-
Ophthalmology May 2016Myopia is a common cause of vision loss, with uncorrected myopia the leading cause of distance vision impairment globally. Individual studies show variations in the... (Meta-Analysis)
Meta-Analysis Review
PURPOSE
Myopia is a common cause of vision loss, with uncorrected myopia the leading cause of distance vision impairment globally. Individual studies show variations in the prevalence of myopia and high myopia between regions and ethnic groups, and there continues to be uncertainty regarding increasing prevalence of myopia.
DESIGN
Systematic review and meta-analysis.
METHODS
We performed a systematic review and meta-analysis of the prevalence of myopia and high myopia and estimated temporal trends from 2000 to 2050 using data published since 1995. The primary data were gathered into 5-year age groups from 0 to ≥100, in urban or rural populations in each country, standardized to definitions of myopia of -0.50 diopter (D) or less and of high myopia of -5.00 D or less, projected to the year 2010, then meta-analyzed within Global Burden of Disease (GBD) regions. Any urban or rural age group that lacked data in a GBD region took data from the most similar region. The prevalence data were combined with urbanization data and population data from United Nations Population Department (UNPD) to estimate the prevalence of myopia and high myopia in each country of the world. These estimates were combined with myopia change estimates over time derived from regression analysis of published evidence to project to each decade from 2000 through 2050.
RESULTS
We included data from 145 studies covering 2.1 million participants. We estimated 1406 million people with myopia (22.9% of the world population; 95% confidence interval [CI], 932-1932 million [15.2%-31.5%]) and 163 million people with high myopia (2.7% of the world population; 95% CI, 86-387 million [1.4%-6.3%]) in 2000. We predict by 2050 there will be 4758 million people with myopia (49.8% of the world population; 3620-6056 million [95% CI, 43.4%-55.7%]) and 938 million people with high myopia (9.8% of the world population; 479-2104 million [95% CI, 5.7%-19.4%]).
CONCLUSIONS
Myopia and high myopia estimates from 2000 to 2050 suggest significant increases in prevalences globally, with implications for planning services, including managing and preventing myopia-related ocular complications and vision loss among almost 1 billion people with high myopia.
Topics: Global Health; Humans; Myopia; Myopia, Degenerative; Rural Population; Urban Population
PubMed: 26875007
DOI: 10.1016/j.ophtha.2016.01.006 -
The British Journal of Ophthalmology Feb 2023In 2018, a consortium of government bodies in China led by the Ministry of Education released the (CPPNCT), aiming to reduce the incidence of myopia and control myopic... (Review)
Review
In 2018, a consortium of government bodies in China led by the Ministry of Education released the (CPPNCT), aiming to reduce the incidence of myopia and control myopic progression in China. Recommendations span from home-based to school-based interventions, including time outdoors, physical activity, light exposure, near-work activity, screen time, Chinese eye exercises, diet and sleep. To date, the levels of evidence for this suite of interventions have not been thoroughly investigated. This review has summarised the evidence of the interventions recommended by the CPPNCT in myopia prevention and control. Thus, the following statements are supposed by the evidence: (1) Increasing time outdoors and reducing near-work time are effective in lowering incident myopia in school-aged children. (2) All interventions have a limited effect on myopia progression. Ongoing research may lead to a better understanding of the underlying mechanisms of myopia development, the interaction of different interventions and recommendations, confounding variables and their true effect on myopia prevention, and the identification of those most likely to respond to specific interventions. This field may also benefit from longer-term studies of the various interventions or strategies covered within this review article, to better understand the persistence of treatment effects over time and explore more novel approaches to myopia control.
Topics: Humans; Adolescent; Child; Myopia; Longitudinal Studies; Schools; Time Factors; China
PubMed: 34844916
DOI: 10.1136/bjophthalmol-2021-319306 -
The Cochrane Database of Systematic... Feb 2023Myopia is a common refractive error, where elongation of the eyeball causes distant objects to appear blurred. The increasing prevalence of myopia is a growing global... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Myopia is a common refractive error, where elongation of the eyeball causes distant objects to appear blurred. The increasing prevalence of myopia is a growing global public health problem, in terms of rates of uncorrected refractive error and significantly, an increased risk of visual impairment due to myopia-related ocular morbidity. Since myopia is usually detected in children before 10 years of age and can progress rapidly, interventions to slow its progression need to be delivered in childhood.
