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Epidemiology |

Sociodemographic, Lifestyle, and Medical Risk Factors for Visual Impairment in an Urban Asian Population:  The Singapore Malay Eye Study FREE

Elaine W. Chong, MBBS, PhD; Ecosse L. Lamoureux, MSc, PhD; Mark A. Jenkins, PhD; Tin Aung, MBBS, PhD; Seang-Mei Saw, MBBS, PhD; Tien Y. Wong, FRCSE, PhD
[+] Author Affiliations

Author Affiliations: Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital (Drs Chong, Lamoureux, and Wong), and Centre for Molecular, Environmental, Genetic and Analytic Epidemiology (Dr Jenkins), University of Melbourne, Melbourne; Singapore Eye Research Institute, Singapore National Eye Center, Singapore (Drs Lamoureux, Aung, Saw, and Wong); and Departments of Ophthalmology (Drs Aung, Saw, and Wong) and Community, Occupational and Family Medicine (Dr Saw), Yong Loo Lin School of Medicine, National University of Singapore, Singapore.


Section Editor: Leslie Hyman, PhD

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Arch Ophthalmol. 2009;127(12):1640-1647. doi:10.1001/archophthalmol.2009.298.
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Objective  To describe the associations between sociodemographic, lifestyle, and medical risk factors and visual impairment in a Southeast Asian population.

Methods  Population-based cross-sectional study of 3280 (78.7% response rate) Malay Singaporeans aged 40 to 80 years. Participants underwent a standardized interview, in which detailed sociodemographic histories were obtained, and clinical assessments for presenting and best-corrected visual acuity. Visual impairment (logMAR > 0.30) was classified as unilateral (1 eye impaired) or bilateral (both eyes impaired). Analyses used multivariate-adjusted multinomial logistic regression.

Results  Older age and lack of formal education was associated with increased odds of both unilateral and bilateral visual impairment based on presenting and best-corrected visual acuity. The odds doubled for each decade older, and lower education increased the odds 1.59- to 2.83-fold. Bilateral visual impairment was associated with being unemployed (odds ratio [OR], 1.84; 95% confidence interval [CI], 1.30-2.60), widowed status (OR, 1.51; 95% CI, 1.13-2.01), and higher systolic blood pressure (OR, 1.96; 95% CI, 1.44-2.66). Diabetes was associated with unilateral (OR, 1.47; 95% CI, 1.10-1.95) and bilateral (OR, 1.69; 95% CI, 1.23-2.32) visual impairment using best-corrected visual acuity.

Conclusions  Older age, lower education, unemployment, being widowed, diabetes, and hypertension were independently associated with bilateral visual impairment. Public health interventions should be targeted to these at-risk populations.

Visual impairment is a substantial public health problem in Asia.1It is estimated that in the Southeast Asia region alone there are 45 million people with visual impairment, of whom 12 million are blind.2With the aging population and increased life expectancy in this region, the burden of visual impairment is expected to increase. Visual impairment not only results in impaired quality of life with huge personal costs,3but also in significant direct and indirect economic costs to the community.4

It is estimated that for each dollar spent on the prevention of vision loss and eye care, there is a $5 return to the community.5Therefore, by identifying the at-risk population with targeted interventions, we can start to reduce the socioeconomic burden of visual impairment. However, there is insufficient data on the key determinants and risk factors for visual impairment; further delineation is important in culturally and socioeconomically diverse Asia. Thus far, age, unemployment, widowed status, and low education have been associated with bilateral visual impairment among Western populations,68but these associations are less clearly established among Asian populations in Japan and Taipei.9,10Some studies have shown socioeconomic factors to be important determinants of common eye diseases, such as age-related macular degeneration, myopia, and intraocular pressure.1114Additionally, whether diabetes,6high blood pressure, cigarette smoking,15and other medical and lifestyle factors1618are associated with visual impairment remains uncertain. Even fewer studies have evaluated risk factors for unilateral visual impairment. Persons with unilateral visual impairment have poor stereopsis and are immediately excluded from professions that require good vision. Hence in our study, we describe the sociodemographic, lifestyle, and medical factors associated with both unilateral and bilateral visual impairment in an urban Southeast Asian population.

