Optimising Non-Cycloplegic Screening Strategies for Early Detection of Pre-Myopia and Myopia in Young Children

Purpose: Early detection of myopia is essential to delay its onset and progression. Pre-myopia, defined by an inadequate hyperopic reserve, increases myopia risk in childhood. However, effective screening methods remain limited. This study aimed to develop practical non-cycloplegic screening methods for pre-myopia and myopia in 6- to 7-year-olds to support earlier interventions. Methods: This cross-sectional study of 621 Irish schoolchildren (mean age: 7.12 ± 0.45 years; 51.8% boys) assessed uncorrected distance visual acuity (UDVA). Cycloplegic spherical equivalent refraction (SER) classified refractive status (myopia: SER ≤ −0.50D; pre-myopia: SER \u3e −0.50 ≤ 0.75D). Pre- and post-cycloplegic SER were measured using the Welch Allyn Spot Vision Screener and Dong-Yang Rekto-ORK 11, respectively. Axial length (AL) and corneal radius (CR) were measured with the Zeiss IOLMaster, and parental myopia history was measured via questionnaire. Logistic regression and ROC curves evaluated non-cycloplegic screening methods. Results: Pre-myopia prevalence was 24.3% (95% confidence intervals (CIs): 29.3–36.2), and myopia prevalence was 3.3% (CI: 2.5–5.5). UDVA screening had an area under the curve (AUC) (CI) = 0.72 (0.59–0.86) and 0.42 (0.36–0.47) for detecting myopia and pre-myopia, respectively. For pre-myopia discrimination, non-cycloplegic SER, AL, AL/CR and parental myopia had AUCs of 0.67 (0.62–0.72), 0.67 (0.62–0.72), 0.69 (0.64–0.74) and 0.59 (0.53–0.64), respectively. The best method combined non-cycloplegic SER and AL/CR (AUC = 0.72 (0.67–0.76)). Including UDVA or parental myopia did not improve results. For myopia detection, AUCs were non-cycloplegic SER: SER:0.84 (0.72–0.97), AL: 0.88 (0.82–0.95), AL/CR: 0.84 (0.75–0.94) and parental myopia: 0.62 (0.48–0.75). The best method combined AL and non-cycloplegic SER 0.94 (0.90–0.99). Adding parental myopia did not improve the AUC = 0.93 (0.87–0.99), but adding UDVA achieved an AUC = 0.95 (0.90–0.99). Conclusion: While UDVA alone provided acceptable discrimination for myopia, it was insufficient for screening pre-myopia. Non-cycloplegic SER alone had relatively poor discrimination for pre-myopia, but its performance improved when combined with the AL/CR ratio. The best results for myopia discrimination were achieved by combining non-cycloplegic SER, axial length and UDVA measures

Axial Length Growth Trajectories in Children Transitioning to Myopia

Purpose To characterize axial length (AL) growth trajectories in children who developed myopia compared with children who remained non-myopic. Design Retrospective longitudinal cohort study. Participants Clinical data from 895 Chinese children (aged 4-15 years at baseline) with non-myopic refractive error (spherical equivalent refraction [SER] > –0.50D) at baseline spanned at least 2 years. They were categorized into non-myopic (n = 541) and incident myopia (n = 354) groups, based on whether they developed myopia (SE ≤ –0.50D) during follow-up. Children in the incident myopia group contributed data to both pre-myopia onset and post-myopia onset stages. Methods Right eye data were used for all analyses. Participants were classified as myopic based on the right eye’s SER, regardless of the left eye status. AL was measured at multiple visits, and the rate of AL growth between visits calculated. Generalized estimating equations (GEE) were used to model AL growth rate, accounting for within-subject correlations. Age, baseline AL, gender, and parental myopia were included as predictors in the model. Main Outcome Measures Annual AL growth rate (mm/year). Results GEE modeling revealed significant differences in AL growth rates; children in the post-myopia onset stage exhibited significantly faster AL growth compared to both the children in the pre-myopia onset stage and non-myopic group (p < 0.001). This difference was most pronounced in younger children and diminished with age. Post-myopia onset AL growth was significantly faster than pre-myopia onset growth up to age 7 and the non-myopic group up to age 10 (p < 0.05). All groups showed an age-related decline in AL growth rate, with the decline being most pronounced in children in the post-myopia onset stage, followed by the non-myopic group, and then children in the pre-myopia onset stage Baseline AL was significantly associated with post-myopia onset AL growth rate (p < 0.001) but not with pre-myopia onset (p = 0.22) or non-myopic (p = 0.07) growth rates. Neither gender nor parental myopia significantly impacted AL growth rate. Conclusions AL growth accelerates significantly after myopia onset, particularly in children younger than 10. This underscores the need for prompt myopia control interventions in early-onset myopia

