Figure 1 - uploaded by Yingyan Ma
Content may be subject to copyright.
Source publication
Purpose: To evaluate common strategies for screening myopia.
Methods: A total of 2,248 children aged 6 to 12 years from five randomly selected primary schools were included for the screening. Enrolled study participants underwent distant uncorrected visual acuity (UCVA, Standard Logarithmic Visual Acuity E Chart) and non-cycloplegic auto-refraction...
Context in source publication
Context 1
... 1639 children who completed the three tests (UCVA, NCAR and cycloplegic auto-refraction) were included in the analyses for determining the accuracy and the net benefits for the four screening strategies. A 10-fold cross-validation process was used for statistical analyses (Figure 1). The database was randomly divided into 10 groups with 9 groups used for diagnostic model development for the screening strategy and 1 group (validation group) for determining the sensitivity, specificity and the net benefits for the developed model. ...
Citations
... there are some limitations to the present study. First, the noncycloplegic refraction used in this study has high accuracy in myopia screening among children and adolescents [40]. consequently, we could not distinguish between myopia and pseudomyopia using noncycloplegic refraction and may have overestimated the prevalence of myopia [41]. ...
Objectives
To analyze the factors influencing myopia and construct a nomogram to forecast the risk of myopia among school-age children, providing a reference for identifying high-risk groups to aid prevention and control.
Methods
This case-control study enrolled 3512 students from three primary schools in Shenzhen using random cluster sampling for a questionnaire survey, myopia screening and ocular biometric parameter measurement. Logistic regression was used to analyze the influencing factors of myopia, and a nomogram was constructed to forecast myopia risk. Bootstrap resampling was used to verify the practicability of the nomogram.
Results
Older age (odds ratio[OR] = 1.164; 95% confidence interval [CI]: 1.111–1.219), female sex (OR = 2.405; 95% CI: 2.003–2.887), maternal myopia (OR = 1.331; 95% CI: 1.114–1.589), incorrect posture during reading and writing (OR = 1.283; 95% CI: 1.078–1.528) and axial length (OR = 7.708; 95% CI: 6.044–8.288) are risk factors for myopia, whereas an increase in corneal radius (OR = 0.036; 95% CI: 0.025–0.052) is a protective factor against myopia. The area under the receiver operating characteristic (ROC) curve of the nomogram was 0.857, and the net benefit was high when the risk threshold of the decision curve analyses (DCA) ranged from 0.20 to 1.00. The measured values were consistent with the prediction.
Conclusion
The nomogram was accurate in predicting the risk of myopia among schoolchildren. This study provides a reference for screening high-risk students and for individualized myopia prevention and control.
... Rights reserved www.nature.com/scientificreports/ benefits for myopia screening41 . In the future, strategies are required to rapidly exclude the influence of accommodative spam. ...
This cross-sectional study aims to investigate the prevalence and causes of visual impairment (VI) and blindness in Jiangsu Province, China in 2022 during the COVID-19 pandemic. Participants (n = 13,208, aged 18–93) underwent comprehensive ocular examinations. The prevalence and causes of binocular VI (presenting visual acuity [VA] ≥ 20/400 and < 20/63 in the better eye) and blindness (presenting VA < 20/400 in the better eye) were assessed according to the World Health Organization (WHO) criteria. The estimation of refractive error prevalence was conducted using the following classification: myopia ≤ − 0.50 diopters (D), high myopia ≤ − 6.00 D, hyperopia ≥ 0.50 D, and anisometropia ≥ 1.00 D. The overall prevalence of binocular VI and blindness was 21.04% (95% confidence interval [CI] 20.35–21.74%) and 0.47% (95% CI 0.37–0.60%). The highest prevalence of binocular VI was in the population aged 18–24 years old (46.29%, [95% CI 44.30–48.28%]), those with education at university and above (43.47%, [95% CI 41.93–45.02%]), students (54.96%, [95% CI 52.73–57.17%]). Uncorrected refractive error (URE) was the leading cause of presenting binocular VI (93.40%) and blindness (50.79%). The prevalence of myopia was 54.75% (95% CI 53.90–55.60%). Actions are needed to control URE and myopia within the adult Chinese population, with a particular emphasis on the younger, well-educated demographic.
