Myopia Progression and its Risk Factors among Fourth-Grade Children in Zhejiang, China: a Two-Year Prospective Cohort Study

Introduction

In recent years, the prevalence of myopia among children and adolescents has become a pressing public health issue globally, with particularly alarming rates in East Asia, including China. East and Southeast Asian countries report the highest prevalence rates among schoolchildren, for example, 47.4% in China [1], 64% in Japan [2] and 48.2% in Korea [3]. South Asians have a much lower  rate, such as India (13.1%) [4], black Africans have the lowest prevalence (7%) [5], and white Europeans have inter mediate prevalence, such as Netherland (2.4%) [6], France (42.7%) [7], and Denmark (17.9%) [8]. The prevalence of myopia in South Asians and minimal change in the prevalence of myopia in whites. It is expected that by 2050, the global myopia population will reach 4.76 billion, and the population with high myopia will reach 938 million, accounting for nearly 50% and 10% of the world’s population, respectively [9].

Myopia results from various influences, both genetic and environmental. A wealth of research has identified several key contributors to the development and worsening of myopia, including near work, outdoors time, heavy electronic device usage, and parental myopia [10,11]. Other factors still need to be further confirmed by cohort studies. At present, the mechanisms behind the progression of myopia and the factors influencing it are not yet fully understood. The advancement of axial myopia relies on the elongation of the eye’s axis [11], and since this elongation is a common basis for both the onset and progression of myopia, the progression should also be influenced by the amount of time spent on outdoor activities. An intervention study in Taiwan showed that there was no significant relationship between outdoor activity and myopic shift [12]. However, a cohort study in Henan province of China showed that outdoor activities had protective effect on myopic progression among grade7 school children [13]. A Meta analyses in 2025 assumed higher outdoor exposure appeared more effective in reducing myopia progression, but the certainty of this evidence was rated as low due to suspected publication bias [14]. Therefore, we need to explore new methods to reduce the influence of confounders, identify covariates, and measure the magnitude and importance of interactions between variables.

In this study, we conducted eye examinations and questionnaires on related factors for primary school students in grades 4 in Zhejiang Province, China, for 2 consecutive years (2023-2024), aiming to explore risk factors affecting myopia progression. This study will provide a reference for the development of myopia prevention and control strategies for adolescents.

Methods Study Population

A population-based and cross-sectional study was conducted in September 2023, and again in September 2024. Randomized stratified whole cluster sampling was used in this study. Zhejiang Province has 11 prefecture-level cities. We randomly selected on urban area and on suburban county from each prefecture-level city, with two primary schools from the urban area and two from the suburban county, respectively. Investigations were conducted on whole classes at 4th-5th grade level in primary schools, with at least 80 students selected from each grade. The data of 4th-grade students from survey in 2023 with the 5th-grade students from survey in 2024 were matched by school, class, name, and date of birth. A total of 7115 students were confirmed to be recruited in the investigation over consecutive years.

Informed consent was obtained from all participants. The study was approved by the ethics committee of Zhejiang Provincial Center for Disease Control and Prevention and followed the tenets of the Declaration of Helsinki.

Ocular Measurements

Ocular measurements included distance vision examinations and refraction tests. The staff consisted of at least one specialist ophthalmologist and several technicians or nurses in specialist areas. All testers were trained to be proficient in the testing methods and could only start work after passing the test. Uncorrected distance visual acuity (UDVA) was uniformly performed using a standard logarithmic visual acuity E-chart, and the test results were recorded using the five-point recording method. Non-cycloplegic autorefraction examinations were conducted using Topcon RM800 computer optometry (Topcon Co., Japan) to read the values of spherical lenses, cylinder, and axial length. Spherical equivalent (SE) was calculated as spherical lenses plus 1/2 cylinder. Myopia was defined as UDVA < 5.0 and SE < −0.50D. Subjects wearing keratoconus lenses or using low-concentration atropine eye drops were excluded.

The annual refractive change was defined as the total refractive change, with negative values indicating myopia progression. According to annual rate of refractive error progression, the patterns of refraction development are categorized as follows: (1) Rapid progression pattern: ≤-1.00 diopters (D) per year; (2) Moderate progression pattern: ≤-0.50 D/year and >-1.00 D/year; (3) Slow progression pattern: ≤-0.25 D/year and >-0.50 D/year; (4) Stable pattern: >-0.25 D/year [15].

