Introduction: Myopia is an increasingly serious health problem in China. The aim of this study was to investigate the prevalence of myopia and the factors associated with it among students in Nantong, China, to show the current status of myopia prevention. Methods: This school-based, cross-sectional study examined students from all high schools in an urban area of Nantong, China. At least two classes were randomly selected from each grade of each school. A self-reported questionnaire was used to collect the required information. Univariate analyses were performed to identify associations between myopia and various parameters. Noncycloplegic autorefraction and visual acuity were assessed for each student. Factors that were statistically significant in univariate analyses were selected for multivariate analyses. Myopia was defined as a spherical equivalent refraction of ≤−0.5 diopters. Results: The completion percentage of students out of the whole high school was 6.5%. The overall prevalence of myopia was 94%. The response percentage of the number of validated questionnaires was 90.2%, of which 50.2% (n = 1,466) were from male participants, and 49.8% (n = 1,452) were from female participants. The mean (SD) of age was 15.22 ± 1.75 years, ranging from 12 to 18 years. Factors such as female sex, older age, parental myopia, sitting in the back of the classroom, increased homework time, and minimal outdoor activity were significantly associated with a higher risk of myopia (p < 0.05). In the myopic population, most students (67.9%) did not take measures to prevent further progression of myopia. Conclusion: The prevalence of myopia among high school students was 94%. Female sex, older age, parental myopia, sitting in the back of the classroom, increased homework time, and minimal outdoor activity were significantly associated with a higher risk of myopia. Most students with myopia (67.9%) did not take measures to prevent further progression of myopia.

Myopia is an increasingly serious health problem in the world. By 2050, the prevalence of myopia in the global population will be as high as 49.8% [1]. At present, myopia has become a highly prevalent disease among children and adolescents in East Asia [2, 3]. In China, the prevalence of myopia in preschool children in Shanghai is 5.9% [4], and the prevalence of myopia among school age children in a study involving six provinces was 55.7% [5] and 86.8% [6] among university students in Nanjing. The myopia problem is more than just an optical disorder because it is associated with ocular diseases including cataract, glaucoma, macular degeneration, and retinal detachment [7‒11]. It is therefore important to know the current prevalence of myopia and to understand the factors that influence the development of myopia, to prevent and reduce the incidence.

In previous studies, some factors related to myopia have been studied. These studies showed that a higher educational level, increasing age, larger amount of near work, family history, and less time participating in outdoor activities were correlated with a high risk of myopia [12‒15]. However, some factors are still controversial. For example, the results of studies on the correlation between an overload of close work and the prevalence of myopia are not consistent [16, 17]. More evidence is therefore needed to determine the factors that influence myopia. At present, some interventions to reduce the progression of myopia in children have been effective [18]. However, the use of these interventions among Chinese adolescents remains unknown. In addition, after the closure of schools caused by COVID-19 in 2020, normalized epidemic prevention and control have become important events in the lives of all students, which inevitably led to changes in the quality of life. The effect of these changes on the prevalence of myopia also needs to be determined. In China, high schools are divided into junior high schools and senior high schools. We therefore conducted this cross-sectional study to investigate the prevalence of myopia among high school students, to identify potential contributing factors to myopia, and to provide a snapshot of myopia prevention and control in Nantong, a moderately sized city of seven million people living on the east coast of China.

Ethical Approval, the Study Design, and the Participants

The study was approved by the Ethics Committee of the Second Affiliated Hospital of Nantong University, China (approval number: 2020KT068). All protocols used in this study followed the tenets of the Declaration of Helsinki.

A school-based study conducted in Yiwu last year showed that the prevalence of myopia increased from 75.6% to 92.7% from 12 to 18 years of age [19]. To achieve a power of 80%, the sample size was calculated using the formula, n = t2pq/d2, assuming a design effect of 1.5 due to cluster sampling and a nonresponse rate of 5% (t = 2 for a 95% confidence interval [CI], q = 1 − p, d = 0.1 p). Considering the different prevalence of myopia in each age-group, we separately estimated the sample size of each age-group from 12 to 18 years of age. Among them, the sample size of the 12-year-old population was the largest, with a minimum of 200 students included. To ensure better multifactor analyses (including some factors that previously were rarely studied), more samples were included in the protocol. This study used junior and senior high school students in Nantong as the research subjects. In the urban area of Nantong, all junior and senior high schools (15 schools) participated in this activity. At least two classes were randomly selected from each grade of each school to ensure that no less than 80 students were selected at a time. This sample size was sufficient to detect risk factors using multivariate analyses.