... The combination of UCVA and NCAR can achieve a better accuracy with increasing sensitivity and specificity [11,12,17]. However, UCVA is subject to variability between examination conditions, instruments and examiner performance [18] while NCAR could lead to a more myopic SE and the difference varies with age, SE and AL, due to the accommodation response [19]. ...
... Our Youden Index of the combination of AL/CR ratio and NCAR, and the combination of AL and NCAR (0.82 and 0.81 for 3-to 5-year-olds) were greater than that of the combination of UCVA and NCAR reported in one study (0.71 for ≤ 4-year-olds) [12], and resembled that reported in another study (0.84 for 4-to 6-year-olds) from the same data set as ours [17]. While UCVA and NCAR measurements are more accessible and can be quickly grasped by non-specialists after training, UCVA measurements could vary with ambient light, the skill of the technicians, and participants' cooperativeness [18]. In this regard, AL and CR measurements are more objective with higher accuracy, which is more suitable for dynamic long-term follow-up [20]. ...
Purpose
To investigate the effectiveness and cutoffs of axial length/corneal radius (AL/CR) ratio for myopia detection in children by age.
Methods
Totally, 21 kindergartens and schools were enrolled. Non-cycloplegic autorefraction (NCAR), axial length (AL), horizontal and vertical meridian of corneal radius (CR1, CR2), and cycloplegic autorefraction were measured. Receiver operating characteristic (ROC) curve was used to obtain the effectiveness and cutoff for myopia detection.
Results
Finally, 7803 participants aged 3–18 years with mean AL/CR ratio of 2.99 ± 0.16 were included. Area under the ROC curve (AUC) of AL/CR ratio for myopia detection (0.958 for AL/CR1, 0.956 for AL/CR2, 0.961 for AL/CR) was significantly larger than that of AL (0.919, all P < 0.001), while AUCs of the three were similar with different cutoffs (> 2.98, > 3.05, and > 3.02). When divided by age, the ROC curves of AL/CR ratio in 3- to 5-year-olds showed no significance or low accuracy (AUCs ≤ 0.823) in both genders. In ≥ 6-year-olds, the accuracies were promising (AUCs ≥ 0.883, all P < 0.001), the cutoffs basically increased with age (from > 2.93 in 6-year-olds to > 3.07 in 18-year-olds among girls, and from > 2.96 in 6-year-olds to > 3.07 in 18-year-olds among boys). In addition, boys presented slightly larger cutoffs than girls in all ages except for 16 and 18 years old. For children aged 3–5 years, AL/CR ratio or AL combined with NCAR increased AUC to > 0.900.
Conclusion
AL/CR ratio provided the best prediction of myopia with age-dependent cutoff values for all but preschool children, and the cutoffs of boys were slightly larger than those of girls. For preschool children, AL/CR ratio or AL combined with NCAR is recommended to achieve satisfactory accuracy. AL/CR ratio calculated by two meridians showed similar predictive power but with different cutoffs.
... Lin et al. 57 compared four screening strategies for detecting myopia: (1) cycloplegic autorefraction, (2) noncycloplegic autorefraction, (3) distance uncorrected visual acuity and (4) combined uncorrected visual acuity and non-cycloplegic autorefraction. Not surprisingly, (1) and (4) gave the best sensitivity although distance uncorrected visual acuity gave reasonable sensitivity (58%) and excellent specificity (94%). ...
Purpose
Myopia prevalence is increasing in the UK in teenagers, but little is known about younger children. We hypothesise that if the “myopia epidemic” is affecting young children, there will be increasing prevalence of bilateral reduced unaided vision (V) at vision screening at age 4-5y.
