Characteristics and Risk Factors Associated with Diagnosed and Undiagnosed Symptomatic Dry Eye Using a Smartphone Application

Takenori Inomata, Masao Iwagami, Masahiro Nakamura, Tina Shiang, Yusuke Yoshimura, Keiichi Fujimoto, Yuichi Okumura, Atsuko Eguchi, Nanami Iwata, Maria Miura, Satoshi Hori, Yoshimune Hiratsuka, Miki Uchino, Kazuo Tsubota, Reza Dana, Akira Murakami

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Abstract

Importance: The incidence of dry eye disease has increased; the potential for crowdsource data to help identify undiagnosed dry eye in symptomatic individuals remains unknown. Objective: To assess the characteristics and risk factors associated with diagnosed and undiagnosed symptomatic dry eye using the smartphone app DryEyeRhythm. Design, Setting, and Participants: A cross-sectional study using crowdsourced data was conducted including individuals in Japan who downloaded DryEyeRhythm and completed the entire questionnaire; duplicate users were excluded. DryEyeRhythm was released on November 2, 2016; the study was conducted from November 2, 2016, to January 12, 2018. Exposures: DryEyeRhythm data were collected on demographics, medical history, lifestyle, subjective symptoms, and disease-specific symptoms, using the Ocular Surface Disease Index (100-point scale; scores 0-12 indicate normal, healthy eyes; 13-22, mild dry eye; 23-32, moderate dry eye; 33-100, severe dry eye symptoms), and the Zung Self-Rating Depression Scale (total of 20 items, total score ranging from 20-80, with ≥40 highly suggestive of depression). Main Outcomes and Measures: Multivariate-adjusted logistic regression analysis was used to identify risk factors for symptomatic dry eye and to identify risk factors for undiagnosed symptomatic dry eye. Results: A total of 21394 records were identified in our database; 4454 users, included 899 participants (27.3%) with diagnosed and 2395 participants (72.7%) with undiagnosed symptomatic dry eye, completed all questionnaires and their data were analyzed. A total of 2972 participants (66.7%) were women; mean (SD) age was 27.9 (12.6) years. The identified risk factors for symptomatic vs no symptomatic dry eye included younger age (odds ratio [OR], 0.99; 95% CI, 0.987-0.999, P =.02), female sex (OR, 1.99; 95% CI, 1.61-2.46; P <.001), pollinosis (termed hay fever on the questionnaire) (OR, 1.35; 95% CI, 1.18-1.55; P <.001), depression (OR, 1.78; 95% CI, 1.18-2.69; P =.006), mental illnesses other than depression or schizophrenia (OR, 1.87; 95% CI, 1.24-2.82; P =.003), current contact lens use (OR, 1.27; 95% CI, 1.09-1.48; P =.002), extended screen exposure (OR, 1.55; 95% CI, 1.25-1.91; P <.001), and smoking (OR, 1.65; 95% CI, 1.37-1.98; P <.001). The risk factors for undiagnosed vs diagnosed symptomatic dry eye included younger age (OR, 0.96; 95% CI, 0.95-0.97; P <.001), male sex (OR, 0.55; 95% CI, 0.42-0.72; P <.001), as well as absence of collagen disease (OR, 95% CI, 0.23; 0.09-0.60; P =.003), mental illnesses other than depression or schizophrenia (OR, 0.50; 95% CI, 0.36-0.69; P <.001), ophthalmic surgery other than cataract surgery and laser-assisted in situ keratomileusis (OR, 0.41; 95% CI, 0.27-0.64; P <.001), and current (OR, 0.64; 95% CI, 0.54-0.77; P <.001) or past (OR, 0.45; 95% CI, 0.34-0.58; P <.001) contact lens use. Conclusions and Relevance: This study's findings suggest that crowdsourced research identified individuals with diagnosed and undiagnosed symptomatic dry eye and the associated risk factors. These findings could play a role in earlier prevention or more effective interventions for dry eye disease..

Original languageEnglish
Pages (from-to)58-68
Number of pages11
JournalJAMA Ophthalmology
Volume138
Issue number1
DOIs
Publication statusPublished - 2020 Jan

ASJC Scopus subject areas

  • Ophthalmology

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    Inomata, T., Iwagami, M., Nakamura, M., Shiang, T., Yoshimura, Y., Fujimoto, K., Okumura, Y., Eguchi, A., Iwata, N., Miura, M., Hori, S., Hiratsuka, Y., Uchino, M., Tsubota, K., Dana, R., & Murakami, A. (2020). Characteristics and Risk Factors Associated with Diagnosed and Undiagnosed Symptomatic Dry Eye Using a Smartphone Application. JAMA Ophthalmology, 138(1), 58-68. https://doi.org/10.1001/jamaophthalmol.2019.4815