Data used in this project were obtained from the National Students’ Common Diseases and Health Influencing Factors Surveillance and Intervention in the Shihezi City Area, a project conducted by the Chinese Center for Disease Control and Prevention (CDC). The program was jointly administered by education and health departments at all levels, providing high-quality surveys and data. This study was conducted in 2022 and students from schools in Shihezi city were selected as the study population. A multi-stage stratified cluster sampling method was used. In the first step, the city was divided into urban and rural administrative units, and schools were selected from three categories: primary, junior high, and senior high schools. In the second step, stratified sampling was conducted according to grade, followed by class-level sampling to form the study sample. In the random cluster sampling, a certain number of classes were selected to meet the minimum requirements for the study and sample size. This included three elementary schools, five middle schools, and four high schools in urban areas, as well as three elementary schools and two middle schools in rural areas (where there are no high schools). All students underwent a vision examination, while only students in grades ≥4 of primary school completed the questionnaire. The final sample size comprised 6,092 students (3,113 boys and 2,979 girls), of whom 4,578 were in grades ≥4. Additionally, 4,511 and 2,039 students were from urban and rural areas, respectively. Each student’s parent or guardian was informed and provided written consent before the ophthalmological examinations. This study adhered to the tenets of the Declaration of Helsinki and was approved by the Ethical Review Committee of the First Affiliated Hospital of Shihezi University. Participants provided informed consent to participate in the study before taking part (KJ2024-036-02).

A standard logarithmic visual acuity chart and computerized automated optometry TOPCON KR-1 (Tokyo, Japan) under non-ciliary muscle paralysis (non-dilated pupils) were used to test visual acuity in both the right and left eyes. The standard GB/T 11533–2011 logarithmic 5-point recording visual acuity chart was utilized. Refraction was assessed through an objective examination using desktop automatic computer optometry under non-ciliary muscle paralysis conditions. Three measurements were taken for each eye and averaged. The test results were recorded by the on-site testing physician in the CDC Student Common Diseases and Health Factors Monitoring Information System.

The questionnaire was developed by the Chinese CDC and completed on-site by students in grades ≥4. Before administering the questionnaire, the researcher explained its significance, emphasized the confidentiality of the responses, and asked students to maintain an appropriate distance from each other to ensure careful answering. The survey covered several aspects, including parental myopia, eye environment, eye habits, screen use, outdoor activities, and sleep (Schedule 2). The results of the questionnaire were directly uploaded to the CDC Student Common Diseases and Health Factors Monitoring Information System.

According to the Chinese National Myopia Screening Standards, the diagnostic criteria for screening myopia included a standard logarithmic visual acuity of <5.0 in the naked eye (without correction) and a computerized optometric spherical equivalent visual acuity of <−0.50 D in the case of non-ciliary muscle paralysis (14). Individuals with myopia in at least one eye, or those wearing keratoconus lenses, were counted in the total number of myopia cases. Subjects wearing contact lenses were asked to remove them for the examination.

The screeners were certified national practitioners, technicians, or nurses specializing in optometry, all of whom had received relevant training. During the survey, retest subjects were randomly selected, constituting 5% of the students tested that day. Both non-corrected visual acuity and best-corrected visual acuity were reassessed.

Data were double-entered into the database using the EpiData 3.1 parallel data entry method based on a standardized questionnaire provided by the CDC. The data were verified by the National Center for Disease Control and Prevention (NCDC). Statistical analysis was performed using SPSS 27.0. Count data were expressed as the number of cases (percentage), and analysis of variance for the count data was performed using the χ² test. Myopia influences were analyzed using unconditional binary logistic regression, with myopia-related influences as the independent variable and the presence or absence of myopia as the dependent variable. Propensity score matching was based on matching baseline characteristics of students in the myopic and non-myopic groups. The determinants used to create the propensity scores included four variables: gender, grade level, urban/rural residence, and parental myopia. Unconditional binary logistic regression analyses were performed by matching students with the same propensity score on a one-to-one basis without replacement and equalizing the two groups by eliminating non-matched cases. The significance level was set at α = 0.05 (two-sided).

Only students in grade 4 or above completed the questionnaire: 1,514 participants were in grades 1–3, and 4,578 were in grade 4 or above. Univariate logistic regression analysis revealed that the following factors were associated with an increased risk of myopia: female sex, rural residence, higher school grade, greater height, higher body weight, infrequent seat changes, never adjusting seat height, spending >2 h on homework after school, reduced exercise time due to academic workload, parental non-restriction of electronic device use, poor writing posture, lack of teacher reminders for proper reading/writing postures, lack of parental reminders for postures, prolonged near-work without breaks, outdoor time < 1 h/day, parental myopia, no vision examination within the past year, reading/using electronic devices in sunlight, reading/using devices in dark conditions, reading/using devices while lying on one’s side, and reading/using devices while walking or riding. Conversely, sleep duration >10 h/day and outdoor activities during class breaks were protective factors against myopia. The details are presented in Table 3.

The univariate analysis results were evaluated using unconditional binary logistic regression. The multifactorial analysis showed that parental myopia and reading and writing with eyes no more than one foot away from the book were risk factors for myopia after removing the effects of gender, grade, and urban versus rural areas (Table 4).