The investigators arranged a meeting with the class director, the students, and at least one parent or other responsible adult before recruitment to explain the objectives and procedures of the study. After explaining the nature of the study, the informed consent of each child was obtained from at least one parent or other responsible adult of a student. Verbal consent was also obtained from each student. With the help of a well-trained investigator, all students and their parents completed a detailed questionnaire together at the meeting. Within the following week, the survey was conducted by a team of four optometrists, two public health doctors, and five ophthalmologists from January 5 to January 11, 2020, including an experienced chief physician in pediatric ophthalmology, who acted as the project coordinator and was responsible for the whole survey procedure.

Before commencement of the study, the investigators visited and arranged each venue to regulate standardized lighting and testing distances. A closed classroom was used to minimize interference and to limit the number of students being checked who entered, to facilitate the testing. Autorefractors for measuring refractive errors were calibrated every day. The students with current corneal refractive therapy were asked to wear spectacle glasses on the day of testing. Everyone wore safety masks throughout the process. The percentage of children voluntarily participating in the invitation was 89.34%.

A total of 3,621 students were invited to participate in the study, and 3,235 students volunteered for the eye examinations. A total of 2,918 questionnaires were completed and qualified for our survey. The completion percentage of students out of the whole high school was 6.5%. The completion percentage of the questionnaires was 90.2% of the 3,235 students who ended up participating. The criterion for acceptance of each student into the study was as follows: 100% completion of the questionnaire plus parental/guardian consent. We obtained advice about the questionnaire from experts engaged in refractive diseases and epidemiological research and developed the questionnaire according to their advice. The questionnaire was divided into several sections. The questionnaire is available online (online suppl. Material 1; for all online suppl. material, see www.karger.com/doi/10.1159/000524293).

It included questions about demographic information, such as sex, age, current height, and current weight. Some of the questions included the parental history of myopia, whether the student was born prematurely, feeding status during childhood, preference for sweets, preference for carbonated beverages, average daily sleep time, and where the student liked to stay during recess.

The students’ near work was assessed by asking how many hours they spent doing homework and using electronic products (e.g., online tutoring after class, mobile phone use, iPad use, and computer use) on average every day. In addition, a question queried whether the distance between their eyes and books was less than 33 cm.

Visual behavioral factor questions included the time watching TV every week, the rest time after close work, and the position of the classroom seat. The mean number of hours spent outdoors each day was calculated using the following formula [13]: ([hours spent on a weekday] × 5 + [hours spent on a weekend day] × 2 divided by 7). In addition, the following questions were asked: if your parents find that your eyesight has decreased, will they take you for an examination; and what are your current measures used to prevent and control myopia?

In the optometric tests, well-trained investigators performed eye examinations. Noncycloplegic autorefraction was conducted using a micro vision (WSRMK-8000; Biobase, Shandong, China). Refractive error was measured three times. If any two of three results were greater than 0.50 D (diopters), additional checks were conducted at the same visit. The average value of the three good measurements was then analyzed. Uncorrected visual acuity and best-corrected visual acuity were measured by a standard logarithmic liquid crystal tumbling E chart (WSVC-100; Qingda Optometry, Berkeley, CA, USA) at 5 m. The best-corrected visual acuity was corrected according to the autorefractor results. The results of the measurements were recorded in the student’s online refractive archives.

The spherical equivalent (SE) refraction was calculated as the sum of the sphere power and half of the cylinder power. Considering that almost 87.7% of epidemiologic studies of myopia used less than −0.50 D or −0.50 D or less as the definition of myopia [20], we defined myopia as an SE of ≤−0.5 D. Emmetropia was defined as −0.5 D < SE ≤ 0.5 D. Low myopia was defined as −3.0 D < SE ≤ −0.5 D. Moderate myopia was defined as −6.0 D ≤ SE ≤−3.0 D. High myopia was defined as an SE < −6.0 D. Hyperopia was defined as an SE > +0.5 D.

