Regional variations and temporal trends of childhood myopia prevalence in Africa: A systematic review and meta-analysis

Smart Devices in Optometry: Current and Future Perspectives to Clinical Optometry

There is a huge unmet need for eye care with more than a hundred million people living without basic eye care services and facilities. There is an exigency to deploy adequate resources in terms of manpower and equipment to address this. The usage of smart devices in optometry and eye care practice has been gaining momentum for last half a decade, due to the COVID-19 pandemic and technological advancements in telemedicine. These smart devices will help facilitate remote monitoring of important visual functions, ocular signs and symptoms, thus providing better eye care services and facilities and promoting outreach services. Smart devices in optometry exist in the form of gadgets that can be worn in the wrist, and spectacle-mounted or head-mounted devices. On the other hand, with the ubiquitous nature of smartphones, a large number of smartphone applications have been developed and tested for advanced optometry and primary eye care practice, which may potentially reduce the burden of inadequate resources and the unmet need for eye care. This article aims to give an overview of the current trends and future perspectives on the application of such smart devices in optometric practice.

Refractive Errors, Amplitude of Accommodation, and Myopia Progression in Kazakhstani Medical Students: 5-Year Follow-Up

Background/Objectives: this longitudinal study aimed to investigate the refractive errors, the amplitude of accommodation, and myopia progression in Kazakhstani medical students as they progressed from the first to the fifth course of their studies. Methods: A total of 696 students from Semey Medical University underwent non-cycloplegic and cycloplegic autorefraction in the first course, and 655 were available for examination in the fifth year of study. The amplitude of accommodation was measured before the instillation of cycloplegics using the push-up and push-down methods. A self-administered questionnaire was applied to evaluate the risk factors associated with myopia progression. Results: In the first course, the median spherical equivalent was -0.75 Diopters before cycloplegia and -0.25 Diopters after cycloplegia. In the fifth course, it constituted -1.125 Diopters before cycloplegia and -0.5 Diopters after cycloplegia. The proportion of students with myopia following cycloplegic refraction increased from 44.7% in the first course to 47.5% in the fifth course. The proportion of emmetropic students declined from 31.5% to 30.3%, and hyperopia decreased from 23.8% to 16.8%. The dioptric power of accommodative excess increased from 0.375 in the first year to 0.50 in the fifth year. The hours spent on near-work activities, such as reading books, writing, working at a computer, and using a mobile device, were significantly associated with a myopia progression of ≥0.5 Diopters. Conclusions: the findings of this study suggest implications for public health policy and educational practice.

The optimal atropine concentration for myopia control in Chinese children: a systematic review and network Meta-analysis

AIM

To figure out whether various atropine dosages may slow the progression of myopia in Chinese kids and teenagers and to determine the optimal atropine concentration for effectively slowing the progression of myopia.

METHODS

A systematic search was conducted across the Cochrane Library, PubMed, Web of Science, EMBASE, CNKI, CBM, VIP, and Wanfang database, encompassing literature on slowing progression of myopia with varying atropine concentrations from database inception to January 17, 2024. Data extraction and quality assessment were performed, and a network Meta-analysis was executed using Stata version 14.0 Software. Results were visually represented through graphs.

RESULTS

Fourteen papers comprising 2475 cases were included; five different concentrations of atropine solution were used. The network Meta-analysis, along with the surface under the cumulative ranking curve (SUCRA), showed that 1% atropine (100%)>0.05% atropine (74.9%) >0.025% atropine (51.6%)>0.02% atropine (47.9%)>0.01% atropine (25.6%)>control in refraction change and 1% atropine (98.7%)>0.05% atropine (70.4%)>0.02% atropine (61.4%)>0.025% atropine (42%)>0.01% atropine (27.4%)>control in axial length (AL) change.

CONCLUSION

In Chinese children and teenagers, the five various concentrations of atropine can reduce the progression of myopia. Although the network Meta-analysis showed that 1% atropine is the best one for controlling refraction and AL change, there is a high incidence of adverse effects with the use of 1% atropine. Therefore, we suggest that 0.05% atropine is optimal for Chinese children to slow myopia progression.

Study of myopia progression and risk factors in Hubei children aged 7-10 years using machine learning: a longitudinal cohort

BACKGROUND

To investigate the trend of refractive error among elementary school students in grades 1 to 3 in Hubei Province, analyze the relevant factors affecting myopia progression, and develop a model to predict myopia progression and the risk of developing high myopia in children.

