Purpose: To describe the ethnic variations in the prevalence and risk factors for undercorrected refractive error and its impact on vision-specific functioning (VF) in a multiethnic Asian population.
Methods: A total of 3353 Chinese, 3400 Indians, and 3280 Malays in Singapore participated in this population-based cross-sectional study. Distance presenting visual acuity (VA) was measured using a logarithm of the minimum angle of resolution number chart. Best-corrected VA was assessed using the same test protocol as presenting VA. Undercorrected refractive error was defined as an improvement of at least 0.2 logarithm of the minimum angle of resolution (two lines equivalent) in the best-corrected VA compared with the presenting VA in the better eye when presenting VA was less than 20/40 in the better eye. The VF-11 questionnaire measured participants’ VF. Multivariate linear regression was performed to assess the impact of undercorrected refractive error on the overall VF score.
Results: Regardless of ethnicity, participants with undercorrected refractive error had a reduction in VF score compared to those with normal vision in both eyes. The overall prevalence of undercorrected refractive error was highest in Indians (25.1%), followed by Malays (22.2%) and Chinese (19.7%). Undercorrected refractive error was less common in spectacles or contact lenses wearers than in non–spectacle wearers or non–contact lenses wearers. Adults with mild to moderate refractive errors were most likely to have undercorrected refractive error (p < 0.001). In multivariate analysis, increasing age (p < 0.001), Indian race (p < 0.001), lower education level (p < 0.001) or poorer housing (p < 0.001), having refractive errors (p < 0.001), and not wearing optical corrections (p < 0.001) were significantly associated with increasing undercorrected refractive error.
Conclusions: In Singapore, undercorrected refractive error is most prevalent in Indians and least prevalent in Chinese. The impact of undercorrected refractive error on VF was consistent across all three ethnicities. There may be higher barriers to visual correction among Malays or Indians compared with Chinese in Singapore.
Singapore Eye Research Institute (C-WP, PP-CC, TYW, Y-FZ, MC, S-MS, ELL, C-YC); Saw Swee Hock School of Public Health (C-WP, TYW, S-MS, C-YC) and Department of Ophthalmology (TYW, MC, S-MS, C-YC), Yong Loo Lin School of Medicine, National University of Singapore and National University Health System; and Centre for Quantitative Medicine (C-YC), Office of Clinical Sciences, Duke-NUS Graduate Medical School, Singapore.
Chen-Wei Pan Singapore Eye Research Institute 16 Medical Drive, MD3, Level 5 Singapore 117597 e-mail: firstname.lastname@example.org
Globally, 153 million people older than 5 years are visually impaired as a result of undercorrected refractive error; of these, 8 million are blind.1 As early as in 1997, the World Health Organization has targeted to eliminate avoidable blindness in the world by 2020, with one of the five main priorities being refractive errors.2 However, undercorrected refractive error remains a major cause of visual impairment (VI) and blindness in many countries.3–8 It is especially worthwhile to study the pattern and predictors of undercorrected refractive error in middle aged to elderly adults because severe VI significantly increased the risk of falling and is associated with poor vision-specific functioning (VF).9
Although the prevalence of undercorrected refractive error has been estimated in a few population-based studies,10–14 it is still unclear whether the observed difference in undercorrected refractive error rates is due to ethnic disparity or variations in methodological issues (e.g., inclusion criteria, definitions, and sampling methods). Understanding the ethnic difference in the prevalence of undercorrected refractive error would be of great importance for many countries, in particular for those with multiethnic populations, where a key objective of public health system reform is to redress ethnic inequality. Despite established health disparity among ethnic groups, there has been a lack of study exploring differences in under corrected refractive error across different Asian ethnic groups. In Asia, Chinese people are thought to have a higher prevalence of myopia and astigmatism than the other ethnic groups, but it is unclear if the prevalence of undercorrected refractive error is also higher in Chinese people.15–17 Therefore, there is a need to elucidate the interethnic patterns of undercorrected refractive error in newly urbanized Asian communities, where an “epidemic” of refractive errors, especially myopia, has been observed.18,19
In addition, VI has a negative impact on daily living activities such as mobility, participation in social events, and other domains of quality of life.20 It has been suggested that disease-specific interventions are required in reducing the adverse impact of VI on daily activities.21 Although undercorrected refractive error is a major cause of VI,3–8 whether there are ethnic differences of the impact of undercorrected refractive error on VF remains unclear. Therefore, it is important to investigate whether undercorrected refractive error has a different impact on VF across ethnic groups.