OBJECTIVES
To assess the comparative efficacy of optical, pharmacological and environmental interventions for slowing myopia progression in children using network meta-analysis (NMA). To generate a relative ranking of myopia control interventions according to their efficacy. To produce a brief economic commentary, summarising the economic evaluations assessing myopia control interventions in children. To maintain the currency of the evidence using a living systematic review approach. SEARCH METHODS: We searched CENTRAL (which contains the Cochrane Eyes and Vision Trials Register), MEDLINE; Embase; and three trials registers. The search date was 26 February 2022. SELECTION CRITERIA: We included randomised controlled trials (RCTs) of optical, pharmacological and environmental interventions for slowing myopia progression in children aged 18 years or younger. Critical outcomes were progression of myopia (defined as the difference in the change in spherical equivalent refraction (SER, dioptres (D)) and axial length (mm) in the intervention and control groups at one year or longer) and difference in the change in SER and axial length following cessation of treatment ('rebound'). DATA COLLECTION AND ANALYSIS: We followed standard Cochrane methods. We assessed bias using RoB 2 for parallel RCTs. We rated the certainty of evidence using the GRADE approach for the outcomes: change in SER and axial length at one and two years. Most comparisons were with inactive controls.
MAIN RESULTS
We included 64 studies that randomised 11,617 children, aged 4 to 18 years. Studies were mostly conducted in China or other Asian countries (39 studies, 60.9%) and North America (13 studies, 20.3%). Fifty-seven studies (89%) compared myopia control interventions (multifocal spectacles, peripheral plus spectacles (PPSL), undercorrected single vision spectacles (SVLs), multifocal soft contact lenses (MFSCL), orthokeratology, rigid gas-permeable contact lenses (RGP); or pharmacological interventions (including high- (HDA), moderate- (MDA) and low-dose (LDA) atropine, pirenzipine or 7-methylxanthine) against an inactive control. Study duration was 12 to 36 months. The overall certainty of the evidence ranged from very low to moderate. Since the networks in the NMA were poorly connected, most estimates versus control were as, or more, imprecise than the corresponding direct estimates. Consequently, we mostly report estimates based on direct (pairwise) comparisons below. At one year, in 38 studies (6525 participants analysed), the median change in SER for controls was -0.65 D. The following interventions may reduce SER progression compared to controls: HDA (mean difference (MD) 0.90 D, 95% confidence interval (CI) 0.62 to 1.18), MDA (MD 0.65 D, 95% CI 0.27 to 1.03), LDA (MD 0.38 D, 95% CI 0.10 to 0.66), pirenzipine (MD 0.32 D, 95% CI 0.15 to 0.49), MFSCL (MD 0.26 D, 95% CI 0.17 to 0.35), PPSLs (MD 0.51 D, 95% CI 0.19 to 0.82), and multifocal spectacles (MD 0.14 D, 95% CI 0.08 to 0.21). By contrast, there was little or no evidence that RGP (MD 0.02 D, 95% CI -0.05 to 0.10), 7-methylxanthine (MD 0.07 D, 95% CI -0.09 to 0.24) or undercorrected SVLs (MD -0.15 D, 95% CI -0.29 to 0.00) reduce progression. At two years, in 26 studies (4949 participants), the median change in SER for controls was -1.02 D. The following interventions may reduce SER progression compared to controls: HDA (MD 1.26 D, 95% CI 1.17 to 1.36), MDA (MD 0.45 D, 95% CI 0.08 to 0.83), LDA (MD 0.24 D, 95% CI 0.17 to 0.31), pirenzipine (MD 0.41 D, 95% CI 0.13 to 0.69), MFSCL (MD 0.30 D, 95% CI 0.19 to 0.41), and multifocal spectacles (MD 0.19 D, 95% CI 0.08 to 0.30). PPSLs (MD 0.34 D, 95% CI -0.08 to 0.76) may also reduce progression, but the results were inconsistent. For RGP, one study found a benefit and another found no difference with control. We found no difference in SER change for undercorrected SVLs (MD 0.02 D, 95% CI -0.05 to 0.09). At one year, in 36 studies (6263 participants), the median change in axial length for controls was 0.31 mm. The following interventions may reduce axial elongation