Methods
Retrospective anonymised data from computerised vision screening at age 4-5 years were analysed in a serial cross-sectional study. Refractive error is not assessed in UK vision screening, so vision was investigated. Data were only included from schools that screened every year from 2015/16 to 2021/22. The criterion used was unaided LogMAR vision >0.2 in each eye. In selecting this criterion, we aimed to maximise the chances of detecting myopia. Use of >0.2 cut-off in each eye reduces the risk of including amblyopes but excludes unilateral myopia and bilateral low myopia. The decision not to set a maximum inter-ocular difference criterion has the advantage of including aniso-myopes but also includes some amblyopes with reduced vision in each eye from hyperopia/astigmatism.
Results
Anonymised raw data were obtained for 336,649 screening episodes from 2,075 schools. Once schools were excluded for which data were not available for every year and data were cleaned, the final database comprised 110,076 episodes. The proportion (%) failing the criterion from 2015/16 to 2021/22 are 7.6, 8.5, 7.5, 7.8, 8.7, 8.5 and 9.3 respectively. A linear trendline shows increasing prevalence of reduced bilateral unaided vision, consistent with increasing prevalence of myopia (Cochrane-Armitage test, p<0.0001). A decreasing linear trendline was noted for children Under Professional Care.
Conclusions
At the young age of 4-5 years, there are signs of reducing vision in the UK over the last 7 years. Consideration of the most likely causes support the hypothesis of increasing myopia. The increase in screening failures highlights the importance of eyecare in this young population.
... Lin et al (2019) compared four screening strategies for detecting myopia: (1) cycloplegic auto-refraction, (2) non-cycloplegic autorefraction, (3) distance uncorrected visual acuity, and (4) combined uncorrected visual acuity and non-cycloplegic autorefraction. 57 Not surprisingly, (1) and (4) gave best sensitivity although distance uncorrected visual acuity gave reasonable sensitivity (58%) and excellent specificity (94%). Indeed, the ease and low cost of visual acuity testing probably explains why most studies that have screened for myopia have relied on visual acuity testing. ...
Purpose:
Myopia prevalence has increased in the UK at age 10-16y, but little is known about younger children. We hypothesise that if the 'myopia epidemic' is affecting young children, then there will be increasing rates of bilateral reduced unaided vision (V) at vision screenings of children 4-5 years of age.
Methods:
Retrospective anonymised data from computerised vision screening at age 4-5 years were analysed from serial cross-sectional data. Refractive error is not assessed in UK vision screening, so vision was investigated. Data were only included from schools that screened every year from 2015/16 to 2021/22. The criterion used was unaided monocular logMAR (automated letter-by-letter scoring) vision >0.20 in both the right and left eyes, so as to maximise the chances of detecting bilateral, moderate myopia rather than amblyopia.
Results:
Anonymised raw data were obtained for 359,634 screening episodes from 2075 schools. Once schools were excluded where data were not available for every year and data were cleaned, the final database comprised 110,076 episodes. The proportion (percentage and 95% CI) failing the criterion from 2015/16 to 2021/22 were 7.6 (7.2-8.0), 8.5 (8.1-8.9), 7.5 (7.1-7.9), 7.8 (7.4-8.2), 8.7 (8.1-9.2), 8.5 (7.9-9.0) and 9.3 (8.8-9.7), respectively. The slope of the regression line showed a trend for increasing rates of reduced bilateral unaided vision, consistent with increasing frequency of myopia (p = 0.06). A decreasing linear trendline was noted for children 'Under Professional Care'.
Conclusions:
For children 4-5 years of age, there were signs of reduced vision over the last 7 years in England. Consideration of the most likely causes support the hypothesis of increasing myopia. The increase in screening failures highlights the importance of eye care in this young population.