Singapore is an urbanized city state consisting of immigrants of Chinese, Malaysian, and Indian ancestries, where optometric services are not part of the government health subsidy plan. Patients with refractive errors have to use their own funds to obtain optical corrections. In this study, we assessed the ethnic variations in the prevalence and risk factors of undercorrected refractive error and its impact on VF in a multiethnic Asian population older than 40 years living in Singapore.
The Singapore Epidemiology of Eye Diseases program (SEED) comprises 10,033 Singapore adults of 3280 Malays, 3400 Indians, and 3353 Chinese older than 40 years. The SEED cohort is a combination of SiMES (Malay cohort) and SICC (Indian and Chinese cohorts), and the detailed methods of these studies have been published elsewhere.22,23 In brief, an age-stratified random sampling was used to select ethnic Malays, Indians, and Chinese older than 40 years living in Singapore. The overall response rate for SEED was 75.6%, with the rate being 78.7% for Malays, 75.6% for Indians, and 72.8% for Chinese. Participants of the study were younger than nonparticipants were (p < 0.001), but there was no sex difference (p = 0.68).
This study was approved by the Singapore Eye Research Institute Institutional Review Board, and the conduct of the studies adhered to the Declaration of Helsinki.
All study participants were required to bring their optical corrections (i.e., spectacles or contact lenses). Subjects who had optical corrections but did not bring them to the clinic were categorized as non–spectacle wearers or non–contact lens wearers because they may not use their optical corrections habitually if they did not bring their optical corrections with them to the clinic. Presenting visual acuity (VA) was monocularly measured with a logarithm of the minimum angle of resolution (logMAR) number chart (Lighthouse International, New York, NY) at a distance of 4 m, with the participants wearing their “walk-in” optical correction (spectacles or contact lenses), if any. A number chart was used for participants who were illiterate in the Latin-script alphabet. If no numbers were read at 4 m, the participant was moved to 3, 2, or 1 m, consecutively.24 If no numbers were identified on the chart, VA was assessed as counting fingers, hand movements, perception of light, or no perception of light.
Noncycloplegic refractive error was determined by subjective refraction by study optometrists. Autorefraction measurements (Auto Ref-Keratometer RK-5; Canon, Tokyo, Japan) were used as the starting point, and refinement was performed until the best-corrected VA was obtained. Best-corrected VA was monocularly assessed and recorded in logMAR scores using the same test protocol as that used for presenting VA. Undercorrected refractive error data were available for 10,014 subjects (3262 Malays, 3400 Indians, and 3352 Chinese) because VA measurement could not be performed in 19 subjects. Slitlamp examination (model BQ-900; Haag-Streit, Koeniz, Switzerland) was performed by trained research ophthalmologists (Y.F.Z. and M.C.) after pupil dilation.
Refractive error was expressed as spherical equivalent (SE = sphere +1/2 cylinder). Myopia was defined as an SE of more than −0.50 D, hyperopia as an SE of more than +0.50 D, and astigmatism as cylinder more than −0.50 D based on the eye with better presenting VA. Undercorrected refractive error was defined as an improvement of at least 0.2 logMAR (equivalent to two lines) in best-corrected VA compared with presenting VA in the eye with better presenting VA when presenting VA was worse than 20/40 in the better eye.
Risk Factors Assessment
A detailed interviewer-administered questionnaire was used to collect data including educational level, housing type, lifestyle risk factors (e.g., smoking and alcohol intake), and country of birth. Blood pressure was measured with a digital automatic blood pressure monitor (Dinamap model Pro Series DP110X-RW, 100V2; GE Medical Systems Information Technologies, Inc., Milwaukee, WI) after the participants were seated for at least 5 minutes. Hypertension was defined as systolic blood pressure more than 140 mm Hg or diastolic blood pressure more than 90 mm Hg or self-reported history of hypertension. Diabetes was defined as a self-reported previous diagnosis of the disease, use of diabetic medication, or hemoglobin A1c (HbA1c) of 6.5% or greater (American Diabetes Association’s new diagnostic criterion for undiagnosed diabetes).25 Cataract was defined using the Lens Opacities Classification System (LOCS) III26 based on the eye with better presenting VA.