Because the study population varied widely in terms of gender, urban/rural status, parental myopia, and baseline grade status, to eliminate the effects of covariates, we ended up conducting a multifactorial analysis of the 2,454 individuals after matching propensity scores for these four variables. The results of the multifactorial analysis are shown in Table 5. The results indicated that shorter sleep duration and reading distances of less than 33 cm were risk factors for myopia while receiving a visual acuity examination at least once in the past year and watching television from a distance of more than 3 m from the display were protective factors.

In this study, the overall myopia prevalence was 60.66%, with 41.01% of primary school students, 74.11% of middle school students, and 86.02% of high school students affected—rates that exceed the national average. According to data released in 2020 by the National Health Commission of China, the overall myopia rate among Chinese children and adolescents was 52.7%, with 35.6% in primary school students, 71.1% in junior high school students, and 80.5% in senior high school students, reflecting an increase of 2.5 percentage points compared to 2019 (50.2%). Myopia incidence rates among Chinese children and adolescents not only rank among the highest globally but also continue to rise, with onset ages trending younger. Therefore, urgent measures are necessary to curb the rapid progression of myopia.

This study found that the prevalence of myopia tends to increase as the grade level advances. The highest myopia prevalence, 86.02%, was observed among high school students, likely due to the heavy school workload and prolonged, frequent periods of eye strain. This may also explain the difference in myopia prevalence between urban and rural students, as myopia prevalence is lower in rural students. This may be because rural students experience less study pressure compared to urban students.

In this study, a statistically significant difference in myopia prevalence was found between boys and girls (male: 57.43%, female: 64.06%, χ² = 30.118, p = 0.001), with girls having a 1.445 times higher risk of developing myopia compared to boys, similar to the results of many studies (6, 15, 16). This gender difference may be due to boys spending more time outdoors than girls. However, it could also be influenced by social factors, as girls have had access to educational opportunities in recent years (17).

The present study showed a high genetic predisposition to myopia, consistent with previous studies demonstrating that children with myopic parents are more likely to develop myopia than those with non-myopic parents (18–20). Jones et al. (21) stated that myopia in one parent increases the risk of myopia in the child by a factor of 2.08, while myopia in both parents raises the risk by a factor of 5.07. However, the rapid increase in myopia incidence cannot be attributed to genes alone; environmental and behavioral factors are likely more significant contributors.

Compared to the past, young people are increasingly involved in indoor and sedentary activities, and electronic devices have an ever-growing presence in daily life. Additionally, more stringent entry barriers and the need for higher qualifications keep students in school for longer periods, leaving less time for relaxation.

We found that urban/rural status, gender, school age, and parental myopia had a significant impact on the results of the multifactorial analyses, affecting the inclusion of other variables in the model. Therefore, we attempted to eliminate the influence of these variables by using propensity score matching before conducting the multifactorial analysis. The results showed that keeping the eyes ≤33 cm away from the book while reading was a risk factor for myopia (OR = 1.347, p = 0.048). Furthermore, studies have demonstrated that a shorter reading distance leads to faster myopia progression (22), suggesting that maintaining good reading and writing postures and sleeping less than 8 h are beneficial in preventing myopia. These findings are consistent with previous studies (23, 24).

Exploring the factors influencing myopia aims to improve future interventions and provide valuable guidelines for effective myopia prevention in children and adolescents. According to Lin et al. (10), myopia prevention in primary and secondary school students needs to be differentiated and targeted based on region, school type, and climatic conditions. Some inherent factors, such as family history, gender, and school age, cannot be changed. Additionally, it seems unlikely that the increasing demands for higher grades will allow children to reduce their workload. Therefore, our common aspiration is to prevent myopia without affecting students’ normal learning.

Based on our results, students need to sit upright and keep their hands 1 inch away from the tip of the pen, their chests 1 fist away from the table, and their eyes 1 foot away from the book while reading and writing. When engaging in prolonged eye activities, taking breaks, going outdoors for a few minutes, and looking into the distance are important. Recess activities should be outdoors as much as possible at school, as some studies show that outdoor activities can prevent myopia (25). It is also important to avoid putting strain on the eyes under poor lighting conditions, crouching or lying down to read, and reading while walking or traveling in a car. Teachers should encourage students to maintain good sitting posture in class or during studying and to go outdoors between classes, as some studies demonstrate that proper monitoring of outdoor activity adherence is essential for the protective effect of the intervention (26). Additionally, avoiding the reduction of time allocated to students’ physical education classes or outdoor activities is necessary. For parents, limiting the amount of time their children spend on electronic devices, such as mobile phones, tablets, and computers, is necessary. Furthermore, they should supervise their children at home to ensure they maintain good reading and writing postures and purchase eye-protecting desk lamps to ensure good lighting conditions when reading and writing.

This study was conducted as part of the National Monitoring and Intervention Program for Common Diseases and Health Influencing Factors of Chinese Students, ensuring methodological standardization and centralized quality control measures across all regions. The research team comprised uniformly trained professionals, further enhancing the reliability and validity of the findings. Methodologically, our use of propensity score matching to address confounding variables represents an innovative approach in this field. Notably, our inclusion of rural student populations distinguishes this study from previous studies that often overlooked this demographic. However, several limitations should be acknowledged. First, despite the substantial sample size, the cross-sectional design inherently restricts causal inference regarding myopia development. Second, as with many large-scale screening programs, ethical and logistical constraints precluded pupil dilation during refractive assessments, potentially leading to an overestimation of myopia prevalence. These limitations highlight the need for longitudinal studies and refined diagnostic protocols in future research.