Statistical Analyses

Data were analyzed using SPSS statistical software for Windows, version 22 (SPSS, Chicago, IL, USA). The measurements of the right eye were used for data analyses. Correlations between myopia and the various parameters considered in this study were then determined. Among them, the χ2 test was used for disordered enumeration data, the rank sum test was used for orderly enumeration data, and two independent samples t tests were used for the measurement data. The specific associations of those factors that correlated with myopia were confirmed using univariate analyses. Factors that showed a univariate association with a value of p < 0.05 were selected as candidate variates for multivariate analyses [6]. The odds ratio (OR) and 95% CI for the associated factors were then calculated. Factors with an OR <1 were regarded to be protective against myopia, whereas those with an OR >1 were considered to be risk factors for myopia. Continuous variables are expressed as the mean ± standard deviation, and the categorical variables are expressed as percentages. A value of p < 0.05 was considered as statistically significant.

Invalid questionnaires were excluded, and 2,918 questionnaires were validated for analyses. The response percentage of the number of validated questionnaires was 90.2%, of which 50.2% (n = 1,466) were from male participants, and 49.8% (n = 1,452) were from female participants. According to the study, the overall prevalence of myopia was 94%. The mean of age was 15.22 ± 1.75 years, ranging from 12 to 18 years. Figure 1 shows the characteristics of the participants. Among them, most students had mild (35.0%) and moderate (44.7%) myopia, the proportion of high myopia was as high as 14.3%, 4.9% had emmetropia, and only 1.1% of the students had hyperopia.

Fig. 1.

Distribution of the refractive status. Emmetropia was defined as −0.5 D < SE ≤0.5 D. Low myopia was defined as −3.0 D < SE ≤−0.5 D. Moderate myopia was defined as −6.0 D ≤ SE ≤−3.0 D. High myopia was defined as an SE < −6.0 D. Hyperopia was defined as an SE > +0.5 D.

Fig. 1.

Distribution of the refractive status. Emmetropia was defined as −0.5 D < SE ≤0.5 D. Low myopia was defined as −3.0 D < SE ≤−0.5 D. Moderate myopia was defined as −6.0 D ≤ SE ≤−3.0 D. High myopia was defined as an SE < −6.0 D. Hyperopia was defined as an SE > +0.5 D.