Establishment of noncycloplegic methods for screening myopia and pre-myopia in preschool children

PurposePre-myopia, a non-myopic refractive state, is a key concern for myopia prevention because of its association with a significantly higher risk of myopia in children under 3 years of age. Amid the myopia pandemic, its onset at younger ages is increasing, yet research on screening methods for myopia and pre-myopia in preschool children remains limited. This study aimed to establish effective noncycloplegic screening methods for myopia and pre-myopia in preschool children.MethodsThis cross-sectional study included 16 kindergartens in Shanghai, China. Uncorrected distance visual acuity (UDVA) was recorded using a logMAR visual acuity chart. Pre- and post-cycloplegic refractions were obtained using an auto-refractor (TopconKR-800). Noncycloplegic axial length (AL) and corneal curvature radius (CR) were measured using the IOL Master-700. Logistic regression models were developed to establish accurate noncycloplegic screening methods for myopia and pre-myopia.ResultsA total of 1,308 children with a mean age of 4.3 ± 0.9 years were included; among them 640 (48.9%) were girls. The myopia prevalence rate was 2.8% (n = 36), and the prevalence of pre-myopia was 21.9% (n = 286). Pre-myopia screening (cycloplegic spherical equivalent [SE] ≤ −0.5 < SE ≤0.75 diopters [D]) using UDVA exhibited an area under the receiver operating curve (AUC) of 0.52, noncycloplegic SE had an AUC of 0.70 and AL had an AUC of 0.63. The accuracy of combining the SE and AL/CR ratio was among the best with the least number of checks used, and the AUC was 0.74 for pre-myopia screening and 0.94 for myopia screening (cycloplegic SE ≤ −0.5 D). The addition of UDVA did not further improve the accuracy.ConclusionUsing UDVA alone did not achieve good accuracy in pre-myopia or myopia screening of young children. Under non-cycloplegic conditions, the combination of AL/CR and SE demonstrated favorable results for pre-myopia and myopia screening of preschool children

Analysis of risk factors associated with pre-myopia among primary school students in the Mianyang Science City Area

Objectives To find out the prevalence rate of pre-myopia among primary school students in the Mianyang Science City Area, analyze its related risk factors, and thus provide a reference for local authorities to formulate policies on the prevention and control of myopia for primary school students. Methods　 October 2022, Cluster sampling was adopted by our research group to obtain the vision levels of 2278 primary school students employing a diopter test in the Science City Area. In addition, questionnaires were distributed to help us find the risk factors associated with pre-myopia. Results The prevalence rate of pre-myopia among primary school students in the Science  City Area was 45.27%, of which 43.82% were boys and 46.92% were girls, with no statistically significant difference in the prevalence rate of myopia between boys and girls (c2 =2.171, P=0.141). Multiple logistic regression analysis demonstrated that the main risk factors for pre-myopia were having at least one parent with severe myopia, spending less than 2 hours a day outdoors, lack of sleep looking at electronic screens for more than 1 hours, and having an improper reading and writing posture. Outdoor activity time less than 2 hours per day, lack of sleep, looking at the electronic screen for more than 1 hour per day, and incorrect reading and writing posture were all positively associated with the pre-myopia (P values < 0.05). Conclusion The Science City Area has a high prevalence rate of pre-myopia among primary school students. It is proposed that students, schools, families, and local authorities work together to increase the time spent outdoors, get adequate sleep, reduce the time spent staring at digital screens and develop scientific use of eye habits

A study on the status of myopia and pre-myopia among primary school students in different regions of Shaanxi Province, China

