Title: Prevalence of Dry Eye Disease in Computer Users in Kashmir

Authors: Dr Sabia Salam, Dr Syed Sadaf Altaf, Prof. Sabia Rashid

 DOI: https://dx.doi.org/10.18535/jmscr/v9i9.21

Abstract

Background: Dry eye disease is a chronic ocular pathology and a major global health problem that manifests with a plethora of symptoms such as burning, photophobia, tearing, and grittiness. Prevalence of dry eye disease ranges from 5% to 35% and is greatly influenced by geographic location and climatic conditions. Computer vision syndrome (CVS) is a leading occupational hazard of 21 century and its symptoms affect nearly about 70% of all computer users. Nearly about 60 million people suffer from CVS with 1 million new cases occurring each year.

Objective: To assess the prevalence of dry eye disease in computer users in our population and to study the relationship between computer usage per day and dry eye disease.

Methods: Computer users aged between 20-40 years of both genders were included in the study. Subjective assessment for dry eye disease was performed using Ocular surface disease index (OSDI) questionnaire. All the study subjects underwent a detailed routine ophthalmologic examination including, visual acuity, anterior segment and fundus examination with a slit lamp biomicroscope. After routine ophthalmologic examination objective tests, Schirmer’s test and TBUT were performed on the subjects.

Results: The patients were in the age group of 20-40 years with mean age of 24 years with 276 (58.7%) males and 194 (41.3%) females. Presence of redness, watering of eyes, headache, eye fatigue, pain in and around the eyes, blurred vision was found to be present in 25.5%, 54%, 44.8%, 40.2% and 17.6% respectively. Patients were grouped in groups A, B, C depending on working hours of computer use per day. Group A 2-4 hrs/day, Group B 4-6 hrs/day, Group C 6-8 hrs/day. The objective tests (TBUT and Schirmer’s test) were undertaken only in patients with dry eye disease based on OSDI questionnaire. There were 72.1%, 8.3%, 12.1% and 7.4% persons having OSDI score of 0-12, 13-22, 23-32 and >33 respectively. Mean value of OSDI score was 15.3+10.08. Prevalence of dry eye disease was found to be 27.9%. Prevalence of dry eye disease was found to be 23.2%, 32.6%, 38.5% and 47.1% in the age group of 20-24 years, 25-29 years, 30-34 years and > 35 years respectively. Prevalence of dry eye disease in computer users was found to be 28.3% and 27.3% in males and females respectively. Prevalence of dry eye disease was found to be 11.9%, 26.3% and 48.1% in groups A, B and C respectively.

Conclusion: Prevalence of dry eye disease was found to increase with increase in duration of computer use per day. OSDI questionnaire is the best validated questionnaire for diagnosis and grading of DED on basis of symptoms of DED.TBUT measurement is an easy and fast method used to assess the stability of tear film.

Keywords: Dry eye disease, photophobia, Computer vision syndrome, Schirmer’s test, TBUT.