... Therefore, many studies use noncycloplegic refraction to conduct myopia screening. Studies have confirmed the sensitivity and specificity of myopia screening in children aged 6-12 years (85.06% and 89.74%, respectively) who underwent a combination of distant uncorrected visual acuity and non-cycloplegic auto-refraction (57). Second, all the risk factor data in the present study were obtained from a questionnaire, which was subjective. ...
Objectives: To study the epidemiological characteristics and influencing factors of myopia to provide a scientific basis for the prevention and control of myopia.
Methods: 7,597 students studying in grades 1–3 were followed up. Eye examinations and questionnaire surveys were conducted annually from 2019 to 2021. The influencing factors of myopia were analyzed by logistic regression model.
Results: The prevalence of myopia among students in grades 1–3 in 2019 was 23.4%, which increased to 41.9% and 51.9% after the 1-and 2-year follow-up, respectively. The incidence of myopia and change in the spherical equivalent refraction (SER) were higher in 2020 than in 2021. The 2-year cumulative incidences of myopia were 2.5%, 10.1%, 15.5%, 36.3%, and 54.1% in students with a baseline SER >+1.50D, +1.00D to +1.50D, +0.50D to +1.00D, 0.00D to +0.50D, and -0.50D to 0.00D, respectively. Outdoor activities, sex, age, baseline SER, parental myopia, sleep time, and digital device exposure were associated with myopia.
Conclusion: The prevalence of myopia demonstrated a rapid increase; thus, healthy habits and outdoor activities should be promoted for the prevention and control of myopia.
... SE equals diopter of spherical power (DS) plus 1/2 diopter of cylindrical power (DC). Students exhibiting either of two conditions were judged to be myopic: (a) those wearing orthokeratology lenses or (b) those having a mean uncorrected visual acuity (UCVA) <5.0 and a mean SE < −0.50D (20). In addition, high myopia was defined as having an SE ≤ −6.00 D (21). ...
Objectives
To investigate myopia progression and associated factors of refractive status among children and adolescents in Tibet and Chongqing in China during the COVID-19 pandemic.
Methods
A population-based cross-sectional study was conducted to compare rates of myopia and high myopia, axial length (AL), spherical equivalent (SE), outdoor activity time, digital device use, and frequency of visual examinations for children and adolescents affected by myopia in Chongqing and Tibet in 2021.
Results
A total of 2,303 students from Chongqing and 1,687 students from Tibet were examined. The overall prevalence of myopia and high myopia in these two groups were 53.80 and 7.04% vs. 43.86 and 1.30%, respectively in each case. The Chongqing students had a longer AL than the group from Tibet (23.95 vs. 23.40 mm, respectively; p < 0.001). The mean SE of the students with myopic parents in Tibet was lower than that of the students in Chongqing with myopic parents (−2.57 ± 2.38 diopters (D) vs. −2.30 ± 2.34 D, respectively) (p < 0.001). Conversely, the mean SE of the students from urban areas in Chongqing was lower than that of the students in Tibet (−2.26 ± 2.25 D vs. −1.75 ± 1.96 D, respectively; p < 0.001). The Chongqing students exhibited lower SE (−2.44 ± 2.22 D) than their Tibetan counterparts (mean SE: −1.78 ± 1.65 D (p = 0.0001) when spending more than 2.5 h outdoors. For example, 61.35% of the students in Tibet spent more than 2.5 h outdoors daily, compared with 43.04% of the students in Chongqing. Correspondingly, the proportion of students using digital devices in Tibet (64.43%) was lower than that in Chongqing (100%). For the latter, 38.62% of the students in Chongqing spent more than 2.5 h online using digital devices compared to 10.49% of the students in Tibet. Greater monitoring of visual status was observed for the Chongqing students (mean SE: −1.90 ± 1.98 D) compared with students in Tibet (mean SE: −2.68 ± 1.85 D) (p = 0.0448), with the frequency of optimal examinations being every 6 months. Outdoor activity time was identified as a common risk factor for myopia in both of the populations examined, with odds ratios (ORs) of 1.84 (95% CI: 1.79–1.90) in Chongqing and 0.84 (95% CI: 0.73–0.96) in Tibet. Digital screen time was associated with myopia and high myopia in Chongqing, with ORs of 1.15 (95% CI: 1.08–1.22) and 1.06 (95% CI: 0.94–1.77), respectively. Digital screen time was also found to be a risk factor for high myopia in Tibet (OR: 1.21, 95% CI: 0.77–1.61). The type of digital devices used was also associated with myopia and high myopia in Tibet (OR: 1.33, 95% CI: 1.06–1.68 and OR: 1.49, 95% CI: 0.84–2.58, respectively). Finally, examination frequency was found to correlate with high myopia in the Tibet group (OR: 1.79, 95% CI: 0.66–2.71).
