Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2016 Oct 28;16(1):188.
doi: 10.1186/s12886-016-0364-4.

Smartphone use is a risk factor for pediatric dry eye disease according to region and age: a case control study

Affiliations

Smartphone use is a risk factor for pediatric dry eye disease according to region and age: a case control study

Jun Hyung Moon et al. BMC Ophthalmol. .

Abstract

Background: In 2014, the overall rate of smartphone use in Korea was 83 and 89.8 % in children and adolescents. The rate of smartphone use differs according to region (urban vs. rural) and age (younger grade vs. older grade). We investigated risk and protective factors associated with pediatric dry eye disease (DED) in relation to smartphone use rate according to region and age.

Methods: We enrolled 916 children and performed an ocular exam that included slit lamp exam and tear break-up time. A questionnaire administered to children and their families consisted of video display terminal (VDT) use, outdoor activity, learning, and modified ocular surface disease index (OSDI) score. DED was defined based on the International Dry Eye Workshop guidelines (Objective signs: punctate epithelial erosion or short tear break-up time; subjective symptoms: modified OSDI score) We performed statistical analysis of risk factors and protective factors in children divided into groups as follows: DED vs. control, urban vs. rural, younger grade (1st to 3rd) vs. older grade (4th to 6th).

Results: A total of 6.6 % of children were included in the DED group, and 8.3 % of children in the urban group were diagnosed with DED compared to 2.8 % in the rural group (P = 0.03). The rate of smartphone use was 61.3 % in the urban group and 51.0 % in the rural group (P = 0.04). In total, 9.1 % of children in the older-grade group were diagnosed with DED compared to 4 % in the younger-grade group (P = 0.03). The rate of smartphone use was 65.1 % in older-grade children and 50.9 % in younger-grade children (P < 0.001). The mean daily duration of smartphone use was longer in the DED group than controls (logistic regression analysis, P < 0.001, OR = 13.07), and the mean daily duration of outdoor activities was shorter in the DED group than controls (logistic regression analysis, P < 0.01, OR = 0.33). After cessation of smartphone use for 4 weeks in the DED group, both subjective symptoms and objective signs had improved.

Conclusions: Smartphone use in children was strongly associated with pediatric DED; however, outdoor activity appeared to be protective against pediatric DED. Older-grade students in urban environments had DED risk factors (long duration of smartphone use), and a short duration of outdoor activity time. Therefore, close observation and caution are needed when older children in urban areas use smartphones.

Keywords: Dry eye disease; Outdoor activity; Pediatrics; Smartphone; Video display terminal.

PubMed Disclaimer

References

    1. McCarty CA, Bansal AK, Livingston PM, Stanislavsky YL, Taylor HR. The epidemiology of dry eye in Melbourne, Australia. Ophthalmology. 1998;105:1114-9. - PubMed
    1. Ang CK, Mohidin N, Chung KM. Effects of wink glass on blink rate, nibut and ocular surface symptoms during visual display unit use. Curr Eye Res. 2014;39:879–84. doi: 10.3109/02713683.2013.859273. - DOI - PubMed
    1. Yaginuma Y, Yamada H, Nagai H. Study of the relationship between lacrimation and blink in VDT work. Ergonomics. 1990;33:799–809. doi: 10.1080/00140139008927186. - DOI - PubMed
    1. Yang WJ, Yang YN, Cao J, Man ZH, Yuan J, Xiao X, Xing YQ. Risk factors for Dry Eye syndrome: a retrospective case-control study. Optom Vis Sci. 2015;92:199–205. doi: 10.1097/OPX.0000000000000541. - DOI - PubMed
    1. González-Pérez M, Susi R, Antona B, Barrio A, González E. The Computer-Vision Symptom Scale (CVSS17): development and initial validation. Invest Ophthalmol Vis Sci. 2014;55:4504–11. doi: 10.1167/iovs.13-13818. - DOI - PubMed

LinkOut - more resources