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Original Investigation |

Secular Trends of Reduced Visual Acuity From 1985 to 2010 and Disease Burden Projection for 2020 and 2030 Among Primary and Secondary School Students in China FREE

Hong-Peng Sun, PhD1; Ang Li, BSc1; Yong Xu, MSc1; Chen-Wei Pan, MD, PhD1
[+] Author Affiliations
1School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu, China
JAMA Ophthalmol. 2015;133(3):262-268. doi:10.1001/jamaophthalmol.2014.4899.
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Published online

Importance  Understanding the burden and trends of reduced visual acuity (VA), a proxy measure for myopia, is essential to guide future health care and clinical management in China.

Objectives  To describe the secular trends from 1985 to 2010, correlate the prevalence of reduced VA among children and adolescents with population density, and project the burden of reduced VA in China in 2020 and 2030.

Design  The National Survey on the Constitution and Health of Chinese Students conducted from 1985 to 2010, including 6 repeated surveys with a 3-stage clustering sampling strategy.

Setting  Mainland China.

Participants  Primary and secondary school students 7 to 18 years of age were randomly selected from 30 of 31 mainland provinces, excluding Tibet.

Main Outcomes and Measures  Unaided distance VA was measured using a retroilluminated logMAR chart with tumbling-E optotypes. World Population Prospects data (the 2012 revision from the Population Division of the Department of Economic and Social Affairs of the United Nations) were used to project the number of people affected by reduced VA in 2020 and 2030.

Results  This analysis included 725 423, 142 655, 206 601, 219 663, 234 377, and 215 308 students in 1985, 1991, 1995, 2000, 2005, and 2010, respectively. The overall prevalence of reduced VA was 28.6% (95% CI, 28.4%-28.7%) in 1985, 38.6% (95% CI, 38.3%-38.8%) in 1991, 41.0% (95% CI, 40.8%-41.2%) in 1995, 38.5% (95% CI, 38.3%-38.7%) in 2000, 49.5% (95% CI, 49.3%-49.7%) in 2005, and 56.8% (95% CI, 56.6%-57.0%) in 2010. Girls were more susceptible than boys to having reduced VA (odds ratio, 1.38 [95% CI, 1.35-1.40]), and reduced VA was more prevalent in urban areas than in rural areas (odds ratio, 1.84 [95% CI, 1.81-1.87]). Reduced VA was not significantly associated with population density (P = .11). The projected numbers of cases with reduced VA are about 152.4 million (95% CI, 151.9-152.9 million) in 2020, increasing to 180.4 million (95% CI, 179.8-181.2 million) in 2030 among students who are 7 to 18 years of age in mainland China.

Conclusions and Relevance  There was an increasing trend of reduced VA in both urban and rural areas from 1985 to 2010 in China. Although reduced unaided distance VA is not equal to visual impairment, these summary data are helpful in designing strategies for eye care and health services in China, which may also have public health implications for other developing countries whose economies are growing rapidly.

Figures in this Article

Myopia is an important but often underestimated health problem associated with a great socioeconomic burden13 and various vision-threatening ocular complications.48 Recent epidemiologic studies have demonstrated that the prevalence of myopia has reached epidemic levels in some urban Asian communities.9 For example, the prevalence of myopia among teenagers has been reported to be about 81% in Singapore,10 86% in Taiwan,11 96% in Seoul, Korea,12 and 95% in Shanghai, China.13

Unaided visual acuity (VA) has been widely used as a proxy measure for myopia in children in previous studies1416 and has achieved a satisfactory sensitivity and specificity profile for myopia screening. For example, a myopia screening test in Singapore found that using a referral criterion of VA worse than or equal to 0.28 logMAR in at least 1 eye achieved a sensitivity of 72% (95% CI, 68%-76%) and a specificity of 97% (95% CI, 95%-98%).17 Similarly, myopia was found to have the highest sensitivity and specificity of any of the refractive errors for detection using VA (97.8% and 97.1%, respectively) in Australian school children.18 Among Chinese children in Guangzhou, the rates of reduced VA were closely correlated with the prevalence of myopia measured by cycloplegic autorefraction reported in a population-based study16 of the same year, with a correlation coefficient of 0.992. These results indicate that VA data may be useful for predicting the prevalence of myopia in large populations undergoing myopia screening examinations because cycloplegic refraction is not feasible.