METHODS

Longitudinal study. Using a cluster-stratified sampling method, elementary school students in grades 1 to 3 (15,512 in total) from 17 cities in Hubei Province were included as study subjects. Visual acuity, cycloplegic autorefraction, and height and weight measurements were performed for three consecutive years from 2019 to 2021. Basic information about the students, parental myopia and education level, and the students' behavioral habits of using the eyes were collected through questionnaires.

RESULTS

The baseline refractive errors of children in grades 1 ~ 3 in Hubei Province in 2019 were 0.20 (0.11, 0.27)D, -0.14 (-0.21, 0.06)D, and - 0.29 (-0.37, -0.22)D, respectively, and the annual myopia progression was - 0.65 (-0.74, -0.63)D, -0.61 (-0.73, -0.59)D and - 0.59 (-0.64, -0.51)D, with the prevalence of myopia increasing from 17.56%, 20.9%, and 34.08% in 2019 to 24.16%, 32.24%, and 40.37% in 2021 (Χ2 = 63.29, P < 0.001). With growth, children's refractive error moved toward myopia, and the quantity of myopic progression gradually diminished. (F = 291.04, P = 0.027). The myopia progression in boys was less than that in girls in the same grade (P < 0.001). The change in spherical equivalent refraction in myopic children was smaller than that in hyperopic and emmetropic children (F = 59.28, P < 0.001), in which the refractive change in mild myopia, moderate myopia, and high myopia children gradually increased (F = 73.12, P < 0.001). Large baseline refractive error, large body mass index, and high frequency of eating sweets were risk factors for myopia progression, while parental intervention and strong eye-care awareness were protective factors for delaying myopia progression. The nomogram graph predicted the probability of developing high myopia in children and found that baseline refraction had the greatest predictive value.

CONCLUSION

Myopia progression varies by age, sex, and myopia severity. Baseline refraction is the most important factor in predicting high myopia in childhood. we should focus on children with large baseline refraction or young age of onset of myopia in clinical myopia prevention and control.

Quality of life and depression among patients with high myopia in Nigeria: a cross sectional study

AIM

To evaluate the quality of life (QOL) and level of depression among participants with high myopia in Nigeria and the demographic factors associated with these outcomes.

METHODS

This cross-sectional study was conducted on 100 adult participants with high myopia (defined as refractive error ≤-5.00 D or worse, and uncorrected visual acuity worse than 6/18 in the better seeing eye) attending ophthalmology centres in Nigeria from 2 October 2021 to 30 August 2022. The means and standard deviations were calculated for each of the four domains of World Health Organization Quality of life scale (WHOQOL-BREF) using the transformed scores. The Beck Depression Inventory (BDI) scale was used to assess the level of depression.

RESULTS

The highest and the lowest mean scores of WHOQOL-BREF domains were found for the psychological and physical health domains (mean percentage scores were 67.0 [95% confidence intervals (CI) 64.1-68.9] and 55.3 (95%CI 51.8-58.8, P<0.001), respectively. One-way analysis of variance (ANOVA) revealed significant differences in physical health with educational status (higher among those with tertiary education: mean difference 0.9, 95%CI -0.2-2.1; P=0.049), differences in psychological health with working status (higher among those who were working 1.2, 95%CI 0.3-2.1; P=0.012). Also, the result showed a statistically significant association between environmental health and marital status (higher among non-married: 1.7, 95%CI -0.9-2.3; P=0.012) while overall health was associated with place of residence (higher in urban areas: 2.3, 95%CI 1.2-3.5; P=0.024). For depression, one in every nine participants reported major depressive symptom, mostly younger people (aged 16-29 vs 30-49y: 17.0% vs 0, P=0.019), and slightly more women than men (14.3% vs 0, P=0.064). There were significant negative correlations between the depression scores and psychological health (r=-0.48, P<0.001), physical health (r=-0.29, P=0.002), social and relationship (r=-0.49, P<0.001), environmental (r=-0.48, P<0.001) and overall health (r=-0.49, P<0.001).

CONCLUSION

People with high myopia have a relatively moderate QOL, but poor physical health, particularly the younger age group, and women who are more likely to experience clinically relevant depression. Eye care professionals should consider possible referrals for counselling for people with high myopia.

Urban Living Environment and Myopia in Children

Importance

The global prevalence of myopia has shown a steady increase over recent decades, with urban areas seemingly experiencing a more significant impact.

Objective

To assess the association between urbanization and the prevalence, incidence, progression, and severity of myopia.

