 2022;6(9):1157-.
Bashorun SD, Balogun BG, Ibidapo O, Bashorun AO. Prevalence of dry eye disease in type 2 diabetic and non-diabetics: A cross-sectional hospital-based study. Journal of West African College of Surgeons. 2024;14(2):180-7.
Bu Y, Shih KC, Tong L. The ocular surface and diabetes, the other 21st Century epidemic. Experimental Eye Research. 2022;220:109099.
Chandler RK, Villani J, Clarke T, McCance-Katz EF, Volkow ND. Addressing opioid overdose deaths: The vision for the HEALing communities study. Drug and Alcohol Dependence. 2020;217:108329.
Chauke MM. Possible correlations between HbA1c and selected modifiable risk factors for type 2 diabetes mellitus in a non-diabetic population: University of Johannesburg; 2023.
del Mar Seguí M, Cabrero-García J, Crespo A, Verdú J, Ronda E. A reliable and valid questionnaire was developed to measure computer vision syndrome at the workplace. Journal of clinical epidemiology. 2015;68(6):662-73.
Khoja L, Atenafu E, Suciu S, Leyvraz S, Sato T, Marshall E, et al. Meta-analysis in metastatic uveal melanoma to determine progression free and overall survival benchmarks: an international rare cancers initiative (IRCI) ocular melanoma study. Annals of Oncology. 2019;30(8):1370-80.
Kropp M, Golubnitschaja O, Mazurakova A, Koklesova L, Sargheini N, Vo T-TKS, et al. Diabetic retinopathy as the leading cause of blindness and early predictor of cascading complications—risks and mitigation. Epma Journal. 2023;14(1):21-42.
Lee KY, Buldum G, Mantalaris A, Bismarck A. More than meets the eye in bacterial cellulose: biosynthesis, bioprocessing, and applications in advanced fiber composites. Macromolecular bioscience. 2014;14(1):10-32.
Loukovaara S, Korhonen A, Niskanen L, Haukka J. Development of diabetic macular oedema shows associations with systemic medication–An epidemiological study. Acta Ophthalmologica. 2023.
Lu Y, Wang W, Liu J, Xie M, Liu Q, Li S. Vascular complications of diabetes: A narrative review. Medicine. 2023;102(40):e35285.
Meem JT. Musculoskeletal characteristics among diabetic and non-diabetic patients attended at CRP: Bangladesh Health Professions Institute, Faculty of Medicine, the University …; 2022.
Morya AK, Ramesh PV, Kaur K, Gurnani B, Heda A, Bhatia K, et al. Diabetes more than retinopathy, it’s effect on the anterior segment of eye. World Journal of Clinical Cases. 2023;11(16):3736.
Nalini M, Khoshnia M, Kamangar F, Sharafkhah M, Poustchi H, Pourshams A, et al. Joint effect of diabetes and opiate use on all-cause and cause-specific mortality: the Golestan cohort study. International journal of epidemiology. 2021;50(1):314-24.
Zewdu D, Gedamu H, Beyene Y, Tadesse M, Tamirat M, Muluken S. Sleep quality and associated factors among type 2 Dm patients and non-Dm individuals in Bahir Dar governmental hospitals: comparative cross-sectional study. Sleep Science and Practice. 2022;6(1):10.
Reeves ND, Orlando G, Brown SJ. Sensory-motor mechanisms increasing falls risk in diabetic peripheral neuropathy. Medicina. 2021;57(5):457.
Rosenfield M. Computer vision syndrome: a review of ocular causes and potential treatments. Ophthalmic and Physiological Optics. 2011;31(5):502-15.
Smith JN, Walker HM, Thompson H, Collinson JM, Vargesson N, Erskine L. Lens-regulated retinoic acid signalling controls expansion of the developing eye. Development. 2018;145(19):dev167171.
Upadhayay P, Bansal K, Goyal A. Epidemiology, Risk Factors, Diagnosis and Treatment of Mucormycosis (Black Fungus): A Review. Current Pharmaceutical Biotechnology. 2023;24(13):1645-56.
Schaumberg DA, Sullivan DA, Buring JE, Dana MR. Prevalence of dry eye syndrome among US women. American journal of ophthalmology. 2003;136(2):318-26.
Shah M, Saboor A. Computer vision syndrome: Prevalence and its associated risk factors among computer-using bank workers in Pakistan. 2022.