STUDY DESIGN AND PROCEDURE

The Singapore Malay Eye Study (SiMES) is a population-based, cross-sectional study of 3280 Malay adults aged 40 to 80 years conducted between August 2004 and June 2006. The study adhered to the Declaration of Helsinki, and ethics approval was obtained from the Singapore Eye Research Institute Institutional Review Board. Details of the SiMES design and methodology have been reported elsewhere.19In brief, an age-stratified random sampling of all Malay adults aged 40 to 80 years residing in 15 residential districts in the southwestern part of Singapore was performed; an initial 5600 names (1400 people from each of the following age groups: 40-49, 50-59, 60-69, and 70-80 years) were selected. We determined study eligibility of participants by sending letters and conducting telephone calls and home visits. Of the 5600 names identified, 4168 individuals (74%) were eligible to participate. People were considered ineligible if they had moved from their residential address, had not lived there in the past 6 months, or were deceased or terminally ill. Of the 4168 eligible individuals, 3280 participants took part in our study (78.7% participation rate). Of the nonparticipants, 831 (19.9%) declined to participate and 57 (1.4%) could not be contacted. In general, there were few differences between participants and nonparticipants by sex, sampling location, or telephone ownership (data not shown).

Visual acuity (VA) data in both eyes were available from 3269 participants.20All examinations were conducted, after informed consent was obtained, at the Singapore Eye Research Institute, a clinical research facility located in central Singapore.

VA TESTING

At the study center, participants underwent an extensive and standardized examination procedure that included VA testing and a detailed clinical slitlamp examination. For each eye, presenting VA (ascertained while the participants wore their own glasses or contact lenses, if any) and best-corrected VA (BCVA; refraction was corrected by certified study optometrists) were obtained. Visual acuity was measured using a logMAR number chart (Lighthouse International, New York, New York) at a distance of 4 m. If no numbers were read at 4 m, the participant was moved to 3, 2, or 1 m, consecutively. If no numbers were identified on the chart, VA was assessed as counting fingers, hand movements, perception of light, or no perception of light.19

DEFINITION OF VISUAL IMPAIRMENT

We used the US definition of visual impairment, which defines blindness as VA of 20/200 or worse in the better seeing eye (logMAR ≥ 1.00) and low vision as VA worse than 20/40 but better than 20/200 in the better seeing eye (logMAR > 0.30 to < 1.00).21Similar to most population-based studies, VA criteria only, and not peripheral visual field criteria, were used to define visual impairment in our study.22In addition to defining visual impairment in terms of the better seeing eye (bilateral visual impairment, which includes those who are bilaterally blind, have bilaterally low vision, and those who are blind in 1 eye and have low vision in the other), we also presented data in terms of the worse seeing eye (when the other eye has normal vision) to provide further insight into unilateral visual impairment.20

SOCIODEMOGRAPHIC, LIFESTYLE, AND MEDICAL RISK FACTORS

A detailed interviewer-administered questionnaire was used to collect relevant sociodemographic, lifestyle, and medical information.14,19,23All interviewers were trained in questionnaire administration, adhering to strict protocols, and were fluent in both Malay and English. The questionnaire was administered, depending on the participant's preference, either in Malay or English. With the participant's consent, investigators recorded randomly selected interviews for periodic review for quality-control purposes. The collected data included country of birth, marital status, smoking history (current, past, or never), education (none, <elementary, elementary, or ≥high school), occupation, and current housing status.14More than 4.5 million people live within the 710 km2of Singapore; as a result, most Singaporeans live in government-built high-rise buildings, with a minority living in private estates. We therefore classified participants by housing status: 1- to 2-, 3- to 4-, or 5-room apartments/private housing. Occupation groups were service workers, professional/office workers (detailed near-work requirement), factory workers, homemakers, or retired or unemployed. Low socioeconomic status was defined as elementary or lower education level (≤grade 6), a monthly income of less than SGD 2000 ($1400), and living in a 1- to 2-room apartment.14