Design, Setting, and Participants

This cohort study included students in grades 1 to 6 in Tianjin, China, who underwent 3 vision examinations conducted over a 2-year period, from March 1, 2021, to March 31, 2023. Participants from grades 1 to 4 completed the 2-year follow-up.

Exposures

Urban living environment.

Main Outcomes and Measures

The association of urbanization with the incidence, progression, prevalence, and severity of myopia. To quantify urbanization, an urban score was constructed using satellite data and an iterative exploratory factor analysis.

Results

Of 177 894 students (51.7% male; mean [SD] age, 10.27 [1.75] years) included in the study, 137 087 students (52.3% male; mean [SD] age, 8.97 [1.21] years) were followed up for 2 years. A positive association was identified between myopia incidence and urbanization. Specifically, each 1-unit increment in the urban score was associated with an increased risk of myopia over a 1-year period (odds ratio [OR], 1.09; 95% CI, 1.01-1.15; P = .02) and a 2-year period (OR, 1.53; 95% CI, 1.50-1.57; P < .001). Conversely, each 1-unit increase in the urban score was associated with a significant decrease in myopia progression at 1 year (OR, 0.84; 95% CI, 0.82-0.86; P < .001) and 2 years (OR, 0.73; 95% CI, 0.70-0.75, P < .001). In a cross-sectional data analysis, the urban score was positively associated with myopia prevalence (OR, 1.62; 95% CI, 1.08-2.42; P = .02) and negatively associated with myopia severity, as indicated by spherical equivalent refraction (OR, 1.46; 95% CI, 1.07-1.99; P = .02).

Conclusions and Relevance

This study exploring urban living environments and myopia revealed dual associations of urban living with both the incidence and the progression of myopia. The observed patterns emphasize the urgency of promptly implementing myopia control strategies in less urbanized regions, where myopia progression may be accentuated.

Prevalence of myopia in school-age children in Ethiopia: A systematic review and meta-analysis

Objective

This study aimed to estimate the pooled prevalence of myopia among school-age children in Ethiopia.

Methods

Eligible articles were searched from PubMed, Embase, and Web of Science databases. In addition, Google Scholar and reference lists of the retrieved articles were searched from 30 July 2022 to 02 January 2023. The preferred reporting of items for systematic reviews and meta-analysis was used to report the search results. Microsoft Excel was used to keep the data. The qualities of eligible studies were checked using the Joanna Briggs Institute critical appraisal checklist for prevalence studies. Analysis was held using STATA Version 11. The degree of heterogeneity was checked using I² statistics. The possible sources of heterogeneity were examined using meta-regression and subgroup analyses. The funnel plot and Egger's test were used to assess the potential publication bias. A correction was made for publication bias using Duval and Twee Die's trim-and-fill analysis. The systematic review registration number is PROSPERO (#CRD42022330541).

Results

We identified 21 eligible articles including 20,757 subjects. Of those participants, 10,601 (51.1%) and 10,156 (48.9%) were males and females, respectively. A total of 15,152 (73%) participants were urban residents. The estimated prevalence of myopia among school-age children in Ethiopia was found to be 5.26% (95% confidence interval: 4.09-6.42).

Conclusions

The prevalence of myopia among school-age children in Ethiopia is considerable, affecting one in 20 school-age children. Therefore, the authors recommend the stakeholders take extra steps to speed up the implementation of the school vision screening program and its integration plan into the existing school nutrition program.

Correlation between spherical equivalent and biometry parameters in adult Cynomolgus macaque

PURPOSE

To characterize the distribution of refractive and ocular biometry parameters and analyze the effect factors of the refractive status in cynomolgus monkey colonies.

METHODS

A Population-based cross-sectional study was conducted in adult cynomolgus macaque colonies. Animals were anesthetized with Zoletil 50. Intraocular pressure was measured using the Icare tonometer. Cycloplegic refraction (three drops of 1% tropicamide) and corneal radius of curvature (CRC) were measured using an autorefractor. The spherical equivalent (SE) was calculated. Biometric measurements, including the anterior chamber depth (ACD), lens thickness (LT), and axial length (AL), were obtained by A-scan ultrasonography. The AL-to-CR ratio (AL/CRC) was calculated. Central corneal thickness (CCT) and choroidal thickness (ChT) were measured using the Heidelberg Spectralis HRA OCT. Multiple regression analysis was performed to explore the association between refraction and ocular biometry.