Vision-Specific Function Assessment
The VF-11 questionnaire was used to assess VF in participants. The VF-11 was administered face-to-face by trained research assistants fluent in English, Tamil, Malay, and Chinese.27 The interviewers were masked to the results of the VA and eye examination. All 11 questions assessed the level of difficulty in performing certain vision-oriented activities. Rasch analysis, a modern psychometric technique, assessed the reliability, validity, and measurement characteristics of the VF-11. The ordinal scores in the VF-11 were transformed into interval-level Rasch scores, expressed in log of odds units or logits.
The prevalence of undercorrected refractive error was estimated for the overall population and for age groups and sex within each racial group. The prevalence of undercorrected refractive error was also estimated in adults who did or did not wear spectacle or contact lenses. Multiple logistic regression models were developed with undercorrected refractive error as the dichotomous dependent variable and relevant predictors as covariates. If the p value was less than 0.10 in univariate models, these possible predictors were included in multiple logistic regression models, and manual backward stepwise elimination procedures were performed. To determine whether ethnicity modified associations, a logistic regression model was constructed with the interaction between ethnicity and each risk factor, and a likelihood ratio test was performed on the interaction terms. Multivariate linear regression analysis was then performed to assess the impact of undercorrected refractive error on the overall VF Rasch score. All probabilities quoted were two-sided and were considered statistically significant at p < 0.05. Commercially available statistical software was used (SPSS for Windows, version 16; SPSS, Chicago, IL).
Table 1 summarizes the basic characteristics of included study participants in the three major ethnic groups in SEED. In general, Malays had lower education levels, had poorer housing, and were most likely to be affected by hypertension and cataract compared to Indians and Chinese. Of the 10,014 subjects with and without optical corrections in our study, 2238 (20.4%) had undercorrected refractive error.
Table 2 shows the impact of undercorrected refractive error on VF. The mean VF scores in Malays, Indians, and Chinese were 4.08, 4.19, and 4.68, respectively (p < 0.001). In multivariate linear regression models, adjusting for age, sex, education, and systemic comorbidities such as cardiovascular disease and diabetes, VF was independently associated with undercorrected refractive error (regression coefficient = −0.26, 95% confidence interval [CI] = −0.37 to −0.16, p < 0.001). No ethnic variations were found (p for interaction = 0.46). The reduction in VF was consistent across the three ethnic groups.
The prevalence of undercorrected refractive error by age, sex, and ethnicity in the SEED population is summarized in Table 3. The prevalence of undercorrected refractive error was highest in Indians (25.1%), followed by Malays (22.2%) and Chinese (19.7%). In all three ethnic groups, women had a high prevalence of undercorrected refractive error compared with men (24.0% vs. 20.2% for Malays, respectively; 25.4% vs. 24.8% for Indians, respectively; and 20.2% vs.19.2% for Chinese, respectively). Adults aged 40 to 49 years had the lower prevalence of undercorrected refractive error compared with their older counterparts within the respective ethnic groups.
Table 4 further demonstrates the prevalence of undercorrected refractive error in adults who did or did not wear spectacles or contact lenses. The vision was undercorrected in 12.8% of Malays, 14.2% of Indians, and 9.4% of Chinese who wore spectacles or contact lenses, whereas these rates were 27.4%, 33.3%, and 29.4% in non–spectacle wearers or non–contact lenses wearers in the three ethnic groups, which were significantly higher than their counterparts wearing spectacles or contact lenses (all p < 0.001).