Conclusion
Based on our data, we observed that the prevalence of refractive errors in children and adolescents was significantly lower in Tibet than in Chongqing. These results are potentially due to prolonged outdoor activity time, and the type and time of use for digital devices that characterize the group of children and adolescents from Tibet. It is recommended that parents and children in Chongqing would benefit from increased awareness regarding myopia progression and its prevention.
... In the setting of vision screening, myopia is defined as a noncycloplegic SER <−0.50 D with an uncorrected distant VA on the Snellen chart of <20/20 in at least one eye. 14 15 Considering the involuntary accommodation in NCAR, the vision acuity criterion is used combined with refraction to avoid mistaken identification of instrument myopia as myopia. Instrument myopia was defined as a non-cycloplegic SER of <−0.50 D with an UCVA of not less than 20/20 in both eyes. ...
... 20 Besides shifting the NCAR SER cutoff more myopic, 12 another method to avoid overmeasure of myopia is adopting the combined criteria of SER and UCVA, 7 which has been proven with the highest net benefits for myopia screening. 15 Myopia prevalence was significantly higher in urban areas. 21 In recent years, China has been undergoing dramatic economic development and urbanisation, bringing about environmental risk factors such as exposure to air pollution, increasing intense educational pressure, near work and reduced outdoor activity, which are known to be associated with myopia. ...
Aims
To explore the prevalence and risk factors for myopia and uncorrected myopia in schoolchildren in southern China.
Methods
The government-led Shantou Myopia Study was conducted from September 2020 to June 2021. Non-cycloplegic refraction was performed. Uncorrected visual acuity (UCVA) was measured along with presenting visual acuity if participants wore spectacles. Spherical equivalent refraction (SER) is defined as the spherical dioptres added to half of the cylindrical dioptres. Myopia is defined as SER <−0.50 dioptre with UCVA of <20/20 in at least one eye.
Results
This study enrolled 724 828 schoolchildren (77.8% of all schoolchildren in Shantou) from 901 schools. Data from 721 032 schoolchildren (99.5%) were analysed (mean age 11.53±3.13 years, 6–20 years, 373 230 boys and 347 802 girls). Among them, 373 459 (51.8%) had myopia: 37.1% of 465 696 children in primary schools, 75.4% of 170 164 children in junior high schools and 84.8% of 85 172 children in senior high schools. The prevalence of myopia increases non-linearly with age. Older age, female and urban living environment were independently associated with myopia prevalence and myopic SER. Among the 373 459 children with myopia, 60.0% had no refractive correction: 74.9%, 53.9% and 35.5% in primary, junior high and senior high schools, respectively.
Conclusion
The overall prevalence of myopia among schoolchildren in Shantou was 51.8%, higher than the national average in China. The proportion of uncorrected myopia is high, especially in primary schools. Our results indicate the need for public education on eye care among schoolchildren even in a municipal city.
... In our study, myopia was defined as UCVA (logMAR) < 5.0 and SER of � −0.50 dioptres (D) in either eye [18,19], or receiving corneal refractive therapy, such as wearing ortho-K lenses. The following categories of myopia were designated: mild myopia (� -0.50 D to >-3.00 D), moderate myopia (�−3.00D to >-6.00 D), and high myopia (� −6.00 D) [20]; other conditions were defined as nonmyopia. ...