China is the world’s most populous country and has had a booming economy for the past few decades. Although data on the refractive errors and visual impairment of children and adolescents in China have been reported in various epidemiologic studies,1924 and considering the huge economic and health-related disparities seen in the different parts of the country, these sporadic estimates do not reflect the whole picture of the nationwide burden and trends. In addition, variations in methodological issues, such as using different sampling strategies and refraction methods, may also make it difficult to compare the results among these individual studies. Population-based studies have also shown that more than 90% of the cases of poor vision among school children in China are due to uncorrected refractive error, almost exclusively myopia.20,21 Therefore, a systematic nationwide surveillance of the Chinese population based on unaided VA measurements is a useful approach for understanding the secular trends of reduced VA in different parts of China and could further provide an early warning of an epidemic of myopia in this world’s most populous country. In addition, to our knowledge, there have been no studies that have systematically compared the burden of this condition across areas with different population densities, which, from a public health perspective, would be important for planning health care policy and allocating appropriate resources.

The objectives of this effort are (1) to estimate the secular trends of reduced VA in Chinese children and adolescents 7 to 18 years of age on a national level from 1985 to 2010, (2) to correlate the prevalence of reduced VA among children and adolescents with population density, and (3) to project the burden of reduced VA among children and adolescents 7 to 18 years of age in 2020 and 2030 in mainland China.

Study Population and Sampling Strategy

The National Survey on the Constitution and Health of Chinese Students (NSCHCS), conducted once every 5 years since 1985, is a series of multistage, cross-sectional, nationwide surveys aimed at estimating the nationwide and area-specific burdens of common health problems of children and adolescents 7 to 18 years of age in mainland China. We performed the analysis using data obtained from previous surveys conducted in 1985, 1991, 1995, 2000, 2005, and 2010. The study methods of the NSCHCS have been described elsewhere.25 In brief, all study participants were primary and secondary school students 7 to 18 years of age who were randomly selected from 30 of 31 mainland provinces, excluding Tibet (the only province where Han Chinese do not constitute an ethnic majority). Each province was treated as a cluster, and province-wide samples of students were selected by the local institutes of school health during a 3-stage clustering process.

In the first sampling stage, the study participants in each province were classified by sex and region (urban vs rural), and each of the 4 groups consisted of equal numbers of individuals from 3 classes based on socioeconomic status (ie, upper, middle, or lower class). These classes were defined using 5 indices created in 1985: the regional gross domestic product, the total yearly income per capita, the average food consumption per capita, the natural growth rate of the population, and the regional social-welfare index.

During the second sampling stage, 3 urban and 3 rural residential areas were randomly selected. Several primary and secondary schools were randomly selected from a list compiled by each area’s educational committee. During the third sampling stage, a list of students from grade 1 to grade 12 was compiled, and 2 or 3 classes (depending on their size) from each grade were randomly selected. The sampling strategies were the same in all of the surveys at different time points. All of the study participants lived in their local areas for at least 1 year and were Han Chinese; this ethnic groups comprises 92.7% of the nationwide population in China. This analysis included 725 423, 142 655, 206 601, 219 663, 234 377, and 215 308 students in 1985, 1991, 1995, 2000, 2005, and 2010, respectively.

Our study was approved by the ethics committee of the Medical College of Soochow University in Suzhou, Jiangsu, China, and followed the tenets of the Declaration of Helsinki. Oral informed consent was obtained from all parents after the nature of the study was explained to them.

VA Measurements

Certified optometrists measured the unaided distance VA for both eyes of students using a retroilluminated logMAR chart with tumbling-E optotypes (Precision Vision) in rooms with an illumination of approximately 500 lux. During the examination, study participants were required to indicate the direction of the E optotype within 5 seconds. Visual acuity measurements began at a distance of 5 m, with the fourth line from the bottom (6/6), using a staircase protocol. If 4 of the 5 optotypes were identified, it was considered as a correct response. The VA of the eye was determined by the lowest line read correctly. If the top line was not read correctly, the study participant was advanced to 2.5 or 1 m. Visual acuity examinations were performed using a uniform protocol throughout the surveys at different time points. Because of limited resources, presenting VA and best-corrected VA were not measured. Reduced VA was defined as VA worse than 6/6. Mildly reduced VA was defined as less than 6/9 but greater than 6/6, moderately reduced VA was defined as less than 6/18 but greater than or equal to 6/9, and severely reduced VA was defined as less than or equal to 6/18.