In Malays, the proportion of undercorrected refractive error was 28.7% in the adults with myopia only, 31.0% in those with hyperopia only, 22.7% in those with astigmatism only, 37.4% in those with both myopia and astigmatism, and 33.0% in those with both hyperopia and astigmatism. These proportions were 17.7%, 39.3%, 19.6%, 31.5%, and 38.6%, respectively, in Indians and 14.9%, 33.3%, 16.7%, 20.0%, and 29.9%, respectively, in Chinese. Indians were most likely to have undercorrected refractive error in hyperopic refractive status groups, whereas Malays were most likely to have undercorrected refractive error in myopic refractive status groups. The prevalence of undercorrected refractive error was highest in adults with mild to moderate myopia (−0.5D to −3.0D) or hyperopia (+0.5D to +2.0D) (p < 0.001).
Table 5 shows the univariate and multivariate associations of undercorrected refractive error in the study population. In univariate analysis, increasing age, female sex, Malay or Indian race, poorer education level, being born in Singapore, poor housing, the presence of hypertension, the presence of cataract, the presence of refractive errors, and not wearing spectacle or contact lens were significantly associated with a higher prevalence of undercorrected refractive error (all p < 0.05). Other factors such as alcohol consumption, diabetes mellitus, smoking, and living alone were found not to be significantly associated with the prevalence of undercorrected refractive error. In multivariate analysis, increasing age (p < 0.001), Indian race (p < 0.001), lower education level (p = 0.01) or poorer housing (p = 0.001), having refractive errors (p < 0.001), and not wearing spectacle or contact lens (p < 0.001) were significantly associated with an increasing prevalence of undercorrected refractive error. In addition, the association of lower education status with undercorrected refractive error was stronger in Malays and Indians compared with Chinese (p for interaction = 0.03; Fig. 1).
In this multiethnic Asian population of Malays, Indians, and Chinese aged 40 years or older, Indians had the highest, whereas Chinese had the lowest, prevalence of undercorrected refractive error. Age, education level/socioeconomic status, refractive status, and spectacle or contact lens wear are the most important factors associated with undercorrected refractive error. Adults with mild to moderate refractive errors were mostly likely to have undercorrected refractive error. The impact of undercorrected refractive error on VF was significant and consistent among the three ethnic groups, which highlights that adequate refractive error correction, regardless of ethnic groups, will be able to improve VF in people with refractive errors.
To be best of our knowledge, our study is the first one that compared the prevalence of undercorrected refractive error among different ethnic groups using the same definitions and methods to collect data, filling the gap of knowledge in the ethnic difference in undercorrected refractive error. In other published population-based data on undercorrected refractive error, the prevalence was estimated to be 10.2% in Whites in Australia,10 15.1% in Latinos in the United States,11 9.55% in Chinese in Taiwan,12 10.2% in Bengalese,13 and 6.0% in Mexicans in the United States.14 However, it is difficult to compare results across studies because of inherent differences in data collection and definition of undercorrected refractive error. In our study, the prevalence of undercorrected refractive error was highest in Indians and lowest in Chinese of the same age range. The possible reasons include interethnic differences in health awareness and culture. Considering the fact that Chinese have a higher prevalence of refractive errors (myopia and astigmatism) than Malays or Indians in Singapore,28 these data could be interpreted that the percentage of those with identified need for correction of refractive errors among Malays or Indians is higher than that among Chinese in Singapore. Although the three ethnic groups are living in the same health care system, the need for correction is not being identified as well in Malays or Indians as it is in Chinese in Singapore and that there may be higher barriers to correction among Singaporean Malay or Indian adults.
Another important finding of our study is that adults with mild to moderate refractive errors including myopia (−0.5D to −3.0D) or hyperopia (+0.5D to +2.0D) were most likely to be affected by undercorrected refractive error. Many older people with mild to moderate refractive errors, especially hyperopia, may not be aware that distance glasses could improve their vision. Alternatively, they may feel that they can see quite well without glasses or may resist wearing distance glasses, having not needed these in the past. Therefore, the health education programs should be targeted at the high-risk groups such as older Indians with mild to moderate refractive errors and advise them to visit the eye care professional at regular intervals to update their spectacle prescription.