Close modal

Using univariate analysis (Table 1), the prevalence of myopia in girls (95.2%) was significantly higher than that in boys (91.4%) (χ2: 16.58, p < 0.05). The prevalence of myopia increased with age (Z: −2.94, p < 0.05), from 12 to 18 years of age, and the prevalence of myopia increased from 90.6% to 96.1%. The prevalence of myopia among the students who had a break in the classroom sessions was 93.9%, while it was 91.8% among students who had a break outdoors, with the difference showing statistical significance (χ2: 4.36, p < 0.05). Daily sleep time was significantly correlated with the prevalence of myopia (Z: −2.89, p < 0.05). With a decrease of sleep time, the prevalence of myopia increased (shown in Table 1). The prevalence of myopia in students who slept less than 6 h a day was 95.2%. In comparison, students whose sleep times were 7–8 h and more than 8 h per day had significantly lower myopia (OR: 0.54, 95% CI: 0.34–0.86, p < 0.05 and OR: 0.49, 95% CI: 0.25–0.96, p < 0.05, respectively). The time spent on homework after class was significantly correlated with the prevalence of myopia (Z: −5.88, p < 0.05). The prevalence of myopia of students who were able to finish homework within 1 h was 88.8%. In comparison, as shown in Table 2, when the daily homework time was more than 2 h, the difference was significant (OR: 2.03, 95% CI: 1.24–3.31, p < 0.05). When the daily homework time was more than 4 h, the prevalence of myopia increased to 96.5% (OR: 3.46, 95% CI: 1.91–6.28, p < 0.05). Daily outdoor activity was significantly correlated with the prevalence of myopia (Z: −3.9, p < 0.05). When the daily outdoor activity was less than 30 min, the prevalence of myopia was 94.9%. In comparison, the prevalence of myopia of students whose daily outdoor activity was 1–2 h and more than 2 h a day was significantly lower (OR: 0.59, 95% CI: 0.38–0.91, p < 0.05 and OR: 0.4, 95% CI: 0.26–0.63, p < 0.05, respectively). A rest interval after close work was significantly correlated with the prevalence of myopia (Z: −2.13, p < 0.05). The prevalence of myopia of students whose rest interval after close work was less than 30 min was 92.1%. In comparison, the prevalence of myopia of students whose rest interval after close work was more than 3 h was significantly increased to 96.4% (OR: 2.19, 95% CI: 1.16–4.12, p < 0.05). The classroom row location was significantly correlated with the prevalence of myopia (Z: −2.24, p < 0.05). The prevalence of myopia in the first row was 90.1%. The prevalence of myopia for students who sat behind the sixth row was 96.2% (OR: 2.81, 95% CI: 1.31–6.04, p < 0.05). However, there was no significant difference between the fourth row and the first row (OR: 1.28, 95% CI: 0.82–2.0, p = 0.27). The proportions of myopia among students with one and two myopic parents were 93.9% and 95.5%, respectively. The prevalence of myopia among students whose parents were not myopic was 91.4%. The presence of myopia in one or both parents was strongly associated with the presence of myopia in the student (OR: 1.44, 95% CI: 1.04–1.99, p < 0.05 and OR: 1.98, 95% CI: 1.3–2.99, p < 0.05, respectively). Table 2 shows the ORs. The two independent samples t tests showed that there was no significant difference in weight and height between the myopia group and the nonmyopia group (p = 0.53, p = 0.24).

Table 1.

The prevalence of myopia and its association with the factors studied

 The prevalence of myopia and its association with the factors studied
 The prevalence of myopia and its association with the factors studied
Table 2.

The association between myopia and other factors studied

 The association between myopia and other factors studied
 The association between myopia and other factors studied

Factors significantly associating with myopia using univariate analysis were processed using multivariate logistic regression analysis (Table 3). After adjustment for other characteristics, female sex, older age, and increased daily homework time had a significantly higher risk of myopia. Having one myopic parent was a risk factor for myopia (OR: 1.46, 95% CI: 1.04–2.03, p < 0.05), and children whose parents were both myopic had the higher risk of myopia (OR: 1.9 95% CI: 1.24–2.91, p < 0.05). Performing more than 2 h of outdoor activity per day was associated with decreased myopia (OR: 0.54, 95% CI: 0.34–0.86, p < 0.05). The prevalence of myopia in the students sitting in the first row of seats in the classroom was 90.1%, and after the sixth row, it was 96.2% (OR: 3.04, 95% CI: 1.39–6.63, p < 0.05).

Table 3.

Factors associated with myopia based on multiple logistic regression analysis

 Factors associated with myopia based on multiple logistic regression analysis
 Factors associated with myopia based on multiple logistic regression analysis

Among 2,722 myopic students, 2,031 wore glasses and 691 did not. Among myopic students, 6.8% used low-dose atropine eye drops (0.01%) to control the development of myopia, 3.9% used high-dose atropine eye drops (1%), and 0.6% used corneal refractive therapy. In addition, 1% used tropicamide or other eye drugs, and 19.8% used traditional Chinese massage, such as ocular gymnastics, to control myopia. A total of 67.9% of the myopic students did not use any treatment to control myopia.

Preventing myopia and its associated pathologies is challenging, although the ability to prospectively identify individuals at greatest risk could help to determine the affected individuals and their possible treatments. This study used noncycloplegic autorefraction, and not more than −0.5 was taken as the standard of myopia. Although these may cause the results to be overestimated, these findings suggested that the current prevalence rates of myopia among high school in China are high. The prevalence of myopia was higher than reported in previous studies in some other cities in China [21, 22]. We confirmed the association between increased myopia and factors among high school students in Nantong, Jiangsu, including older age, parental myopia, increased homework time, little outdoor activity, female sex, and sitting in the back of the classroom.