Questionnaire Study

Self-administered questionnaires, including students’ basic information, myopia-related reading and writing postures, and behavioural habits, were used in 2023. After the unified training, investigators sent questionnaires to schools, asked the students to fill in, and requested the teachers to collect them back. After collecting and reviewing the questionnaires, in case of incomplete and illogical questionnaires, investigators contacted the respondent to explain it and refill the questionnaire.

Statistical Analysis

The data were analyzed using the SE for the worst eye of each student. A database was created using Epi Data 3.1, and after data were entered in a double-blind manner and checked for errors, the data were analyzed using the R software (version 4.0.3, https://www.r-project.org/). Descriptive statistics were expressed as the mean ± standard deviation (mean ± SD) for continuous variables and as the rate (%) for categorical variables. Non-normal continuous variables are expressed in the form of quartiles. Paired t-test was conducted to compare SE in two consecutive years, and paired chi-squared test was applied for myopia rate comparation. Multifactor linear regression was used to analyze the relationship between individual baseline characteristics and environmental factors and changes in students’ SE change. To determine the associations between influencing factors and refraction progression patterns, logistic regression analysis was applied to compare slow, moderate and rapid pattern with stable pattern. Due to the similar results between the baseline and the final refraction for the right eye and the left eye, this study only presents the data of regression models for the right eye, and results for the left eye was presented as supplementary tables for sensitivity analysis. A p-value <0.05 was considered to be statistically significant.

Supplementary 1: Refractive status of left eye from 2023 to 2024

Supplementary 2: Multivariate regression analysis of factors on refractive change.

Supplementary 3: Multivariate logistic regression analysis of factors on myopic shift.

Results

The main characteristics of the study participants are reported in Table 1. Of the 7115 Grade 4 school students, the mean age in the 2023 baseline survey was 9.36±0.49 years. The proportion of male students in the three groups was 52.49%. The situation of parental myopia and frequency of reading, outdoor activity and electronic device usage were also shown in Table 1.

Table 1: Baseline characteristics of the study participants.

The median equivalent spherical lenses were -0.38(-1.38,0.13) D in Grade 4 and -0.75(-2.00, -0.13) D in Grade 5, respectively. The difference between the two groups was statistically significant (t=3.886, P<0.001). Among male students, the SE in Grade 4 and Grade 5 were -0.38 (-1.31, 0.13) and -0.69 (-1.88, 0.00), respectively, with a statistically significant difference between the two years (t=2.235, P<0.001). A similar trend was found among males (-0.38(-1.31, 0.13) vs. -0.69(-1.88, 0.00), t=-15.818, P<0.001) and females (-0.50(-1.50,0.00) vs. -0.93(-2.13, -0.13), t=3.189, P<0.001). (Figure 1a). The myopic rates significantly increased from 2023 (39.38%) to 2024 (52.89%) (χ²=589.64, P<0.001). The myopia rate progression was also existed among male (37.02% vs. 48.38%, χ²=231.77, P<0.001) and female students (41.99% vs. 57.87%, χ²=363.21, P<0.001) (Figure 2b).

Figure 1: Refractive status of right eye (a) and prevalence of myopia (b) from grade 4 to grade 5.

There were significant differences in the annual refractive change among students with different refractive statuses. Multiple linear regression analyses were performed with annual refractive change as the dependent variable and 9 risk factors of myopia progression as the independent variables (Table 2). The results revealed that female (ß(SE)=-0.186(0.037), P <0.001), higher baseline refraction (ß(SE)=-1.000(0.000), P <0.001), more parents with myopia (ß(SE)= -0.352(0.025), P <0.001) will show more decreased myopic refractive change, and increased outdoor activity duration was associated with increased refractive change (1~2h: ß(SE)=0.094(0.044), P=0.032; 2~3h: 0.244(0.057), <0.001; ≥3h: 0.264(0.084), 0.002).

Table 2: Multivariate regression analysis of factors on refractive change.

Multiple logistic regression analyses were conducted, utilizing refractive development pattern as the dependent variable and 9 risk factors as the independent variables (Table 3). Female (moderate: OR (95%CI) =1.23(1.09-1.39), P<0.001; rapid: 1.58(1.38-1.80), <0.001) and more parents with myopia (rapid: 1.18(1.08-1.28), <0.001) were risks factors for refraction development progression, while increased outdoor activity duration (moderate: ≥3h: 0.73(0.55-0.97), 0.024; rapid: 2~3h: 0.75(0.62-0.92), 0.003; ≥3h: 0.69(0.51-0.93), 0.009) and sleeping hour (rapid: 0.93(0.88-0.99), 0.030) were protective factor.

Table 3: Multivariate logistic regression analysis of factors on patterns of refraction development.