February 3, 2025
By Michael Lipson, OD, and Bruce Koffler, MD
Why develop a clinician’s digital smart guide for myopia management and control? We’ve asked that same question. As busy clinicians, we’ve realized the value of having an easily accessible, understandable, and updated reference in the exam room to help manage children with myopia. This guide will be of value to those eye care professionals first getting into myopia control, “newbies,” as well as experienced clinicians. It is intended to be easy to understand, not only for the ECP but also for their staff, and it should also serve as a teaching tool for parents of myopic children.
The modalities and protocols to treat myopia progression are improving and changing on a daily basis. Accordingly, any digital guide needs to have the capability of being modified on a regular basis. We are excited that this guide will have this capability.
Myopia has now been recognized by the National Academies of Sciences, Engineering, and Medicine as a disease entity.1 The literature shows that we are in the midst of a myopic epidemic where 50% of the population will be myopic in 2050.2 Certain populations, Asians in particular, are faced with a higher prevalence of myopia, 80-90%, and a significant degree of high myopia, (>6.00 D).3,4 We recognize that with every diopter increase in myopia, there is an exponentially increased risk of other ocular diseases later in life, such as myopic macular degeneration.5 More practitioners are now aware of these risks and are preparing themselves to get more involved in treating myopic children in order to reduce those risks. The time seems right for the creation of a digital diagnostic and treatment guide to enable early intervention with evidence-based treatments to slow myopic progression in a more systematic way.
Our guide will incorporate seven attributes (ethnicity, gender, age of onset, parental myopia, time outdoors, time on near tasks, and baseline axial length) from the literature as significant evidence-based risk factors. Based on the patient and family history and exam, each attribute will be assigned an appropriate score. The scoring results will produce an overall risk score, which, in a subsequent article on a prescribing protocol, will guide the practitioner in initiating a treatment plan.
Assessment of Risk
This guide is intended to assess pre-myopic children and children who are already myopic. A combination of clinical experience and clinical research has established seven categorical attributes that contribute to the risk of myopia development and becoming a high myope (>6.00 D). Using a risk score of zero to four for each attribute, a total score is generated to create a numerical risk score. This total score is intended to quantify the risk of a child developing myopia for those not yet myopic and to quantify the risk of significant myopic progression and axial elongation for those already myopic. It can be used for diagnosis, explaining to parents, and creating a treatment protocol.
These seven attributes and their influences are described as follows, and the scores attributed to aspects of each are indicated:
Ethnicity
Children of all ethnicities normally become more myopic as they grow. Numerous studies have shown that Asian eyes develop myopia earlier and progress more quickly and to a higher degree of myopia than those of Indian, Caucasian, Hispanic, and African American ethnicities.6-9
Scoring: Asian = 4, East Indian = 3, Caucasian = 2, Hispanic = 2, African-American = 2
Gender
Both males and females show myopic progression during growth years, but females show a higher rate of progression at an earlier age.6,8
Scoring: Female = 3, Male = 2
Age of Myopia Onset
The earlier myopia is diagnosed, the higher the degree of ultimate myopia as an adult. Also, the rate of myopic progression has been shown to be fastest in the year prior to first myopia diagnosis and between the ages of 6-10. A very extensive and highly cited study concluded that refractive status at various ages was the best predictor of future myopia. In that study, the development of myopia in any amount was more likely when refraction was < +0.75 D of hyperopia at age 6, +0.50 D or less at age 7-8, +0.25 D or less at age 9-10, and emmetropia or any myopia at 11.7,10,11
Relative to the development of “high myopia,” the age of myopia onset is probably the single most significant risk factor, as shown in Table 1.12
Scoring: Age 6 or under = 4, Age 7-9 = 3, Age 10-11 = 2, Age 12 or more = 1

Table 1. Percentage of children who develop high myopia in adulthood based on the age of myopia onset, from Hu, Ding, et al. (2020).12
Parental Myopia
Heredity has shown a definite influence on childhood myopia. This is particularly evident when either of the parents is highly myopic (> 6.00 D). The risk of a child becoming myopic and showing rapid progression is greatest when both parents are myopic.11
Scoring: Both parents myopic = 4, One parent = 3, Neither parent = 1
Time Outdoors per Week
Increased time spent outdoors has been shown unequivocally to contribute to delaying the onset of myopia. Once myopia has developed, studies on this effect have shown mixed results, some showing a continued beneficial effect while others show minimal impact on the rate of progression.13,14
Scoring: 0-3 hours/week = 4, 4-6 hours/week = 3, 7-9 hours/week = 2, 10-13 hours/week = 1, ≥14 hours/week = 0
Time Spent on Near Tasks
Extended periods of time spent reading, watching television, and using electronic devices may have an impact on the rate of myopic progression. Results from numerous studies are quite varied. Looking at more than 30 studies on the subject, about 60% of these studies show that longer time on these near tasks increases the degree of myopia progression, while about 40% show no effect on the progression rate.15
Scoring: >21 hours/week = 4, 17-20 hours/week = 3, 12-16 hours/week = 2, 8-11 hours/week = 1, <7 hours/week = 0
Baseline Axial Length – Percentile Scoring
Longer axial length is the most significant risk factor for serious vision-threatening complications from myopia. Also, normative data for childhood axial length can be used to establish risk for myopia development and progression to high myopia.6,16,17 Using the charts below to plot the patient’s axial length and age, a percentile score can be found. This percentile is used to establish a risk score for the baseline axial length attribute.
