BackgroundHigh myopia (HM) may elicit irreversible pathological changes in the fundus and severely impair visual quality, thereby becoming a major public health issue in China. However, the influencing factors associated with HM remain unknown in Chinese college students, whose visual quality is crucial to country development.MethodsThis is a cross-sectional observational study. Two thousand three hundred and fifteen undergraduate and graduate students were initially recruited from various majors in 3 universities in Tianjin, China. Under the principle of voluntary participation and informed consent, simple random sampling was conducted in the recruited subjects while maintaining balanced number of subjects from each major. After screening with inclusion and exclusion criteria, 96 undergraduate and graduate students (186 eyes) were finally included and divided into non-HM and HM groups. The eyes of subjects were examined by optical coherence tomography angiography (OCTA) for vessel density and structure thickness at the macula and optic disc, and the subjects were surveyed by an itemized questionnaire on lifestyles and study habits.ResultsThe OCTA and questionnaire results revealed 10 factors, including hemodynamic and anatomic parameters and lifestyle metrics, with statistical significance between the non-HM and HM groups. Receiver operating characteristic curve analysis showed that vessel density of the inner retina at the macula, vessel density of the radial peripapillary capillary at the optic disc, smartphone usage time, continuous near work time, and sleeping after midnight had superior values of area under the curve (AUC > 0.700). Therefore, these 5 factors were selected for univariant and multivariant logistic regression analyses. A prediction model comprising the 5 influencing factors had an AUC of 0.940 and 95% CI of 0.908–0.972.ConclusionThis study for the first time identified the vessel density of the inner retina at the macula, the vessel density of the radial peripapillary capillary at the optic disc, smartphone usage time, continuous near work time, and sleeping after midnight as influencing factors associated with HM in Chinese college students. A prediction model comprising the 5 influencing factors was proposed for calculating likelihood of a Chinese college student developing HM, based on which lifestyle improvement and medical intervention might be recommended.