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Investigation and analysis of poor vision status and related influencing factors in adolescents

Published on Jul. 03, 2023Total Views: 1380 times Total Downloads: 348 times Download Mobile

Author: Yun-Yao WANG 1 Qin-Mei WANG 1 Chun-Jiao WU 2 Ying-Shan SHAO 3

Affiliation: 1. Eye and Optometry Center of Wenzhou Medical University, Wenzhou 325000, Zhejiang Province, China 2. Department of Ophthalmology, Aier Eye Hospital of Xianning, Xianning 437000, Hubei Province, China 3. Department of Ophthalmology, Aier Eye Hospital of Jingzhou, Jingzhou 434020, Hubei Province, China

Keywords: Adolescents Poor vision Quality of life Vision care behavior Influencing factor

DOI: 10.12173/j.issn.1004-4377.202302092

Reference: Wang YY, Wang QM, Wu CJ, Shao YS. Investigation and analysis of poor vision status and related influencing factors in adolescents[J]. Journal of Mathematical Medicine, 2023, 36(6): 427-433. DOI: 10.12173/j.issn.1004-4337.202302092[Article in Chinese]

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Abstract

Objective  To investigate and analyze the status of poor vision in adolescents and the related influencing factors.

Methods  A retrospective analysis was conducted to select 1 256 adolescents who received visual acuity examination in Eye and Optometry Center of Wenzhou Medical University from July 2021 to October 2022 as the research subjects. The patients were grouped according to whether they had detected impaired visual acuity. 527 adolescents without impaired visual acuity were set as the control group, and 729 adolescents with impaired visual acuity were set as the observation group. The status of poor visual acuity among adolescents was analyzed, and the relevant influencing factors of poor visual acuity among adolescents were summarized by univariate analysis and Logistic regression analysis.

Results  In 1 256 cases of adolescents, 729 cases of poor vision were detected, accounting for 58.04%. Among them, 186 cases (14.81%) had mild impaired vision, 213 cases (16.96%) had moderate impaired vision and 330 patients (26.27%) had severe impaired vision. The score of quality of life in observation group was higher than that in control group, and the score of visual care behavior was lower than that in control group (P<0.05). Univariate analysis and Logistic multivariate regression analysis showed that gender, residence, heredity, reading distance, reading and writing posture, time spent online, outdoor activities, diet, eye exercises and sleep time were not only related but also independent influencing factors of poor vision in adolescents (P<0.05).  Conclusion  The current situation of poor vision among adolescents is not optimistic, and targeted measures need to be taken in time to improve their visual health and quality of life.

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References

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