Purpose:
The aim of this study was to investigate the change of myopic prevalence in students with different demographic characteristics before and after the COVID-19 pandemic in Suqian, China.
Methods:
A retrospective, cross-sectional study was conducted. Student data from 52 schools in 2019 and 2020 were collected from the electronic medical records database through cluster sampling. Ophthalmic examinations were conducted on students from September to December in 2019 and 2020. Measurements of uncorrected visual acuity (UCVA) and noncycloplegic autorefraction were included to obtain the spherical equivalent refraction (SER) and prevalence of myopia. The difference in the rate of myopia and SER of students ages 6 to 18 with various demographic characteristics was compared between the two years.
Results:
Records from 118,479 students in 2019 and the 121,881 students in 2020 were obtained. In 2019 and 2020, the prevalence of overall myopia increased from 43.1% to 48.9% (5.8 percentage point), and a substantial shift in myopic rate occurred in grades 4 to 6 (6.9 percentage point). The change in the prevalence of myopia in girls (5.9 percentage point) was approximately equal to that in boys (5.8 percentage point) and it was more common in rural students (5.9 percentage point) than in urban students (5.1 percentage point). The prevalence of low myopia increased more in children, and the prevalence of moderate myopia increased more in adolescents. The mean spherical equivalent refraction (SER) (-1.34±2.03 D) was lower in 2020 than in 2019 (-1.16±1.92 D), while SER decreased mainly at ages 7 to 15. The SER presented myopic status at the age of 9 (-0.55±1.26 D in 2019, -0.71±1.42 D in 2020), and attained moderate myopia at the age of 15 (-3.06±2.41 D in 2019, -3.22±2.40 D in 2020).
Conclusions:
After the COVID-19 pandemic, myopia increased in this population with variable rates of increase in different demographic groups. The change of myopia in children was comparatively greater than that in adolescents. Therefore, we should take measures to prevent and control the development of myopia after the COVID-19 pandemic, especially for younger students.
... Variables Prediction accuracy curves of random forest models in five study years, that is, the accumulated percentage of samples as a function of the absolute difference between predicted and actual spherical equivalent refractions and myopia screening [31]. This implies that UDVA of primary school children should be monitored frequently to identify children at risk of myopia. ...
Introduction:
To investigate the risk factors for myopia progression in primary school children and build prediction models by applying machine learning to longitudinal, cycloplegic autorefraction data.
Methods:
A total of 2740 children from grade 1 to grade 6 were examined annually over a period of 5 years. Myopia progression was determined as change in cycloplegic autorefraction. Questionnaires were administered to gauge environmental factors. Each year, risk factors were evaluated and prediction models were built in a training group and then tested in an independent hold-out group using the random forest algorithm.
Results:
Six variables appeared in prediction models on myopia progression for all 5 years, with combined weight of 77% and prediction accuracy over 80%. Uncorrected distance visual acuity (UDVA) had the greatest weight (mean 28%, range 22-39%), followed by spherical equivalent (20%, 7-28%), axial length (13%, 10-14%), flat keratometry reading (K1) (7%, 4-11%), gender (6%, 2-9%), and parental myopia (3%, 1-10%). UDVA and spherical equivalent had peak weight at the second and third study years, respectively. The weight of myopic parents decreased steadily over the 5 years (9.5%, 1.9%, 1.8%, 1%, and 1.3%). Weekly time spent reading, reading distance, reading in bed, and frequency of eating meat were included as variables in different study years.
Conclusions:
Myopia progression in children was predicted well by machine learning models. UDVA and spherical equivalents were good predictive factors for myopia progression in children through primary school. Parental myopia was found to play a substantial role in the early stage of myopia progression but waned as children grew older.