Participants also underwent an extensive and standardized examination procedure in which the participant's height, weight, and blood pressure were measured.19A 40-mL sample of nonfasting venous blood was also collected at the same setting. All serum biochemistry tests were conducted by the National University Hospital Reference Laboratory on the same day the blood sample was taken. Diabetes mellitus was defined as a nonfasting blood glucose level of 200 mg/dL or greater (to convert to millimoles per liter, multiply by 0.0555) or physician diagnosis of diabetes and use of diabetic medications.23,24Body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) was classified into 4 categories (normal, 18.5-22.9; underweight, <18.5; overweight, 23-27.4; and obese, >27.5) according to the World Health Organization and Singapore health promotion board recommendations.25Blood pressure measurements were taken twice 5 minutes apart while the subject was at rest and seated. If the 2 systolic blood pressures differed by more than 10 mm Hg, a third measurement was taken and the mean between the 2 closest readings was recorded.

STATISTICAL ANALYSIS

Multinomial logistic regression was performed to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for the association between potential risk factors and unilateral and bilateral visual impairment adjusting for age and sex. Variables identified as significant (P < .05) were retained as risk factors for further analyses. Multiple multinomial logistic regression models were then used to calculate the OR and 95% CI for different potential risk factors, adjusting for all variables retained from the base model. Analyses were performed using Stata, version 9.1 (Stata Corp, College Station, Texas).

Table 1lists the participants' characteristics by age group. Older participants tended to be male, less educated, bornoutside of Singapore, widowed, or retired or unemployed; to have lower incomes, diabetes, or higher systolic blood pressure; to live in smaller homes; and were less likely to be a smoker compared with younger participants. Participants in the 50- to 59-year age group were the most obese.

Table Graphic Jump LocationTable 1. Participants' Characteristics Stratified by Age

Table 2shows the association of specific sociodemographic, medical, and lifestyle characteristics with visual impairment, adjusted for age and sex and using presenting VA. Older age and lack of formal education, low income, and living in a small apartment were associated with unilateral and bilateral visual impairment. Results for BCVA were similar (results not shown), except for those for diabetes, which was associated with an increased odds of unilateral (OR, 1.53; 95% CI, 1.18-1.99) and bilateral (OR, 1.53; 95% CI, 1.15-2.05) visual impairment using BCVA criteria. No statistically significant associations were seen between smoking and visual impairment.

Table Graphic Jump LocationTable 2. Analysis of Risk Factors for Unilateral and Bilateral Visual Impairment, Based on Presenting Visual Acuity Adjusted for Age and Sex

Table 3shows the multivariate associations of risk factors for visual impairment, using presenting VA after adjusting for all other statistically significant factors. Increasing age was independently exponentially associated with both unilateral and bilateral visual impairment, while sex was no longer a statistically significant predictor of either outcome. Independent of age and all other risk factors, people who were less educated or widowed; lived in small homes; worked as factory workers or homemakers; or were retired or unemployed were also more likely to have bilateral visual impairment. Low socioeconomic status, as defined by the SiMES, was associated with both unilateral and bilateral visual impairment. Interestingly, higher BMI was inversely associated with bilateral visual impairment. The sociodemographic factors associated with visual impairment using BCVA (results not shown) were similar to those associated with visual impairment using presenting VA, except for diabetes, which was associated with an increased odds of unilateral (OR, 1.47; 95% CI, 1.10-1.95) and bilateral (OR, 1.69; 95% CI, 1.23-2.32) visual impairment. (Additional tables [eTable 1, eTable 2, eTable 3, and eTable 4] evaluating unilateral and bilateral low vision and blindnessare available at http://www.archophthalmol.com.)

