Incidence, demographics, types and risk factors of dry eye disease in India: Electronic medical records driven big data analytics report I

• Published in: The ocular surface Vol. 17; no. 2; pp. 250 - 256
• Main Authors: Donthineni, Pragnya Rao, Kammari, Priyanka, Shanbhag, Swapna S., Singh, Vivek, Das, Anthony Vipin, Basu, Sayan
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.04.2019
• Subjects: Adult; Aged; Big Data; Child; Demography; Dry eye disease; Dry Eye Syndromes; Electronic Health Records; Electronic medical records; Epidemiology; Female; Humans; Incidence; India; Male; Risk Factors; India; Big data; Dry eye disease; Epidemiology; Electronic medical records
• ISSN: 1542-0124; 1937-5913; 1937-5913
• DOI: 10.1016/j.jtos.2019.02.007

To describe the incidence, demographics, types and risk-factors of dry eye disease (DED) in patients presenting to a multi-tier ophthalmology hospital network in India. This was an observational hospital-based study of 1,458,830 new patients presenting between 2010 and 2018. Patients with recent onset of both symptoms and signs, as defined by the tear film and ocular surface society dry eye work shop (TFOS DEWS) II guidelines, were considered as DED subjects. The data was prospectively collected using an electronic medical record system. Multiple logistic regression with odds ratio (OR) estimation was performed to identify the high risk-factors of DED. Overall, 21,290 (1.46%) patients were diagnosed with recent-onset DED. The incidence of DED was 2688 and 16,482 per million population in children and adults, respectively (p < 0.0001). While incidence was significantly greater in males in 3rd, 4th, 9th and 10th decade (p < 0.03), it was greater in females in 5th and 6th decade (p < 0.0001) of life. Classified etiologically 35.5%, 20.6% and 39.9% of patients had evaporative, aqueous deficient and mixed type of DED, respectively. Age (OR 3.7–13.5), urban residence (OR 1.6), professional work (OR 1.5); homemaking (OR 1.42), retirement/unemployment (OR 1.24) and socio-economic affluence (OR 1.6–3.2) were identified as high risk-factors for developing DED. The study results indicate that age, sex, residence, occupation, and socio-economic status have significant impact on development of DED. Since India is an emerging economy with a growing middle-class, increasing urban-migration and large aging population, the country is on the brink of a DED epidemic.