ObjectiveThis cross-sectional study aimed to investigate the geographic disparities in myopia and pre-myopia prevalence among elementary school students across three distinct regions of Shaanxi Province (southern Hanzhong, Guanzhong, and northern Yulin) to inform region-specific myopia control strategies.MethodsFrom March to May 2024, we employed multistage cluster sampling to recruit 8,207 eligible students (2,724 southern Shaanxi, 2,761 Guanzhong, 2,722 northern Shaanxi) from 12 randomly selected primary schools. Comprehensive ophthalmic examinations including uncorrected visual acuity and non-cycloplegic autorefraction were conducted. Continuous variables were expressed as mean ± standard deviation, while categorical variables were analyzed using chi-square tests.ResultsAge-standardized myopia prevalence was highest in northern Shaanxi (48.02%), followed by central Shaanxi/Guanzhong (42.96%) and southern Shaanxi (30.43%). Gender disparities persisted across all regions, with female students exhibiting significantly elevated myopia rates (southern Shaanxi: 34.00% vs. 26.91%; Guanzhong: 48.02% vs. 37.99%; northern Shaanxi: 52.54% vs. 44.13%; P &lt; 0.05 for all comparisons). Pre-myopia prevalence displayed an inverse geographic pattern (southern Shaanxi: 40.60% &gt; Guanzhong: 34.19% &gt; northern Shaanxi: 33.73%; χ2 = 185.3, P &lt; 0.001), with male students consistently showing higher pre-myopia detection rates than females (southern Shaanxi: 42.45% vs. 38.73%; Guanzhong 38.28% vs. 30.01%; northern Shaanxi: 37.64% vs. 29.17%; P &lt; 0.05). A marked grade-level progression was observed, with myopia prevalence increasing annually while pre-myopia rates declined significantly.ConclusionOur findings reveal a north–south gradient in ocular health outcomes, with northern Shaanxi demonstrating concerningly high myopia prevalence coupled with reduced pre-myopia detection rates. The persistent female predominance in myopia burden and early detection gaps underscores the need for gender-sensitive interventions. The observed progression patterns suggest critical windows for prevention, advocating for: (1) Preschool-initiated vision protection programs, (2) Establishment of digital refractive registries for high-risk cohorts, and (3) Implementation of regionally tailored myopia control protocols prioritizing northern districts

Factors predicting myopia incidence in China and Europe

Aims: To develop a predictive model for myopia incidence using population-based data from Chinese and European children. Methods: Analysis of four longitudinal studies from the UK, Sweden and China was conducted. Data from 4405 non-myopic children aged 6 to 16.8 years with spherical equivalent (SE) refraction from −0.49 D to +10.00 D were analysed. Kaplan–Meier and Cox proportional hazard models were used to evaluate the probability of myopia incidence by 12 and 24 months based on age, sex, parental myopia, cycloplegic SE, axial length and axial length/corneal radius of curvature (AL/CR). Hyperopic reserve was defined as the minimum level of hyperopia required to provide &lt;10% probability of developing myopia by 24 months. Results: The cumulative incidence of myopia by the 24th month was 18.8% for Chinese and 6.7% for European (p &lt; 0.001) populations. Based on multivariate Cox regression, a greater risk of myopia incidence was seen in Chinese children, younger ages, females, children with parental myopia, less hyperopic SE and higher AL/CR. SE had the highest predictive accuracy (C statistic 0.90). The AL/CR ratio had a greater predictive accuracy (C statistic 0.75) than axial length alone (C statistic 0.63). Predictive accuracy of all variables was similar between ethnicities (p &gt; 0.50) apart from axial length, which was higher in Chinese children (C statistic 0.65) versus European children (C statistic 0.55, p = 0.04). To avert the risk of myopia, Chinese eyes required a greater hyperopic reserve ranging from 0.5 to 1.5 D compared to European eyes ranging from 0 to 0.5 D, depending on age and other predictive factors. Conclusions: SE is the strongest predictive factor for both ethnicities. The influence of predictive factors is similar between ethnicities/regions though Chinese children have a greater risk of developing myopia and require a higher hyperopic reserve. These data could be useful for developing a predictive tool of myopia incidence.</p