References

  1. Miljanovic B, Dana R, Sullivian DA, Schaumberg DA. Impact of dry eye syndrome on vision related quality of life. Am J Ophthalmol 2007; 143: 409-15.
  2. Wu H, Wang Y, Dong N, Yang F, Lin Z, Shang X, et al. Meibomian gland dysfunction determines the severity of the dry eye conditions in visual display terminal workers. PLoS One 2014; 9: e 105575.
  3. Schiffman RM, Christian MD, Jacobsen Greis BL. Reliability abd validity of the ocular disease index. Arch Ophthalmol 2000; 118: 615-21.
  4. Nichols KK, Mitchell GL, Zadnik K. The repeatability of clinical measurements of dry eye. Cornea 2004; 23: 272-85.
  5. The epidemiology of dry eye disease: Report of the epidemiology Subcommittee of the International Dry Eye Workshop (2007). Ocul Surf 2007; 5: 93-107.
  6. Charpe NA and Kaushik V. Computer vision syndrome (CVS): recognition and control in software professionals. Journal of Human Ecology, 2009; 28(1): 67-69.’
  7. Wimalasundera S. Computer vision syndrome. Galle Medical Journal, 2006; 11(1): 25-29.
  8. Charpe NA and Kaushik V. Computer vision syndrome (CVS): recognition and control in software professionals. J Hum Ecol. 2009; 28(1): 67-69.
  9. Trusiewicz D, Niesluchowska M, Makszewska- Chetnik Z. Eye – strain symptoms after work with a computer screen. Kiln Oczna 1995; 97: 343-45.
  10. Begley CG, Chalmers RL, Abetz L, Venkatramank K, Caffery BA, et al. The relationship between habitual patient reported symptoms and clinical signs among  patients with dry eye of varying severity. Invest Ophthalmol Vis Sci 2003; 44: 4753-61.
  11. Fenety A, walker JM. Short – term effects of workstation exercise on musculoskeletal discomfort and postural changes in seated video display unit workers. PhysTher 2002; 82: 578-89.
  12. Thomson WD. Eye problems and visual display terminals, the facts and the fallacies. OphthalPhysiol opt 1998; 18: 111-19.
  13. Tadesse S, Kelaye T, and Assefa Y. Utilization of personal protective equipment and associated factors among textile factory workers at Hawassa Town, Southern Ethiopia. Journal of Occupational Medicine and Toxicology. 2016; 11(1): 1-6.
  14. Lin PY, Tsai SY, Cheng CY, Hsu WM, et al. Prevalence of dry eye among an elderly Chinese population in Taiwan: The Shihpai eye study. Ophthalmollogy 2003; 110: 1096-101.
  15. Gupta N, Prasad I, Jain R, D’Souza P. Estimating the prevalence of dry eye among Indian patients attending a tertiary Ophthalmology clinic. Ann Trop Med Parasitol 2010; 104: 247-55.
  16. McCarty CA, Bansa IAK, Livingston PM, Stanislavsky YL, Taylor HR. The epidemiology of dry eye in Melbourne, Australia. Ophthalmology 1998; 105: 1114-19.
  17. Uchino M, Yokio N, Uchino Y, Komuro A, et al. Prevalence of dry eye disease and its risk factors in visual display terminal users: the Osaka study. Am J Ophthalmol 2013; 156: 759-66.
  18. Pflugfelder SC, Tseng SC, Sanabria O, Kell H, Garcia CG, Felix C, Feuer W, Reis BL. Evaluation of subjective assessments and objective diagnostic tests for diagnosing tear- film disorders known to cause ocular irritation. Cornea.  1998; 17: 38-56.
  19. Perry HD, Donnenfield ED. Dry eye diagnosis and management in 2004. CurrOpinOphthalmol. 2004; 15: 299-304.
  20. Patil SD, Trivedi HR, Parekh NV, Jethva JJ. Evaluation of dry eye in computer users. Int J C ommunity Med Public Health. 2016; 3: 3403-7.
  21. Tsubota K. Short Tear Film Breakup Time-Type Dry Eye. Investigative Ophthalmology and Visual Science. 2018; 59 (14): DES64-DES70.
  22. Reshma BKS, Iram S. Prevalence of dry eye in computer users. Int  J Ocul Oncol Oculoplasty 2020; 6(2): 95-98.
  23. Raj A, Dhasmana R, Bahadur H. Evaluation of impact of computer usage on various tear parameters in normal healthy tertiary hospital based population in Uttarakhand, India. Int J Community Med Public Health. 2016; 43 (11): 3130-3134.
  24. Pulla A, Asma, Samyuktha N, Kasubagula S, Kataih A, Banoth D, et al. A cross sectional study to assess the prevalence and associated factors of computer vision syndrome among engineering students of Hyderabad, Telangana. Int J Community Med Public Health 2019; 6(1): 308-13.
  25. Ranasinghe P, Wathurapatha WS, Perera YS, Lamabadusuriya DA, Kulatunga S, Jayawardana N, Katulanda P. Computer vision syndrome among computer office workers in a developing country: an evaluation of prevalence and risk factors. BMC Res Notes. 2016;9:150.
  26. Damle V, Agarwal PC, Gupta SK. Study of prevalence of dry eye disease in bank employees. IP International Journal of Ocular Oncology and Oculoplasty, 2018; 4(2): 73-77.
  27. Titiyal JS, Falera RC, Kaur M, Sharma V, Sharma N. Prevalence and risk factors of dry eye disease in North India: Ocular surface disease index- based cross sectional hospital study. Indian J Ophthalmol 2018; 66: 207- 11.
  28. Yazici A, Sari ES, Sahin G, Kilic A, Cakmak H, Ayar O, Ermis SS. Change in tear film characteristics in visual display terminal users. Eur J Ophthalmol. 2015; 25(2):85-89.
  29. Bhargava R, Kumar P, Kaur A, Kumar M, Mishra A. The Diagnostic Value and Accuracy of Conjunctival Impression Cytology. Dry Eye Symptomatology, and Routine Tear Function Tests in Computer Users J Lab Physicians. 2014;6(2):102-8.
  30. Prabhasawat P, Pinitpuwadol W, Angsriprasert D, Chonpimai P, Saiman M. Tear film change and ocular symptoms after reading printed book and electronic book: a crossover study. Jpn J Ophthalmol. 2019; 63(2): 137-144.

Corresponding Author

Syed Sadaf Altaf

Senior Resident GMC Srinagar, India