Statistical Analysis

The prevalence of reduced VA was estimated for the overall sample and then stratified by age, sex, and area (urban vs rural) in different study years. Data of the latest survey in 2010 were used to estimate the cross-sectional associations between reduced VA and population density. Census-based data on population density were retrieved from the Chinese government website (http://www.stats.gov.cn/). A simple linear regression model was constructed to evaluate the association between reduced VA and population density for each province. To project the cases with reduced VA for 2020 and 2030, a logistic regression model was established to estimate the nationwide prevalence for each yearly increase in age for boys and girls: logit (P) = β0 + β1 × age + β2 × sex + β3 × year. The estimated population structures of mainland China in 2020 and 2030 were obtained from World Population Prospects data (the 2012 revision from the Population Division of the Department of Economic and Social Affairs of the United Nations [http://esa.un.org/unpd/wpp/unpp/panel_indicators.htm]). The estimated prevalence of reduced VA was used to calculate the total number of individuals with reduced VA in 2020 and in 2030 by multiplying the age-specific estimated prevalence rates found in the World Population Prospects data.

The Table shows the prevalence of reduced VA stratified by sex and area (urban vs rural). The overall prevalence of reduced VA was 28.6% (95% CI, 28.4%-28.7%) in 1985, 38.6% (95% CI, 38.3%-38.8%) in 1991, 41.0% (95% CI, 40.8%-41.2%) in 1995, 38.5% (95% CI, 38.3%-38.7%) in 2000, 49.5% (95% CI, 49.3%-49.7%) in 2005, and 56.8% (95% CI, 56.6%-57.0%) in 2010. In all surveys at different time points, girls were more susceptible than boys to having reduced VA (all P < .001). Reduced VA was more prevalent in urban areas than in rural areas (all P < .001). For example, in 2010, girls had a higher odds ratio of reduced VA than boys (odds ratio, 1.38 [95% CI, 1.35-1.40]), and the prevalence of reduced VA was also higher in urban areas than in rural ones (odds ratio, 1.84 [95% CI 1.81-1.87]).

Table Graphic Jump LocationTable.  Prevalence of Reduced Visual Acuity in the National Survey on the Constitution and Health of Chinese Studentsa

Study participants were categorized into 4 age groups (7-9, 10-12, 13-15, and 16-18 years). Figure 1 shows the age-specific prevalence of reduced VA in different survey years. In general, there was an increasing trend of reduced VA in all age groups. For example, in 1985, the prevalence was only 8.3% (95% CI, 8.2%-8.4%), 16.6% (95% CI 16.4%-16.8%), 35.8% (95% CI, 35.5%-36.0%), and 50.8% (95% CI, 50.6%-51.1%) for children in the age groups of 7 to 9 years, 10 to 12 years, 13 to 15 years, and 16 to 18 years, respectively. In 2010, these figures were 31.8% (95% CI, 31.6%-32.0%), 47.9% (95% CI, 47.7%-48.1%), 67.5% (95% CI, 67.2%-67.8%), and 79.3% (95% CI, 79.0%-79.6%), respectively. Reduced VA was more prevalent among older children than among younger children in all surveys at different time points (P < .001). In addition, there was an increasing trend of severely reduced VA over the past 25 years for all age groups (Figure 2).

Place holder to copy figure label and caption
Figure 1.
Prevalence of Reduced Visual Acuity in China by Age Group From 1985 to 2010

Reduced visual acuity was defined as worse than 6/6.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
Percentages of Students With Mildly, Moderately, and Severely Reduced Visual Acuity in 1985 and 2010

Mildly reduced visual acuity was defined as less than 6/9 but greater than 6/6, moderately reduced visual acuity was defined as less than 6/18 but greater than or equal to 6/9, and severely reduced visual acuity was defined as less than or equal to 6/18.