Among the risk factors of undercorrected refractive error in our study population, older age was strongly associated with undercorrected refractive error in this population, confirming the trends reported in other population-based studies.10,11,13,29 This finding may be explained by an increased frailty or poorer general health of older people preventing attendance to an eye care practitioner, suggesting that that older people should get regular ocular examinations to eliminate any VI as a result of undercorrection of refractive errors. However, the age patterns of undercorrected refractive error among different racial groups are a bit different. The increasing trend in undercorrected refractive error prevalence with age is more prominent in Malays (p for trend <0.001) compared with Indians (p for trend = 0.05) or Chinese (p for trend = 0.03). The reason is unclear. There may be a greater gap of knowledge and beliefs of undercorrected refractive error in different generations of Malays compared with Indians or Chinese. Lower socioeconomic status and lower education level were found to be associated with a higher prevalence of undercorrected refractive error. These findings indicate that both perceived costs of attending an eye care practitioner and lack of knowledge of the potential benefits from refractive correction might inhibit many people from seeking assistance. An interesting observation was a significant interaction effect between race and education on undercorrected refractive error, which indicated that the effect of education status on undercorrected refractive error is influenced significantly by a person’s ethnicity. The magnitude of association between educational level and undercorrected refractive error was stronger in Malays or Indians compared with that in Chinese. This suggests a complex relationship between racial factors (e.g., different cultures) and socioeconomic factors (e.g., reflected by education) that are associated with undercorrected refractive error and that require further study. Because undercorrected refractive error was known to be related to the lack of knowledge and awareness of refractive errors, our study suggests that less educated Chinese may have a better knowledge of eye care and lower barriers to vision service compared with their Malay or Indian counterparts.
Another interesting finding from our study is that despite the ethnic differences found in the prevalence of undercorrected refractive error, the impact of the condition on VF was consistent across the three ethnic groups. This type of effect can also be found in other ethnic groups. For instance, one study found that, by adequately correcting undercorrected refractive error in a group of American Indian/Alaskan Natives, their vision-related quality of life significantly improved.30 Our study implies that regardless of the prevalence variations among these three ethnicities, adequate refractive error correction can improve participation in daily living and vision-related functioning across all ethnicities.
Some implications from our study should be noted. First, our study is the first one that collected population-based epidemiological data of undercorrected refractive error in three major Asian ethnic groups living in the same region. During the data collection, we found that Chinese people were more difficult to recruit than Malays or Indians, leading to a relatively lower response rate among Chinese, which may be explained by the different culture backgrounds among the three ethnic groups. The results of our study may be related to many multiethnic countries where a key objective of public health system reform is to redress racial inequality. Second, because vision clarity is so critical for many aspects of daily living related to public safety including driving vehicles and using electronic devices, health policy makers should be aware that undercorrected refractive error should be corrected, at least in people doing vision-related jobs such as bus drivers. The availability of inexpensive, subsidized spectacles may help to increase the uptake and compliance with full optical correction. Last but not least, the nationwide educational programs to educate high-risk groups on refractive error, the effects of refractive error, and the need for regular eye screening will be useful in reducing the rate of undercorrected refractive error. Media campaigns, brochures, health talks incorporated into grassroots community–based activities, and posters in clinics with appropriate educational messages about the correction of refractive error may increase the general level of knowledge in the high-risk groups.
The study’s strengths included a large sample size, a reasonable response rate, the same methods to collect data among different racial groups, and the use of Rasch analysis. There were also some limitations in this study. We were unable to identify the exact explanatory factors for the observed ethnic differences in undercorrected refractive error. We did not collect the information on why subjects with undercorrected refractive error were not using an appropriately prescribed optical correction. Determining why they are not using a prescribed correction may shed some light to the reasons why their visions remain undercorrected. In addition, nonparticipants in the SEED study were older than participants, which may lead to an underestimation of undercorrected refractive error in all ethnic groups. However, we believe this effect on understanding the racial differences in undercorrected refractive error is marginal.
In conclusion, this population-based study of multiethnic adults older than 40 years in Singapore showed that Indians were most likely, whereas Chinese were least likely, to be affected by undercorrected refractive error. Age, education level/socioeconomic status, refractive status, and spectacle or contact lens wear are the most important factors related to undercorrected refractive error. Regardless of ethnicity, undercorrected refractive error had a negative effect on VF, which further emphasizes the importance of adequate refractive error correction in all ethnic groups. These data on the ethnic difference in the patterns of undercorrected refractive error could assist in targeting education and appropriate referral by general practitioners and other primary care providers.