compared to controls: HDA (MD -0.33 mm, 95% CI -0.35 to 0.30), MDA (MD -0.28 mm, 95% CI -0.38 to -0.17), LDA (MD -0.13 mm, 95% CI -0.21 to -0.05), orthokeratology (MD -0.19 mm, 95% CI -0.23 to -0.15), MFSCL (MD -0.11 mm, 95% CI -0.13 to -0.09), pirenzipine (MD -0.10 mm, 95% CI -0.18 to -0.02), PPSLs (MD -0.13 mm, 95% CI -0.24 to -0.03), and multifocal spectacles (MD -0.06 mm, 95% CI -0.09 to -0.04). We found little or no evidence that RGP (MD 0.02 mm, 95% CI -0.05 to 0.10), 7-methylxanthine (MD 0.03 mm, 95% CI -0.10 to 0.03) or undercorrected SVLs (MD 0.05 mm, 95% CI -0.01 to 0.11) reduce axial length. At two years, in 21 studies (4169 participants), the median change in axial length for controls was 0.56 mm. The following interventions may reduce axial elongation compared to controls: HDA (MD -0.47mm, 95% CI -0.61 to -0.34), MDA (MD -0.33 mm, 95% CI -0.46 to -0.20), orthokeratology (MD -0.28 mm, (95% CI -0.38 to -0.19), LDA (MD -0.16 mm, 95% CI -0.20 to -0.12), MFSCL (MD -0.15 mm, 95% CI -0.19 to -0.12), and multifocal spectacles (MD -0.07 mm, 95% CI -0.12 to -0.03). PPSL may reduce progression (MD -0.20 mm, 95% CI -0.45 to 0.05) but results were inconsistent. We found little or no evidence that undercorrected SVLs (MD -0.01 mm, 95% CI -0.06 to 0.03) or RGP (MD 0.03 mm, 95% CI -0.05 to 0.12) reduce axial length. There was inconclusive evidence on whether treatment cessation increases myopia progression. Adverse events and treatment adherence were not consistently reported, and only one study reported quality of life. No studies reported environmental interventions reporting progression in children with myopia, and no economic evaluations assessed interventions for myopia control in children.
AUTHORS' CONCLUSIONS
Studies mostly compared pharmacological and optical treatments to slow the progression of myopia with an inactive comparator. Effects at one year provided evidence that these interventions may slow refractive change and reduce axial elongation, although results were often heterogeneous. A smaller body of evidence is available at two or three years, and uncertainty remains about the sustained effect of these interventions. Longer-term and better-quality studies comparing myopia control interventions used alone or in combination are needed, and improved methods for monitoring and reporting adverse effects.
Topics: Humans; Child; Network Meta-Analysis; Myopia; Refractive Errors; Atropine; Refraction, Ocular
PubMed: 36809645
DOI: 10.1002/14651858.CD014758.pub2 -
Eye (London, England) May 2022Myopia is a leading cause of visual impairment and has raised significant international concern in recent decades with rapidly increasing prevalence and incidence... (Review)
Review
Myopia is a leading cause of visual impairment and has raised significant international concern in recent decades with rapidly increasing prevalence and incidence worldwide. Accurate prediction of future myopia risk could help identify high-risk children for early targeted intervention to delay myopia onset or slow myopia progression. Researchers have built and assessed various myopia prediction models based on different datasets, including baseline refraction or biometric data, lifestyle data, genetic data, and data integration. Here, we summarize all related work published in the past 30 years and provide a comprehensive review of myopia prediction methods, datasets, and performance, which could serve as a useful reference and valuable guideline for future research.
Topics: Biometry; Child; Disease Progression; Humans; Incidence; Myopia; Refraction, Ocular
PubMed: 34645966
DOI: 10.1038/s41433-021-01805-6 -
The Lancet. Digital Health Dec 2021Excessive use of digital smart devices, including smartphones and tablet computers, could be a risk factor for myopia. We aimed to review the literature on the... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Excessive use of digital smart devices, including smartphones and tablet computers, could be a risk factor for myopia. We aimed to review the literature on the association between digital smart device use and myopia.