Graphic Jump Location

Figure 3 shows the correlation of the prevalence of reduced VA with population density in 2010. The relationship between population density and the prevalence of reduced VA was positive but did not reach statistical significance (regression coefficient = 3.6 × 10−5; P = .11).

Place holder to copy figure label and caption
Figure 3.
Association Between Population Density and Reduced Visual Acuity

Census-based data on population density in 2010 were used.

Graphic Jump Location

The projected numbers of children and adolescents 7 to 18 years of age with reduced VA in 2020 and 2030 are shown in Figure 4. For the year 2020, the projected number of cases with reduced VA will be about 152.4 million (95% CI, 151.9-152.9 million), increasing to 180.4 million (95% CI, 179.8-181.2 million) in 2030, with the largest number being adolescents 15 to 18 years of age. There may be more boys than girls affected by reduced VA in 2020 and 2030.

Place holder to copy figure label and caption
Figure 4.
Projected Number of Students With Reduced Visual Acuity in 2020 and 2030 in China

Reduced visual acuity was defined as worse than 6/6.

Graphic Jump Location

The NSCHCS showed that the nationwide burden of reduced VA, a proxy measure for myopia, had increased among children and adolescents from 1985 to 2010 in mainland China, and this was accompanied by the rapid development in the economy in recent decades. The projected number of children and adolescents 7 to 18 years of age affected by reduced VA is approximately 152 million in 2020 and approximately 180 million in 2030. These data are helpful in designing strategies for eye care and health services in China, which may also have public health implications for other developing countries with rapid economic growth.

Although cycloplegic refraction was not measured owing to limited resources, the observed increasing trends over the past 25 years are largely due to the increasing prevalence of myopia, considering the validation of unaided VA as a predictor for myopia in previous studies. In China, visual impairment among school-aged children is commonly caused by uncorrected refractive errors, especially myopia.20,21 During China’s economic development and urbanization, numerous environmental exposures would have been changed, resulting in increasing myopia rates. However, the exact factors contributing to the increasing trend of reduced VA or myopia remain unclear. In other urban Asian communities, such as Singapore, the increasing prevalence of myopia among different generations was mainly due to intensive schooling that is associated with more time spent doing homework and less time spent outdoors.26 This may also be happening in mainland China, where the school system is becoming more and more competitive, with an emphasis in recent decades on early educational achievements and passing examinations.

For example, the college entrance examination in China is extremely competitive, and adolescents 16 to 18 years of age are usually at the preparation stage of this examination. They have to spend more time doing homework every day and less time playing outdoors, which results in a sedentary lifestyle. Ji et al25 reported that 84.6% of the senior high school students in China have little or no daily physical activity. In the past, these same type of students may have been exposed to less intensive schooling and were less likely to receive preschool education compared with their counterparts born later. In addition, with the development of information technology, children and adolescents are spending more and more time using modern digital products such as computers and smartphones, which may be harmful to their eyes. Ji et al25 reported that, in China, 34.3% of secondary school students spent 2 hours or more per day (and 13.5% spent ≥4 h/d) watching television, 21.2% of primary school students spent 2 hours or more per day (and 3.3% spent ≥4 h/d) playing electronic games, and 25.6% of senior high school students spent 2 hours or more per day (and 5.5% spent ≥4 h/d) on the Internet.

The major strength of our study is the availability of the nationwide data collected using this same study protocol over a time period of 25 years. Nevertheless, the major limitation of our study should be acknowledged. Cycloplegic refraction is the gold standard of measurement for myopia in children and adolescents and was not performed in the NSCHCS. Given that the link between VA and myopia is not simple, using reduced VA as a proxy measure for myopia may not be accurate. However, it is a great challenge to perform cycloplegic refraction in a 25-year nationwide survey in a large and populous country such as China. So even though we did not perform cycloplegic refraction, the NSCHCS data are useful for understanding the epidemiology of myopia in mainland China. In addition, the protocol for the measurement of VA was a bit different from the one used in the Refractive Error Study in Children, and the definition of reduced VA in our study was not in conformity with the World Health Organization (WHO) definition.