Singapore Eye Research Institute
16 Medical Drive, MD3, Level 5
This study was funded by Biomedical Research Council (08/1/35/19/550) and the National Medical Research Council (STaR/0003/2008), Singapore. None of the authors have proprietary or commercial interest in any materials discussed in the article.
Received April 25, 2013; accepted October 17, 2013.
1. Resnikoff S, Pascolini D, Mariotti SP, Pokharel GP. Global magnitude of visual impairment caused by uncorrected refractive errors in 2004. Bull World Health Organ 2008; 86: 63–70.
2. Thylefors B. A global initiative for the elimination of avoidable blindness. Am J Ophthalmol 1998; 125: 90–3.
3. Zheng Y, Lavanya R, Wu R, Wong WL, Wang JJ, Mitchell P, Cheung N, Cajucom-Uy H, Lamoureux E, Aung T, Saw SM, Wong TY. Prevalence and causes of visual impairment and blindness in an urban Indian population: the Singapore Indian Eye Study. Ophthalmology 2011; 118: 1798–804.
4. Thulasiraj RD, Nirmalan PK, Ramakrishnan R, Krishnadas R, Manimekalai TK, Baburajan NP, Katz J, Tielsch JM, Robin AL. Blindness and vision impairment in a rural south Indian population: the Aravind Comprehensive Eye Survey. Ophthalmology 2003; 110: 1491–8.
5. Murthy GV, Gupta S, Ellwein LB, Munoz SR, Bachani D, Dada VK. A population-based eye survey of older adults in a rural district of Rajasthan: I. Central vision impairment, blindness, and cataract surgery. Ophthalmology 2001; 108: 679–85.
6. Zhao J, Ellwein LB, Cui H, Ge J, Guan H, Lv J, Ma X, Yin J, Yin ZQ, Yuan Y, Liu H. Prevalence of vision impairment in older adults in rural China: the China Nine-Province Survey. Ophthalmology 2010; 117: 409–16.
7. Hyman L, Wu SY, Connell AM, Schachat A, Nemesure B, Hennis A, Leske MC. Prevalence and causes of visual impairment in The Barbados Eye Study. Ophthalmology 2001; 108: 1751–6.
8. Varma R, Ying-Lai M, Klein R, Azen SP, Los Angeles Latino Eye Study G. Prevalence and risk indicators of visual impairment and blindness in Latinos: the Los Angeles Latino Eye Study. Ophthalmology 2004; 111: 1132–40.
9. Lamoureux EL, Chong EW, Thumboo J, Wee HL, Wang JJ, Saw SM, Aung T, Wong TY. Vision impairment, ocular conditions, and vision-specific function: the Singapore Malay Eye Study. Ophthalmology 2008; 115: 1973–81.
10. Thiagalingam S, Cumming RG, Mitchell P. Factors associated with undercorrected refractive errors in an older population: the Blue Mountains Eye Study. Br J Ophthalmol 2002; 86: 1041–5.
11. Varma R, Wang MY, Ying-Lai M, Donofrio J, Azen SPLos Angeles Latino Eye Study G. The prevalence and risk indicators of uncorrected refractive error and unmet refractive need in Latinos: the Los Angeles Latino Eye Study. Invest Ophthalmol Vis Sci 2008; 49: 5264–73.
12. Kuang TM, Tsai SY, Hsu WM, Cheng CY, Liu JH, Chou P. Correctable visual impairment in an elderly Chinese population in Taiwan: the Shihpai Eye Study. Invest Ophthalmol Vis Sci 2007; 48: 1032–7.
13. Bourne RR, Dineen BP, Huq DM, Ali SM, Johnson GJ. Correction of refractive error in the adult population of Bangladesh: meeting the unmet need. Invest Ophthalmol Vis Sci 2004; 45: 410–7.
14. Munoz B, West SK, Rodriguez J, Sanchez R, Broman AT, Snyder R, Klein R. Blindness, visual impairment and the problem of uncorrected refractive error in a Mexican-American population: Proyecto VER. Invest Ophthalmol Vis Sci 2002; 43: 608–14.
