Abstract: Objective To investigate the current state of visual fatigue among primary and secondary school students in Zigong City and further analyze its influencing factors, aiming to provide a reference for preventing and treating visual fatigue in this population. Methods A multi-stage stratified cluster random sampling method was used to select students from 12 schools in Zigong between August and October 2023. Basic information was collected, and examinations including uncorrected visual acuity, best-corrected visual acuity, slit-lamp, and fundus examinations were conducted. Students were divided into groups based on the presence or absence of visual fatigue. Descriptive analysis was used to assess the prevalence of visual fatigue, while univariate and multivariate analyses were employed to identify influencing factors. Results A total of 7 510 primary and secondary school students were included in the study, with 1 226 cases of visual fatigue detected, yielding a detection rate of 16.32%. The visual fatigue group showed significantly lower tear secretion test results, tear film breakup time, and uncorrected visual acuity compared to the non-visual fatigue group (all P< 0.01). Multivariate logistic regression analysis revealed that myopia (OR=5.546) and daily computer usage time (OR= 1.964) were risk factors for visual fatigue, while sleep duration (OR=0.456), frequency of daily eye exercises (OR=0.303), and daytime outdoor activity time (OR=0.142) were protective factors. Conclusions The detection rate of visual fatigue among primary and secondary school students in Zigong is relatively high. Factors such as myopia, daily sleep duration, computer usage time, frequency of eye exercises, and daytime outdoor activity time significantly influence the occurrence of visual fatigue. Strengthening vision monitoring and eye health education for students in Zigong, targeting these factors, is essential to alleviate visual fatigue.

Key words: Primary and secondary school students, Visual fatigue, Influencing factors, Vision monitoring