Table Graphic Jump LocationTable 3. Multivariate Models for Unilateral and Bilateral Visual Impairment Based on Presenting Visual Acuity

In this urban Southeast Asian population-based study, we found increasing age to be strongly associated with both unilateral and bilateral visual impairment, for both presenting VA and BCVA, while controlling for potential confounders. The odds of any visual impairment increased exponentially with every decade of age. We also found low education, unemployment, widowed status, and higher systolic blood pressure to be independently associated with bilateral visual impairment, using both presenting VA and BCVA and adjusting for age and other risk factors.

Increasing age and its association with the risk of visual impairment has been consistently reported in other studies, largely in Western populations.68,15Most previous studies defined visual impairment based on best-corrected vision. However, the underrepresentation of presenting or “habitual” vision in the prevalence of visual impairment is now recognized by the World Health Organization.2Given that people generally conduct their daily activities with their habitual vision and that undercorrected refractive error remains a significant problem in many developed and developing nations,20,2628the measurement of visual impairment using presenting VA is perhaps more relevant and practical. We showed that age was more strongly associated with BCVA than presenting VA, suggesting that visual impairment from causes other than refractive error becomes increasingly important with age.

Independent of other factors, participants with less than an elementary school education were more likely to have unilateral and bilateral visual impairment, using both presenting VA and BCVA criteria, compared with participants who completed high school or college. Previous studies have reported similar results. In the Latino Eye Study, 12 or more years of education compared with 0 to 6 years resulted in an OR of 0.5 (95% CI, 0.3-0.8) for visual impairment (BCVA ≤ 20/40 in the better eye).6In Taiwan, every increase in education level (illiterate [no education], primary school, junior high school, high school, and ≥college) decreased the odds of visual impairment by half (OR, 0.58; 95% CI, 0.44-0.78).9It is likely that lifetime exposures and behaviors associated with less education are related to loss of vision. Persons who are illiterate may find reading printed public health messages and navigating through the health care system challenging. These data highlight the importance of targeting this high-risk group for preventive public health strategies.

Previous studies have found employment status to be associated with visual impairment, but most have classified statuses as simply employed or not. In general, these studies showed that unemployment (compared with employment) increased the odds of visual impairment by about 3- to 5-fold.6,11,29We found similar associations and analyzed our results by employment type. Using service workers as the reference group, we found that factory workers, homemakers, and retired and unemployed people have an approximately 2-fold increased odds of bilateral visual impairment, using presenting VA and BCVA, while this increased odds was not seen in professionals and office workers. This may reflect their lower visual requirements for activities of daily living. However, these associations were not observed for unilateral visual impairment, perhaps as a result of reverse causation—bilateral visual impairment having a greater effect on employability—in cross-sectional analyses. Regardless, these data provide further evidence for targeting health messages to homemakers and retired and unemployed people.

In the Beaver Dam Eye Study, participants were at an increased risk of visual impairment (BCVA < 20/40 in the better eye) if they were never married, separated, or divorced or if they were widowed compared with those who were married.11Similar findings were recorded in the Latino Eye Study.6Although Asian family dynamics are different from those in Western populations, a Taiwanese study found that people who were married (vs unmarried) had an OR in a similar direction (0.62; 95% CI, 0.33-1.16), though it was not statistically significant.9We found marital status to be associated with bilateral visual impairment, using presenting VA and BCVA criteria. Widowed compared with married status was associated with increased odds of bilateral visual impairment. Possibly owing to the small numbers of divorced/separated and unmarried participants, other associations were not statistically significant. The association with marital status may be a reflection of a married couple's social support network; married individuals may also feel added pressure from their spouses to maintain their health.

Diabetic retinopathy, with a prevalence of 5.1%, is the third leading cause of visual impairment in SiMES.20We found diabetes to be associated with a 50% increased odds of unilateral and bilateral visual impairment, using BCVA. Diabetes was found to increase the odds of visual impairment in the Latino Eye Study 2-fold (OR, 2.2; 95% CI, 1.5,3.2).6However, its strength of association with visual impairment in another Asian study10is less clear. This illustrates the importance of eye screens in patients with diabetes to reduce the burden of visual impairment.