15. Pan CW, Wong TY, Lavanya R, Wu RY, Zheng YF, Lin XY, Mitchell P, Aung T, Saw SM. Prevalence and risk factors for refractive errors in Indians: the Singapore Indian Eye Study (SINDI). Invest Ophthalmol Vis Sci 2011; 52: 3166–73.
16. Morgan I, Rose K. How genetic is school myopia? Prog Retin Eye Res 2005; 24: 1–38.
17. Morgan IG, Ohno-Matsui K, Saw SM. Myopia. Lancet 2012; 379: 1739–48.
18. Seet B, Wong TY, Tan DT, Saw SM, Balakrishnan V, Lee LK, Lim AS. Myopia in Singapore: taking a public health approach. Br J Ophthalmol 2001; 85: 521–6.
19. Pan CW, Ramamurthy D, Saw SM. Worldwide prevalence and risk factors for myopia. Ophthalmic Physiol Opt 2012; 32: 3–16.
20. Lamoureux EL, Pallant JF, Pesudovs K, Rees G, Hassell JB, Keeffe JE. The effectiveness of low-vision rehabilitation on participation in daily living and quality of life. Invest Ophthalmol Vis Sci 2007; 48: 1476–82.
21. Chiang PP, Zheng Y, Wong TY, Lamoureux EL. Vision impairment and major causes of vision loss impacts on vision-specific functioning independent of socioeconomic factors. Ophthalmology 2013; 120: 415–22.
22. Foong AW, Saw SM, Loo JL, Shen S, Loon SC, Rosman M, Aung T, Tan DT, Tai ES, Wong TY. Rationale and methodology for a population-based study of eye diseases in Malay people: The Singapore Malay eye study (SiMES). Ophthalmic Epidemiol 2007; 14: 25–35.
23. Lavanya R, Jeganathan VS, Zheng Y, Raju P, Cheung N, Tai ES, Wang JJ, Lamoureux E, Mitchell P, Young TL, Cajucom-Uy H, Foster PJ, Aung T, Saw SM, Wong TY. Methodology of the Singapore Indian Chinese Cohort (SICC) eye study: quantifying ethnic variations in the epidemiology of eye diseases in Asians. Ophthalmic Epidemiol 2009; 16: 325–36.
24. Ferris FL 3rd, Kassoff A, Bresnick GH, Bailey I. New visual acuity charts for clinical research. Am J Ophthalmol 1982; 94: 91–6.
25. American Diabetes Association. Standards of medical care in diabetes—2010. Diabetes Care 2010; 33 (Suppl. 1): S11–61.
26. Chylack LT Jr., Wolfe JK, Singer DM, Leske MC, Bullimore MA, Bailey IL, Friend J, McCarthy D, Wu SY. The Lens Opacities Classification System III. The Longitudinal Study of Cataract Study Group. Arch Ophthalmol 1993; 111: 831–6.
27. Lamoureux EL, Pesudovs K, Thumboo J, Saw SM, Wong TY. An evaluation of the reliability and validity of the visual functioning questionnaire (VF-11) using Rasch analysis in an Asian population. Invest Ophthalmol Vis Sci 2009; 50: 2607–13.
28. Tan CS, Chan YH, Wong TY, Gazzard G, Niti M, Ng TP, Saw SM. Prevalence and risk factors for refractive errors and ocular biometry parameters in an elderly Asian population: the Singapore Longitudinal Aging Study (SLAS). Eye (Lond) 2011; 25: 1294–301.
29. Liou HL, McCarty CA, Jin CL, Taylor HR. Prevalence and predictors of undercorrected refractive errors in the Victorian population. Am J Ophthalmol 1999; 127: 590–6.
30. McClure TM, Choi D, Wooten K, Nield C, Becker TM, Mansberger SL. The impact of eyeglasses on vision-related quality of life in American Indian/Alaska Natives. Am J Ophthalmol 2011; 151: 175–82.
Keywords:© 2014 American Academy of Optometry
undercorrected refractive error; vision functioning; epidemiology; ethnicities; Asians