The definition in this analysis should not be confused with WHO definitions of visual impairment, which are based on a best-corrected VA of less than 6/18 in the best eye. Our definition of moderately and severely reduced unaided VA included the WHO categories of moderate and severe visual impairment and blindness, but was even broader. Our definitions of mildly and moderately reduced VA are not visual impairment under WHO definitions. These variations in methodological issues may reduce the possibility of comparisons between our study and others. Finally, the projection of reduced VA was based on the definition of a VA of less than 6/6. In fact, many children with this level of vision may not really have any disability. Therefore, our projection for disease burden may have exaggerated this issue.

From a public health perspective, these data may have considerable implications for future procedures and practices for myopia. First, China is the most populous country and the second largest economy in the world, with about 20% of the world’s current human population living within its borders. Understanding the burden and trends of reduced VA and myopia is essential to guiding future strategies, interventions, and the clinical management of eye care in this large population. Considering the fact that myopia is hard to prevent under current circumstances, efforts and resources could be channeled by the government and health care agencies toward wide-scale treatment programs in schools to retard the progression of myopia to high myopia and prevent associated visually disabling ocular complications. Second, because clear vision is so critical to many aspects of daily living related to public safety (including driving and the use of electronic devices), health policy makers should be aware of these changes in VA and should appropriately address the health-related inequalities in areas with different levels of socioeconomic status in China. Third, these data also have public health implications for other developing countries whose economies are growing rapidly and whose environments have changed dramatically because of urbanization.

In conclusion, these summary data on reduced VA indicate the substantial nationwide burden of myopia among children and adolescents in China, and they provide information to help us understand the effect of the condition and design strategies for eye care and health services. Mainland China may be at an early stage of a myopia epidemic compared with other urban Asian communities. Therefore, myopia may warrant more attention in China and in other developing countries with rapidly growing economies.

Submitted for Publication: August 14, 2014; final revision received October 6, 2014; accepted October 10, 2014.

Corresponding Author: Chen-Wei Pan, MD, PhD, School of Public Health, Medical College of Soochow University, 199 Ren Ai Rd, Suzhou, Jiangsu 215123, China (pcwonly@gmail.com).

Published Online: November 27, 2014. doi:10.1001/jamaophthalmol.2014.4899.

Author Contributions: Dr Pan had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Sun, Xu.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Sun, Xu, Pan.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Sun, Li, Pan.

Administrative, technical, or material support: Xu, Pan.

Study supervision: Xu, Pan.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE form for disclosure of potential conflicts of interest and none were reported.

Funding/Support: This study was supported by the China Postdoctoral Science Foundation (grant 2013M531405).