RESULTS

Among 263 cynomolgus monkeys (aged 5-26 years), which consisted of 520 eyes, 29.42% had hyperopia, 27.12% had emmetropia, 33.27% had mild-to-moderate myopia and 10.19% had high myopia. The mean SE was -1.27 ± 3.44 Diopters (D). The mean CRC, CCT, AL, and ChT was 5.70 ± 0.22 mm, 454.30 ± 32.40 μm, 18.76 ± 0.89 mm and 188.96 ± 38.19 μm, respectively. The LT was the thickest in the hyperopic eyes. CRC was the lowest, and CCT was the thickest in high myopic eyes. AL increased, while ChT decreased as SE decreased. For the SE variance, AL alone explained 40.5%; age, AL, and CRC together explained 57.5%.

CONCLUSIONS

The refractive characteristics and biometry parameters of cynomolgus monkeys are highly comparable to those of humans. AL, CRC, and ChT showed the similar variation tendency in cynomolguses when compared to humans. Cynomolgus monkeys with naturally-occurring refractive errors may be a good animal model for refractive studies.

Machine learning to analyze the factors influencing myopia in students of different school periods

Purpose

We aim to develop myopia classification models based on machine learning algorithms for each schooling period, and further analyze the similarities and differences in the factors influencing myopia in each school period based on each model.

Design

Retrospective cross-sectional study.

Participants

We collected visual acuity, behavioral, environmental, and genetic data from 7,472 students in 21 primary and secondary schools (grades 1-12) in Jiamusi, Heilongjiang Province, using visual acuity screening and questionnaires.

Methods

Machine learning algorithms were used to construct myopia classification models for students at the whole schooling period, primary school, junior high school, and senior high school period, and to rank the importance of features in each model.

Results

The main influencing factors for students differ by school section, The optimal machine learning model for the whole schooling period was Random Forest (AUC = 0.752), with the top three influencing factors being age, myopic grade of the mother, and Whether myopia requires glasses. The optimal model for the primary school period was a Random Forest (AUC = 0.710), with the top three influences being the myopic grade of the mother, age, and extracurricular tutorials weekly. The Junior high school period was an Support Vector Machine (SVM; AUC = 0.672), and the top three influencing factors were gender, extracurricular tutorial subjects weekly, and whether can you do the "three ones" when reading and writing. The senior high school period was an XGboost (AUC = 0.722), and the top three influencing factors were the need for spectacles for myopia, average daily time spent outdoors, and the myopic grade of the mother.

Conclusion

Factors such as genetics and eye use behavior all play an essential role in students' myopia, but there are differences between school periods, with those in the lower levels focusing on genetics and those in the higher levels focusing on behavior, but both play an essential role in myopia.

Baseline metrics that may predict future myopia in young children

PURPOSE

We used baseline data from the PICNIC longitudinal study to investigate structural, functional, behavioural and heritable metrics that may predict future myopia in young children.

METHODS

Cycloplegic refractive error (M) and optical biometry were obtained in 97 young children with functional emmetropia. Children were classified as high risk (HR) or low risk (LR) for myopia based on parental myopia and M. Other metrics included axial length (AXL), axial length/corneal radius (AXL/CR) and refractive centile curves.

RESULTS

Based on the PICNIC criteria, 46 children (26 female) were classified as HR (M = +0.62 ± 0.44 D, AXL = 22.80 ± 0.64 mm) and 51 (27 female) as LR (M = +1.26 ± 0.44 D, AXL = 22.77 ± 0.77 mm). Based on centiles, 49 children were HR, with moderate agreement compared with the PICNIC classification (k = 0.65, p < 0.01). ANCOVA with age as a covariate showed a significant effect for AXL (p < 0.01), with longer AXL and deeper anterior chamber depth (ACD) (p = 0.01) in those at HR (differences AXL = 0.16 mm, ACD = 0.13 mm). Linear regression models showed that central corneal thickness (CCT), ACD, posterior vitreous depth (PVD) (=AXL - CCT - ACD-lens thickness (LT)), corneal radius (CR) and age significantly predicted M (R = 0.64, p < 0.01). Each 1.00 D decrease in hyperopia was associated with a 0.97 mm elongation in PVD and 0.43 mm increase in CR. The ratio AXL/CR significantly predicted M (R = -0.45, p < 0.01), as did AXL (R = -0.25, p = 0.01), although to a lesser extent.

CONCLUSIONS

Although M and AXL were highly correlated, the classification of pre-myopic children into HR or LR was significantly different when using each parameter, with AXL/CR being the most predictive metric. At the end of the longitudinal study, we will be able to assess the predictability of each metric.