Scoring: Percentile: >69 = 4, 50-69 = 3, 35-49 = 2, 20-34 = 1, <20 = 0
Summary
The composite scoring of these seven attributes generates a total score that establishes the risk of becoming a high myope. In a subsequent article, we’ll explain how the total score can be used to guide the prescribing of modalities to control the rate of myopic progression and axial elongation. The total score can also be used to illustrate the risk of a myopic child becoming highly myopic. For parents, creating a graded scale easily demonstrates the likely trajectory of refractive changes for their children and the risk they are subject to.
The following case examples illustrate how the attributes are scored and scaled for a particular patient to establish their risk score. The scores for each attribute are in parentheses following the description.
CASE 1: 6 Y.O Korean (Ethnicity = 4) female (Gender = 3) presents for first annual eye exam with a family history of one parent with high myopia (Parental History = 3), a cycloplegic refraction of +0.50 D (Age of Onset = 0), axial length of 23.50 mm (Axial Length, 98th percentile = 4), loves playing outdoors at least two hours/day (Time Outdoors = 0) and is an avid reader of books and on her iPad for an average of four hours a day (Time on Near Tasks = 4). Total Score = 18 🡪 Moderate Risk |
CASE 2: 9 Y.O. Caucasian (Ethnicity = 2) male (Gender = 2) from U.S. presents for second eye exam, with a family history of one parent being myopic (Parental History = 3) cycloplegic of -3.00 D, with a prior history of being -2.00 D on the first exam two years before (Age of Onset = 3). Current axial length of 24.00 mm (Axial Length, 90th percentile = 4) plays outside about one hour/day (Time Outdoors = 2) and enjoys reading and video games averaging five hours/day (Time on Near Tasks = 4). Total Score = 20 🡪 High Risk |
References
- National Academies of Sciences, Engineering, and Medicine. 2024. Myopia: Causes, Prevention, and Treatment of an Increasingly Common Disease. Washington, DC: The National Academies Press. https://doi.org/10.17226/27734.
- Holden BA, Fricke TR, Wilson DA, et al. Global prevalence of myopia and high myopia and temporal trends from 2000 through 2050. Ophthalmology. 2016;123:1036–42.
- Ip, JM, Huynh, SC, Robaei D, et al. Ethnic differences in refraction and ocular biometry in a population-based sample of 11–15-year-old Australian children. Eye. 2008;22:649–656.
- Logan NS, Shah P, Rudnicka AR, et al. Childhood ethnic differences in ametropia and ocular biometry: the Aston Eye Study. Ophthalmic Physiol Opt. 2011;31:550–558.
- Bullimore MA, Brennan NA. Myopia Control: Why Each Diopter Matters. Optom Vis Sci. 2019; 96:463-465.
- Twelker JD, Mitchell GL, Messer DH, et al. Children’s Ocular Components and Age, Gender, and Ethnicity. Optom Vis Sci. 2009;86:918–935.
- Mutti DO, Sinnott LT, Cotter SA, et al. Predicting the onset of myopia in children by age, sex, and ethnicity: Results from the CLEERE Study. Optom Vis Sci. 2024;101:179–187.
- Jones-Jordan LA, Sinnott LT, Chu RH, et al. Myopia progression as a function of sex, age, and ethnicity. Invest Ophthalmol Vis Sci. 2021;62(10):36.
- Luong TQ, Shu Y-H, Modjtahedi BS, et al. Racial and ethnic differences in myopia progression in a large, diverse cohort of pediatric patients. Invest Ophthalmol Vis Sci. 2020;61:20.
- Zadnik K, Sinnott LT, Cotter SA, et al. Prediction of Juvenile-Onset Myopia. JAMA Ophthalmol. 2015;133:683-689.
- Jones-Jordan LA, Sinnott LT, Manny RE, et al. Early Childhood Refractive Error and Parental History of Myopia as Predictors of Myopia. Invest Ophthalmol Vis Sci. 2010;51:115–121.
- Hu Y, Ding X, Guo X, et al. Association of Age at Myopia Onset With Risk of High Myopia in Adulthood in a 12-Year Follow-up of a Chinese Cohort. JAMA Ophthalmol. 2020;138:1129-1134.
- Xiong S, Sankaridurg P, Naduvilath T, et al. Time spent in outdoor activities in relation to myopia prevention and control: a meta-analysis and systematic review. Acta Ophthalmol. 2017: 95: 551–566.
- Dhakal R, Shah R, Huntjens B, et al. Time spent outdoors as an intervention for myopia prevention and control in children: an overview of systematic reviews. Ophthalmic Physiol Opt. 2022;00:1–14.
- Parssinen O, and Kauppinen M. Associations of near work time, watching TV, outdoors time, and parents’ myopia with myopia among school children based on 38-year-old historical data. Acta Ophthalmol.2022;100:e430-e438.
- Tideman JWL, Polling JR, Vingerling JR, et al. Axial length growth and the risk of developing myopia in European children. Acta Ophthalmol. 2018: 96: 301–309.
- Diez PS, Yang L-H, Lu M-X, et al. Growth curves of myopia-related parameters to clinically monitor the refractive development in Chinese schoolchildren. Graefe’s Arch Clin and Exp Ophthalmology. 2019;257:1045–1053.
- Klaver CCW, & Polling JR; Erasmus Myopia Research Group. Myopia management in the Netherlands. Ophthalmic Physiol Opt. 2020; 40: 230–240.