Role of the Funder/Sponsor: The China Postdoctoral Science Foundation had no role in the design and conduct of the study; collection, management, analysis, or interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Vitale  S, Cotch  MF, Sperduto  R, Ellwein  L.  Costs of refractive correction of distance vision impairment in the United States, 1999-2002. Ophthalmology. 2006;113(12):2163-2170.
PubMed   |  Link to Article
Rein  DB, Zhang  P, Wirth  KE,  et al.  The economic burden of major adult visual disorders in the United States. Arch Ophthalmol. 2006;124(12):1754-1760.
PubMed   |  Link to Article
Zheng  YF, Pan  CW, Chay  J, Wong  TY, Finkelstein  E, Saw  SM.  The economic cost of myopia in adults aged over 40 years in Singapore. Invest Ophthalmol Vis Sci. 2013;54(12):7532-7537.
PubMed   |  Link to Article
Pan  CW, Cheung  CY, Aung  T,  et al.  Differential associations of myopia with major age-related eye diseases: the Singapore Indian Eye Study. Ophthalmology. 2013;120(2):284-291.
PubMed   |  Link to Article
Saw  SM, Gazzard  G, Shih-Yen  EC, Chua  WH.  Myopia and associated pathological complications. Ophthalmic Physiol Opt. 2005;25(5):381-391.
PubMed   |  Link to Article
Pan  CW, Cheng  CY, Saw  SM, Wang  JJ, Wong  TY.  Myopia and age-related cataract: a systematic review and meta-analysis. Am J Ophthalmol. 2013;156(5):1021-1033.
PubMed   |  Link to Article
Chang  L, Pan  CW, Ohno-Matsui  K,  et al.  Myopia-related fundus changes in Singapore adults with high myopia. Am J Ophthalmol. 2013;155(6):991-999.
PubMed   |  Link to Article
Pan  CW, Boey  PY, Cheng  CY,  et al.  Myopia, axial length, and age-related cataract: the Singapore Malay eye study. Invest Ophthalmol Vis Sci. 2013;54(7):4498-4502.
PubMed   |  Link to Article
Pan  CW, Ramamurthy  D, Saw  SM.  Worldwide prevalence and risk factors for myopia. Ophthalmic Physiol Opt. 2012;32(1):3-16.
PubMed   |  Link to Article
Pan  CW, Zheng  YF, Anuar  AR,  et al.  Prevalence of refractive errors in a multiethnic Asian population: the Singapore epidemiology of eye disease study. Invest Ophthalmol Vis Sci. 2013;54(4):2590-2598.
PubMed   |  Link to Article
Lee  YY, Lo  CT, Sheu  SJ, Lin  JL.  What factors are associated with myopia in young adults? a survey study in Taiwan military conscripts. Invest Ophthalmol Vis Sci. 2013;54(2):1026-1033.
PubMed   |  Link to Article
Jung  SK, Lee  JH, Kakizaki  H, Jee  D.  Prevalence of myopia and its association with body stature and educational level in 19-year-old male conscripts in Seoul, South Korea. Invest Ophthalmol Vis Sci. 2012;53(9):5579-5583.
PubMed   |  Link to Article
Sun  J, Zhou  J, Zhao  P,  et al.  High prevalence of myopia and high myopia in 5060 Chinese university students in Shanghai. Invest Ophthalmol Vis Sci. 2012;53(12):7504-7509.
PubMed   |  Link to Article
Tay  MT, Au Eong  KG, Ng  CY, Lim  MK.  Myopia and educational attainment in 421,116 young Singaporean males. Ann Acad Med Singapore. 1992;21(6):785-791.
PubMed
Au Eong  KG, Tay  TH, Lim  MK.  Education and myopia in 110,236 young Singaporean males. Singapore Med J. 1993;34(6):489-492.
PubMed
Xiang  F, He  M, Zeng  Y, Mai  J, Rose  KA, Morgan  IG.  Increases in the prevalence of reduced visual acuity and myopia in Chinese children in Guangzhou over the past 20 years. Eye (Lond). 2013;27(12):1353-1358.
PubMed   |  Link to Article
Tong  L, Saw  SM, Tan  D,  et al.  Sensitivity and specificity of visual acuity screening for refractive errors in school children. Optom Vis Sci. 2002;79(10):650-657.
PubMed   |  Link to Article
Leone  JF, Mitchell  P, Morgan  IG, Kifley  A, Rose  KA.  Use of visual acuity to screen for significant refractive errors in adolescents: is it reliable? Arch Ophthalmol. 2010;128(7):894-899.
PubMed   |  Link to Article
Zhao  J, Pan  X, Sui  R, Munoz  SR, Sperduto  RD, Ellwein  LB.  Refractive Error Study in Children: results from Shunyi District, China. Am J Ophthalmol. 2000;129(4):427-435.
PubMed   |  Link to Article
He  M, Huang  W, Zheng  Y, Huang  L, Ellwein  LB.  Refractive error and visual impairment in school children in rural southern China. Ophthalmology. 2007;114(2):374-382.
PubMed   |  Link to Article
He  M, Zeng  J, Liu  Y, Xu  J, Pokharel  GP, Ellwein  LB.  Refractive error and visual impairment in urban children in southern china. Invest Ophthalmol Vis Sci. 2004;45(3):793-799.
PubMed   |  Link to Article
Pi  LH, Chen  L, Liu  Q,  et al.  Prevalence of eye diseases and causes of visual impairment in school-aged children in western China. J Epidemiol. 2012;22(1):37-44.
PubMed   |  Link to Article
Li  Z, Xu  K, Wu  S,  et al.  Population-based survey of refractive error among school-aged children in rural northern China: the Heilongjiang eye study. Clin Experiment Ophthalmol. 2014;42(4):379-384.
PubMed   |  Link to Article
Li  SM, Liu  LR, Li  SY,  et al; Anyang Childhood Eye Study Group.  Design, methodology and baseline data of a school-based cohort study in central China: the Anyang Childhood Eye Study. Ophthalmic Epidemiol. 2013;20(6):348-359.
PubMed   |  Link to Article
Ji  CY, Chen  TJ; Working Group on Obesity in China (WGOC).  Empirical changes in the prevalence of overweight and obesity among Chinese students from 1985 to 2010 and corresponding preventive strategies. Biomed Environ Sci. 2013;26(1):1-12.
PubMed
Pan  CW, Zheng  YF, Wong  TY,  et al.  Variation in prevalence of myopia between generations of migrant Indians living in Singapore. Am J Ophthalmol. 2012;154(2):376-381.
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.
Prevalence of Reduced Visual Acuity in China by Age Group From 1985 to 2010

