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HomeArticlesVol 34,2024 No.11Detail

Analysis of influencing factors and prediction model construction for asthenopia in mental laborers

Published on Dec. 17, 2024Total Views: 74 timesTotal Downloads: 32 timesDownloadMobile

Author: WANG Hui1 2 MA Xiaolu1 2 ZHANG Yun1 2 ZHANG Lingling1 2 LIU Hui1 2 ZHANG Zhenhua1 2 SUN Jing1 2 GU Jun1 2

Affiliation: 1. Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, Shanghai 200011, China 2. Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, Shanghai 200011, China

Keywords: Asthenopia Mental laborers Influencing factor Predictive model Tea drinking Sleep duration Dry eye Allergic conjunctivitis

DOI: 10.12173/j.issn.1004-5511.202407085

Reference: Wang H, Ma XL, Zhang Y, Zhan LL, Liu H, Zhang ZH, Sun J, Gu J. Analysis of influencing factors and prediction model construction for asthenopia in mental laborers[J]. Yixue Xinzhi Zazhi, 2024, 34(11): 1210-1219. DOI: 10.12173/j.issn.1004-5511.202407085. [Article in Chinese]

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Abstract

Objective To analyze influencing factors of asthenopia among mental laborers, and construct a predictive model.

Methods This cross-sectional study included mental laborers. Basic information, lifestyle habits, and ocular health were collected. Ocular health was assessed using the Ocular Surface Disease Index (OSDI), the Allergic Conjunctivitis 12-item (AC-12), and the Asthenopia Survey Questionnaire 17-Item (ASQ-17). Univariate and multivariate Logistic regression analyses were conducted to identify factors associated with asthenopia and to construct a predictive model. The performance of the predictive model was comprehensively evaluated and validated using the receiver operating characteristic (ROC) curve and area under curve (AUC), calibration curve, decision curve analysis, and Bootstrap resampling method.

Results  221 mental laborers were included, with 102 (46.15%) having asthenopia. Multivariate Logistic regression analysis showed that dry eye [OR=1.16, 95%CI(1.10, 1.21)] and allergic conjunctivitis [OR=1.17, 95%CI(1.06, 1.28)] were risk factors for asthenopia, while appropriate sleep duration with 8~<11 hours per night [OR=0.14, 95%CI(0.02, 0.98)] and daily tea drinking habits [OR=0.40, 95%CI(0.16, 0.99)] were associated with a reduced risk of asthenopia (all P<0.05). The constructed asthenopia predictive model demonstrated good predictive performance, with AUC of 0.913[95%CI(0.875, 0.950)]. The models’ predicted probabilities were highly consistent with actual observations, indicating good calibration. Internal validation results showed an accuracy rate of 80.6% and a Kappa value of 0.609. Decision curve analysis indicated that the model's application net benefit was significantly superior to "no intervention" and "full intervention" strategies.

Conclusion We recommended to strengthen the management of dry eye, allergic conjunctivitis, and abnormal refractive status, and to promote good sleep and tea-drinking habits, which can help alleviate the problem of asthenopia in mental laborers, and improve work efficiency and quality of life.

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