Our results showed an increase in the prevalence of myopia with increasing age, which is consistent with the results of other studies [23]. In the present study, there was a significant relationship between myopic parents and their myopic children (Table 3). The effect of parental myopia on their children also varied with the number of myopic parents. Compared with children whose parents have no myopia, students with one myopic parent were 1.46 times more likely to suffer from myopia; students with both parents myopic were 1.9 times more likely to suffer from myopia. This result is consistent with other studies from China and other countries [24‒26]. The interaction between parental myopia and environmental factors has been widely studied. Although the possibility remains that heredity factors play a role, environmental factors could not be excluded [27]. Saw et al. [28] showed that myopic parents were more likely to create myopiogenic environments such as spending more time reading than those with no myopic parents. In a study on the prevalence of ametropia in the second generation of Australian school age children, the prevalence of myopia among the second-generation Australian school age children in the Middle East was similar to that of children in other school districts in Australia and higher than that reported in the Middle East [29]. Some studies even showed that environmental factors played a greater role in these two factors [30, 31].

Whether premature birth can affect myopia is controversial [32, 33]. In the present study, the prevalence of myopia was not found to be associated with preterm birth. However, participants only provided information about whether it was premature but could not accurately provide the birth weight and other details. Unfortunately, we could not further analyze the relationship between preterm birth and myopia. In a cross-sectional study of 527 Chinese primary school students aged 6–12 years, breast feeding was reported to be associated with a decreased risk of myopia, and breast feeding was associated with higher hyperopic SE refraction [34]. However, in the present study, we did not find an effect of different infant feeding methods on the prevalence of myopia, which is consistent with the results of Sham et al. [35]. Although the feeding status in childhood may affect the early growth of infants, including the growth of eyes, this effect may not be important in the long term, although this possibility needs further research.

Whether close work is related to myopia is still controversial. Jiang et al. [24] conducted a 2.5-year longitudinal cohort study on primary students from first grade to third grade in Wenzhou, China, and found that close work had no effect on myopia. However, the current study reported the effects and possible interactions of near work and outdoor activity on myopia among Chinese high school students in Nantong, China, and found that the risk of myopia was significantly increased after more than 2 h of homework a day. Compared with students with less than 1 h of homework a day, students with 2–3 h were 2.03 times more likely to suffer from myopia. Compared with students with less than 1 h of homework, students who had more than 4 h were 3.46 times more likely to suffer from myopia. This is consistent with previous studies conducted in Taipei [36]. However, our results were different from a previous study conducted in Caucasians [37] and were also different from findings in Anyang, China, involving participants 10–15 years of age [38]. In the present study, the myopia prevalence tended to decrease when individuals spent more than 2 h daily engaged in outdoor activities. This association was also found in another Chinese study in rural Chinese schools: Wu et al. [39] reported that outdoor activity was associated with a lower prevalence of myopia in children 7–12 years of age. There were also similar results in studies of Caucasians [40, 41]. A meta-analysis that included seven cross-sectional studies reported that one additional hour per week spent outdoors reduced the odds by 2% (OR: 0.98, 95% CI: 0.97–0.99) of having myopia in children and adolescents [42]. This protective effect may result from exposure to light received during outdoor activities. Some animal studies have confirmed that light exposure can stimulate the retina to release dopamine to slow down the development of myopia [43, 44]. Thomson et al. [45] reported that dopamine and dopamine precursors controlled the development of myopia and axial length in chicken eyes. In some animal experiments, Ashby et al. [46] reported that chickens exposed to sunlight and artificial light (15,000 lux) were less likely to develop myopia. Based on these observations, if indoor lighting can simulate outdoor sunlight, it may be helpful in the control of myopia, which should be further studied.

Consistent with previous results [47, 48], girls had a higher risk of myopia. Due to the effects of growth hormone and estrogen, girls tend to mature earlier than boys in high school, and they undergo puberty earlier than boys [49]. This may be one of the reasons why myopia in girls is higher than that of boys at a particular age. In addition, despite being repeatedly asked to lighten the burden, the academic load and educational pressure of Chinese high school students are still very heavy. Girls also tend to spend more time on close reading and writing and do less outdoor activities. Therefore, the observed correlations may be causal.