Reduced visual acuity was defined as worse than 6/6.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
Percentages of Students With Mildly, Moderately, and Severely Reduced Visual Acuity in 1985 and 2010

Mildly reduced visual acuity was defined as less than 6/9 but greater than 6/6, moderately reduced visual acuity was defined as less than 6/18 but greater than or equal to 6/9, and severely reduced visual acuity was defined as less than or equal to 6/18.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.
Association Between Population Density and Reduced Visual Acuity

Census-based data on population density in 2010 were used.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 4.
Projected Number of Students With Reduced Visual Acuity in 2020 and 2030 in China

Reduced visual acuity was defined as worse than 6/6.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable.  Prevalence of Reduced Visual Acuity in the National Survey on the Constitution and Health of Chinese Studentsa

References

Vitale  S, Cotch  MF, Sperduto  R, Ellwein  L.  Costs of refractive correction of distance vision impairment in the United States, 1999-2002. Ophthalmology. 2006;113(12):2163-2170.
PubMed   |  Link to Article
Rein  DB, Zhang  P, Wirth  KE,  et al.  The economic burden of major adult visual disorders in the United States. Arch Ophthalmol. 2006;124(12):1754-1760.
PubMed   |  Link to Article
Zheng  YF, Pan  CW, Chay  J, Wong  TY, Finkelstein  E, Saw  SM.  The economic cost of myopia in adults aged over 40 years in Singapore. Invest Ophthalmol Vis Sci. 2013;54(12):7532-7537.
PubMed   |  Link to Article
Pan  CW, Cheung  CY, Aung  T,  et al.  Differential associations of myopia with major age-related eye diseases: the Singapore Indian Eye Study. Ophthalmology. 2013;120(2):284-291.
PubMed   |  Link to Article
Saw  SM, Gazzard  G, Shih-Yen  EC, Chua  WH.  Myopia and associated pathological complications. Ophthalmic Physiol Opt. 2005;25(5):381-391.
PubMed   |  Link to Article
Pan  CW, Cheng  CY, Saw  SM, Wang  JJ, Wong  TY.  Myopia and age-related cataract: a systematic review and meta-analysis. Am J Ophthalmol. 2013;156(5):1021-1033.
PubMed   |  Link to Article
Chang  L, Pan  CW, Ohno-Matsui  K,  et al.  Myopia-related fundus changes in Singapore adults with high myopia. Am J Ophthalmol. 2013;155(6):991-999.
PubMed   |  Link to Article
Pan  CW, Boey  PY, Cheng  CY,  et al.  Myopia, axial length, and age-related cataract: the Singapore Malay eye study. Invest Ophthalmol Vis Sci. 2013;54(7):4498-4502.
PubMed   |  Link to Article
Pan  CW, Ramamurthy  D, Saw  SM.  Worldwide prevalence and risk factors for myopia. Ophthalmic Physiol Opt. 2012;32(1):3-16.
PubMed   |  Link to Article
Pan  CW, Zheng  YF, Anuar  AR,  et al.  Prevalence of refractive errors in a multiethnic Asian population: the Singapore epidemiology of eye disease study. Invest Ophthalmol Vis Sci. 2013;54(4):2590-2598.
PubMed   |  Link to Article
Lee  YY, Lo  CT, Sheu  SJ, Lin  JL.  What factors are associated with myopia in young adults? a survey study in Taiwan military conscripts. Invest Ophthalmol Vis Sci. 2013;54(2):1026-1033.
PubMed   |  Link to Article