METHODS
In this systematic review and meta-analysis we searched MEDLINE and Embase, and manually searched reference lists for primary research articles investigating smart device (ie, smartphones and tablets) exposure and myopia in children and young adults (aged 3 months to 33 years) from database inception to June 2 (MEDLINE) and June 3 (Embase), 2020. We included studies that investigated myopia-related outcomes of prevalent or incident myopia, myopia progression rate, axial length, or spherical equivalent. Studies were excluded if they were reviews or case reports, did not investigate myopia-related outcomes, or did not investigate risk factors for myopia. Bias was assessed with the Joanna Briggs Institute Critical Appraisal Checklists for analytical cross-sectional and cohort studies. We categorised studies as follows: category one studies investigated smart device use independently; category two studies investigated smart device use in combination with computer use; and category three studies investigated smart device use with other near-vision tasks that were not screen-based. We extracted unadjusted and adjusted odds ratios (ORs), β coefficients, prevalence ratios, Spearman's correlation coefficients, and p values for associations between screen time and incident or prevalent myopia. We did a meta-analysis of the association between screen time and prevalent or incident myopia for category one articles alone and for category one and two articles combined. Random-effects models were used when study heterogeneity was high (I>50%) and fixed-effects models were used when heterogeneity was low (I≤50%).
FINDINGS
3325 articles were identified, of which 33 were included in the systematic review and 11 were included in the meta-analysis. Four (40%) of ten category one articles, eight (80%) of ten category two articles, and all 13 category three articles used objective measures to identify myopia (refraction), whereas the remaining studies used questionnaires to identify myopia. Screen exposure was measured by use of questionnaires in all studies, with one also measuring device-recorded network data consumption. Associations between screen exposure and prevalent or incident myopia, an increased myopic spherical equivalent, and longer axial length were reported in five (50%) category one and six (60%) category two articles. Smart device screen time alone (OR 1·26 [95% CI 1·00-1·60]; I=77%) or in combination with computer use (1·77 [1·28-2·45]; I=87%) was significantly associated with myopia. The most common sources of risk of bias were that all 33 studies did not include reliable measures of screen time, seven (21%) did not objectively measure myopia, and nine (27%) did not identify or adjust for confounders in the analysis. The high heterogeneity between studies included in the meta-analysis resulted from variability in sample size (range 155-19 934 participants), the mean age of participants (3-16 years), the standard error of the estimated odds of prevalent or incident myopia (0·02-2·21), and the use of continuous (six [55%] of 11) versus categorical (five [46%]) screen time variables INTERPRETATION: Smart device exposure might be associated with an increased risk of myopia. Research with objective measures of screen time and myopia-related outcomes that investigates smart device exposure as an independent risk factor is required.
FUNDING
None.
Topics: Adolescent; Adult; Cell Phone Use; Child; Child, Preschool; Computers; Female; Humans; Infant; Infant, Newborn; Male; Myopia; Risk Factors; Screen Time; Smartphone; Social Media; Vision, Ocular; Young Adult
PubMed: 34625399
DOI: 10.1016/S2589-7500(21)00135-7 -
International Journal of Environmental... Jan 2023Myopia is a global public health problem affecting quality of life and work productivity. Data is scarce regarding the effects of near work on myopia. Providing a larger... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Myopia is a global public health problem affecting quality of life and work productivity. Data is scarce regarding the effects of near work on myopia. Providing a larger meta-analysis with life-long perspective, including adults and occupational exposure seemed needed.
METHODS
We searched PubMed, Cochrane Library, Embase and Science Direct for studies reporting myopia prevalence in near work. Myopia was defined as a mean spherical equivalent ≤ -0.50 diopter. We performed a meta-analysis using random-effects model on myopia prevalence, myopia progression per year, and odds ratio (OR) of myopia in near work, completed by subgroup analyses and meta-regressions on patients' characteristics, type of work in adults, geographic zones, time and characteristics of near work.
RESULTS
We included 78 studies, representing a total of 254,037 participants, aged from 6 to 39 years. The global prevalence of myopia in near work was 35% (95% CI: 30 to 41%), with a prevalence of 31% (95% CI: 26 to 37%) in children and 46% (95% CI: 30 to 62%) in adults. Myopia progression was -0.39 diopters per year (-0.53 to -0.24 D/year), ranging from -0.44 (-0.57 to -0.31) in children to -0.25 D/year (-0.56 to 0.06) in adults. The odds of myopia in workers exposed vs. non-exposed to near work were increased by 26% (18 to 34%), by 31% (21 to 42%) in children and 21% (6 to 35%) in adults. Prevalence of myopia was higher in adults compared to children (Coefficient 0.15, 95% CI: 0.03 to 0.27).
CONCLUSIONS
Near work conditions, including occupational exposure in adults, could be associated with myopia. Targeted prevention should be implemented in the workplace.