Using univariate analysis, compared with students who slept less than 6 h a day, students who slept more than 7 h a day had a lower prevalence of myopia, but this was not statistically significant using multivariate analysis. Liu et al. [50] reported that in children 6–8 years of age, longer sleep duration did not correlate with increased myopia, although “sleeping late” was a risk factor for myopia prevalence at baseline. This may be related to disordering of circadian rhythm caused by sleeping late.

In addition to the above factors that have been widely discussed, we found that classroom seating location had a significant effect on the prevalence of myopia, which has been rarely mentioned in other studies. The prevalence of myopia in the first row of the classroom was the lowest (90.1%), and the prevalence of myopia among students in the seventh row and above was the highest (96.2%). We speculate that the reason for these differences may be related to optical blur. Optical blur may be the signal that causes myopia: this theory is supported by numerous animal studies [51‒54]. For students sitting in the seventh row and higher, longer distances and smaller targets will result in a significant decline in visual quality and may accelerate the development of myopia.

The overall prevalence of myopia among all junior high school students and senior high school students in Nantong was 94%. The prevalence of myopia was even higher than that of some college students in Jiangsu Province the previous year [6]. In students with myopia, most students (67.9%) did not take adjuvant measures to prevent further progression of myopia. Among the students who took adjuvant treatment measures, only a small number used effective adjuvant treatments [18]; 6.8% used low-dose atropine eye drops to control the development of myopia, 3.9% used high-dose atropine eye drops to control the development of myopia, and 0.6% used corneal refractive therapy. A total of 19.8% of the students used traditional Chinese massage (such as Chinese eye exercises) to control myopia, but its effects remain controversial [6, 55]. Nevertheless, in some other areas of China, the prevention and control of myopia has been successful. For example, in Hong Kong, China, the prevalence of myopia in 2020 [56] is likely to decline than the study in 2012 [57]. In a recent clinical trial among 6-year-old children in Guangzhou, China, the incidence of myopia was significantly reduced over the 3 years after the addition of 40 min of outdoor activity to the daily curriculum [13]. When considering that environmental factors play a leading role in myopia [30, 31, 58], some preventive methods should be implemented, such as increasing the time of outdoor activities, making the indoor light closer to that of the outdoors, avoiding late sleep, and using atropine and other effective measures.

There were some potential limitations in the present study. First, the diopters used in this study were measured without cycloplegia, which ensured a high participation rate. In consideration that cycloplegic autorefraction was the preferred method to determine the amount of myopia [20], overestimation may occur in the absence of cycloplegia. Second, the questionnaires were completed by the student and at least one parent. Although this method may be more accurate than with children alone, recall bias may still be unavoidable, and the fact that children may lie in order to look better in the eyes of their parents cannot be ignored.

The results of the present study indicated that factors such as female sex, older age, parental myopia, sitting in the back of the classroom, increased homework time, and low outdoor activity were significantly associated with a higher risk of myopia. In contrast, increased outdoor activity was associated with a decreased risk of myopia. We also found that the prevalence of myopia at 12 years of age was as high as 90.6%, so we should focus on the prevention and control of myopia in primary schools before this age.

We thank Zhang Xiaoya, Lin Liwei, and Lu Xiyu for their contributions in the data collation.

The study was approved by the Human Research Ethics Committee of the Second Affiliated Hospital of Nantong University, China (NO. 2020KT068) and adhered to the Declaration of Helsinki. Informed consent in written form was obtained from all participants and the participants’ guardians for those under 18 years old.

The authors have no conflicts of interest to declare.

Supported by the Nantong Science and Technology Program (project number: MS2020035).

All the authors contributed to the conception of the work by writing sections of the manuscript and drafting and revising it critically as well as final approval of the published version. Yue Zhou, Xiao Bo Huang, Yu Song, and Zhi Min Sun were involved in the design of the study. Ye Xun Gong, Yao Jia Xiong, Qi Cai, and Nan Xi Jin were involved in data collection and data analysis.

The data that support the findings of this study are openly available in Dryad at http://dx.doi.org/10.5061/dryad.k0p2ngf8f.

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