Jung  SK, Lee  JH, Kakizaki  H, Jee  D.  Prevalence of myopia and its association with body stature and educational level in 19-year-old male conscripts in Seoul, South Korea. Invest Ophthalmol Vis Sci. 2012;53(9):5579-5583.
PubMed   |  Link to Article
Sun  J, Zhou  J, Zhao  P,  et al.  High prevalence of myopia and high myopia in 5060 Chinese university students in Shanghai. Invest Ophthalmol Vis Sci. 2012;53(12):7504-7509.
PubMed   |  Link to Article
Tay  MT, Au Eong  KG, Ng  CY, Lim  MK.  Myopia and educational attainment in 421,116 young Singaporean males. Ann Acad Med Singapore. 1992;21(6):785-791.
PubMed
Au Eong  KG, Tay  TH, Lim  MK.  Education and myopia in 110,236 young Singaporean males. Singapore Med J. 1993;34(6):489-492.
PubMed
Xiang  F, He  M, Zeng  Y, Mai  J, Rose  KA, Morgan  IG.  Increases in the prevalence of reduced visual acuity and myopia in Chinese children in Guangzhou over the past 20 years. Eye (Lond). 2013;27(12):1353-1358.
PubMed   |  Link to Article
Tong  L, Saw  SM, Tan  D,  et al.  Sensitivity and specificity of visual acuity screening for refractive errors in school children. Optom Vis Sci. 2002;79(10):650-657.
PubMed   |  Link to Article
Leone  JF, Mitchell  P, Morgan  IG, Kifley  A, Rose  KA.  Use of visual acuity to screen for significant refractive errors in adolescents: is it reliable? Arch Ophthalmol. 2010;128(7):894-899.
PubMed   |  Link to Article
Zhao  J, Pan  X, Sui  R, Munoz  SR, Sperduto  RD, Ellwein  LB.  Refractive Error Study in Children: results from Shunyi District, China. Am J Ophthalmol. 2000;129(4):427-435.
PubMed   |  Link to Article
He  M, Huang  W, Zheng  Y, Huang  L, Ellwein  LB.  Refractive error and visual impairment in school children in rural southern China. Ophthalmology. 2007;114(2):374-382.
PubMed   |  Link to Article
He  M, Zeng  J, Liu  Y, Xu  J, Pokharel  GP, Ellwein  LB.  Refractive error and visual impairment in urban children in southern china. Invest Ophthalmol Vis Sci. 2004;45(3):793-799.
PubMed   |  Link to Article
Pi  LH, Chen  L, Liu  Q,  et al.  Prevalence of eye diseases and causes of visual impairment in school-aged children in western China. J Epidemiol. 2012;22(1):37-44.
PubMed   |  Link to Article
Li  Z, Xu  K, Wu  S,  et al.  Population-based survey of refractive error among school-aged children in rural northern China: the Heilongjiang eye study. Clin Experiment Ophthalmol. 2014;42(4):379-384.
PubMed   |  Link to Article
Li  SM, Liu  LR, Li  SY,  et al; Anyang Childhood Eye Study Group.  Design, methodology and baseline data of a school-based cohort study in central China: the Anyang Childhood Eye Study. Ophthalmic Epidemiol. 2013;20(6):348-359.
PubMed   |  Link to Article
Ji  CY, Chen  TJ; Working Group on Obesity in China (WGOC).  Empirical changes in the prevalence of overweight and obesity among Chinese students from 1985 to 2010 and corresponding preventive strategies. Biomed Environ Sci. 2013;26(1):1-12.
PubMed
Pan  CW, Zheng  YF, Wong  TY,  et al.  Variation in prevalence of myopia between generations of migrant Indians living in Singapore. Am J Ophthalmol. 2012;154(2):376-381.
PubMed   |  Link to Article

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