Topics: Adult; Child; Humans; Quality of Life; Myopia; Refraction, Ocular; Odds Ratio; Prevalence
PubMed: 36613196
DOI: 10.3390/ijerph20010875 -
International Journal of Molecular... Apr 2022The contributory roles of vitamin D in ocular and visual health have long been discussed, with numerous studies pointing to the adverse effects of vitamin D deficiency.... (Review)
Review
The contributory roles of vitamin D in ocular and visual health have long been discussed, with numerous studies pointing to the adverse effects of vitamin D deficiency. In this paper, we provide a systematic review of recent findings on the association between vitamin D and different ocular diseases, including myopia, age-related macular degeneration (AMD), glaucoma, diabetic retinopathy (DR), dry eye syndrome (DES), thyroid eye disease (TED), uveitis, retinoblastoma (RB), cataract, and others, from epidemiological, clinical and basic studies, and briefly discuss vitamin D metabolism in the eye. We searched two research databases for articles examining the association between vitamin D deficiency and different ocular diseases. One hundred and sixty-two studies were found. There is evidence on the association between vitamin D and myopia, AMD, DR, and DES. Overall, 17 out of 27 studies reported an association between vitamin D and AMD, while 48 out of 54 studies reported that vitamin D was associated with DR, and 25 out of 27 studies reported an association between vitamin D and DES. However, the available evidence for the association with other ocular diseases, such as glaucoma, TED, and RB, remains limited.
Topics: Diabetic Retinopathy; Eye; Glaucoma; Humans; Macular Degeneration; Myopia; Vitamin D; Vitamin D Deficiency; Vitamins
PubMed: 35457041
DOI: 10.3390/ijms23084226 -
Investigative Ophthalmology & Visual... Apr 2020To determine the risk between degree of myopia and myopic macular degeneration (MMD), retinal detachment (RD), cataract, open angle glaucoma (OAG), and blindness. (Meta-Analysis)
Meta-Analysis
PURPOSE
To determine the risk between degree of myopia and myopic macular degeneration (MMD), retinal detachment (RD), cataract, open angle glaucoma (OAG), and blindness.
METHODS
A systematic review and meta-analyses of studies published before June 2019 on myopia complications. Odds ratios (OR) per complication and spherical equivalent (SER) degree (low myopia SER < -0.5 to > -3.00 diopter [D]; moderate myopia SER ≤ -3.00 to > -6.00 D; high myopia SER ≤ -6.00 D) were calculated using fixed and random effects models.
RESULTS
Low, moderate, and high myopia were all associated with increased risks of MMD (OR, 13.57, 95% confidence interval [CI], 6.18-29.79; OR, 72.74, 95% CI, 33.18-159.48; OR, 845.08, 95% CI, 230.05-3104.34, respectively); RD (OR, 3.15, 95% CI, 1.92-5.17; OR, 8.74, 95% CI, 7.28-10.50; OR, 12.62, 95% CI, 6.65-23.94, respectively); posterior subcapsular cataract (OR, 1.56, 95% CI, 1.32-1.84; OR, 2.55, 95% CI, 1.98-3.28; OR, 4.55, 95% CI, 2.66-7.75, respectively); nuclear cataract (OR, 1.79, 95% CI, 1.08-2.97; OR, 2.39, 95% CI, 1.03-5.55; OR, 2.87, 95% CI, 1.43-5.73, respectively); and OAG (OR, 1.59, 95% CI, 1.33-1.91; OR, 2.92, 95% CI, 1.89-4.52 for low and moderate/high myopia, respectively). The risk of visual impairment was strongly related to longer axial length, higher myopia degree, and age older than 60 years (OR, 1.71, 95% CI, 1.07-2.74; OR, 5.54, 95% CI, 3.12-9.85; and OR, 87.63, 95% CI, 34.50-222.58 for low, moderate, and high myopia in participants aged >60 years, respectively).
CONCLUSIONS
Although high myopia carries the highest risk of complications and visual impairment, low and moderate myopia also have considerable risks. These estimates should alert policy makers and health care professionals to make myopia a priority for prevention and treatment.
Topics: Age Factors; Cataract; Disease Progression; Female; Glaucoma, Open-Angle; Humans; Macular Degeneration; Male; Myopia, Degenerative; Prevalence; Prognosis; Risk Assessment; Visual Acuity
PubMed: 32347918
DOI: 10.1167/iovs.61.4.49 -
Eye (London, England) Nov 2023To analyse and compare the efficacy of different interventions for myopia prevention and control in children. (Meta-Analysis)
Meta-Analysis
OBJECTIVES
To analyse and compare the efficacy of different interventions for myopia prevention and control in children.
METHODS
We searched CNKI, VIP, Wan-Fang, CBM, Chinese Clinical Registry, PubMed, The Cochrane Library, Web of Science, Embase and ClinicalTrials.gov from inception to July 2022. We selected randomized controlled trials (RCTs) that included interventions to slow myopia progression in children. The main outcomes included mean annual change in axial length (AL) (millimetres/year) and in refraction (R) (dioptres/year).
RESULTS
A total of 80 RCTs (27103 eyes) were included. In comparison with control, orthokeratology (AL, -0.36 [-0.53, -0.20], P < 0.05; R, 0.56 [0.34, 0.77], P < 0.05), 1%Atropine (AL, -0.39 [-0.65, -0.13], P < 0.05; R, 0.54 [0.31, 0.77], P < 0.05), 0.01%Atropine + orthokeratology (AL, -0.47 [-0.80, -0.14], P < 0.05; R, 0.81 [0.43, 1.20], P < 0.05) could significantly slow the progression of myopia; in addition, progressive multi-focal spectacle lenses (PMSL) (0.42, [0.06, 0.79], P < 0.05), bifocal soft contact lenses (0.40, [0.03, 0.77], P < 0.05), 0.5%Atropine (0.67 [0.25, 1.10], P < 0.05), 0.1%Atropine (0.42 [0.15, 0.71], P < 0.05), 0.05%Atropine (0.57 [0.28, 0.86], P < 0.05), 0.01%Atropine (0.33 [0.15, 0.52], P < 0.05), 1%Atropine + bifocal spectacle lenses (BSL) (1.30 [0.54, 2.00], P < 0.05), 1%Atropine + PMSL (0.66 [0.23, 1.10], P < 0.05), 0.01%Atropine + single vision spectacle lenses (SVSL) (0.70 [0.23, 1.10], P < 0.05), 0.01%Atropine + orthokeratology (0.81 [0.43, 1.20], P < 0.05), BSL + Massage (0.85 [0.22, 1.50], P < 0.05), SVSL + Red light (0.59 [0.06, 0.79], P < 0.05) showed significant slowing effect on the increase in R.
CONCLUSIONS
This network meta-analysis suggests that the combined measures were most effective in AL and R, followed by Atropine.
Topics: Child; Humans; Network Meta-Analysis; Disease Progression; Myopia; Atropine; Contact Lenses, Hydrophilic; Refraction, Ocular; Axial Length, Eye
PubMed: 37106147
DOI: 10.1038/s41433-023-02534-8 -
Ophthalmic & Physiological Optics : the... Mar 2020Digital screen time has been cited as a potential modifiable environmental risk factor that can increase myopia risk. However, associations between screen time and...
PURPOSE
Digital screen time has been cited as a potential modifiable environmental risk factor that can increase myopia risk. However, associations between screen time and myopia have not been consistently reported. Although myopia prevalence increased before the massive use of digital devices in some countries, with the rise being influenced by education, there may be an added recent effect of screen time. The aim of this systematic review is to determine the association between screen time and the risk of developing (1) prevalent or incident myopia, or (2) the risk of myopia progression in children. Published manuscripts were identified in PubMed, ScienceDirect and the Cochrane Library, and citation lists were reviewed.
RECENT FINDINGS
Fifteen studies were included (nine cross-sectional and six cohort studies) with a total of 49 789 children aged between 3 and 19 years old. Seven studies found an association between screen time and myopia. The results showed mixed evidence with the more recent studies exposing a trend of association between hours spent by children using screens and myopia. Meta-analysis using a random-effects model was performed in five studies (n = 20 889) that reported odds ratio (OR). The I statistics was used to assess heterogeneity. A pooled OR of 1.02 (95% CI: 0.96-1.08; p = 0.48) suggests that screen time is not associated with prevalent and incident myopia in this group of five studies.
SUMMARY
The results for screen time and myopia are mixed. Further studies with objective screen time measurements are necessary to assess evidence of an association between screen time and myopia.
Topics: Global Health; Humans; Myopia; Prevalence; Refraction, Ocular; Risk Factors; Screen Time; Time Factors
PubMed: 31943280
DOI: 10.1111/opo.12657