To date, few studies have evaluated systolic blood pressure and visual impairment. Higher blood pressure, however, has been consistently associated with retinal vascular diseases, including retinal vein and artery occlusions and ischemic optic neuropathy.16,30Hypertension has also been implicated as a risk factor for age-related macular degeneration and glaucoma.16We found higher systolic blood pressures to be significantly associated with bilateral visual impairment, with adjusted ORs increasing with each quartile; systolic blood pressure around 180 mm Hg was associated with an 88% increased odds of visual impairment. Higher systolic blood pressures may reflect the participant's general health status and should direct general practitioners toward evaluation of patients' eye health. We acknowledge that misclassification bias could have occurred, as 2 blood pressure readings were obtained at the same visit in our study.

Although BMI has been associated with many eye diseases, including age-related cataract, glaucoma, age-related macular degeneration, and diabetic retinopathy,17there are no data evaluating BMI and visual impairment. Interestingly, we found higher BMI to be inversely associated with bilateral visual impairment. Although higher BMI is associated with lower socioeconomic status in most Western nations, this was not apparent in our SiMES population. Participants from our defined lower socioeconomic background had a mean BMI of 26.0 (standard deviation [SD], 5.0) compared with those with higher socioeconomic statuses (mean, 26.4 [SD, 5.1]); hence, higher BMI may reflect better nutrition and general health.

Our study has several limitations. First, as with any cross-sectional design, we could not address the temporal relationship between sociodemographic factors and visual impairment. However, the identification of specific sociodemographic characteristics, regardless of cause or effect, is important for targeted eye health intervention. Second, similar to other observational studies, residual confounding from unmeasured and unknown confounders cannot be excluded. Third, Singapore is a newly developed Southeast Asian nation, and results from our study may not be directly generalizable to all neighboring countries. Conversely, the strengths of this study are its population-based nature and large sample size. In addition, our study has collected detailed information on many aspects of sociodemographic and lifestyle factors.

In conclusion, our study found that older age, lower education, unemployment, widowed status, diabetes, and hypertension were independently associated with visual impairment in this urban Asian population. Identification of those at risk can aid health care planners in developing appropriate and targeted programs and assist health care educators in preparing relevant materials. Targeted eye health campaigns in other countries have already been shown to result in changes in eye care use and eye health.31,32With the aging population, the impact of visual impairment in Asia is likely to increase. Therefore, early education and specific tailored interventions are needed to offset the escalation of visual impairment in older Asian people.

Correspondence: Tien Yin Wong, FRCSE, PhD, Centre for Eye Research Australia, University of Melbourne, 32 Gisborne St, East Melbourne 3002, Australia (twong@unimelb.edu.au).

Submitted for Publication: January 15, 2009; final revision received June 23, 2009; accepted July 13, 2009.

Financial Disclosure: None reported.

Funding/Support: This study was supported by grants 0796/2003, 0863/2004, and CSI/0002/2005 from the National Medical Research Council and a Biomedical Research Council Grant (501/1/25-5). Additional support was provided by the Singapore Tissue Network and the Ministry of Health.

Previous Presentation: This paper was presented at the 2007 Association for Research in Vision & Ophthalmology Annual Meeting; May 10, 2007; Fort Lauderdale, Florida.

Wong  TYLoon  SCSaw  SM The epidemiology of age related eye diseases in Asia. Br J Ophthalmol 2006;90 (4) 506- 511
PubMed
Resnikoff  SPascolini  DEtya'ale  D  et al.  Global data on visual impairment in the year 2002. Bull World Health Organ 2004;82 (11) 844- 851
PubMed
Lamoureux  ELChong  EWang  JJ  et al.  Visual impairment, causes of vision loss, and falls: the Singapore Malay Eye Study. Invest Ophthalmol Vis Sci 2008;49 (2) 528- 533
PubMed
West  SSommer  A Prevention of blindness and priorities for the future. Bull World Health Organ 2001;79 (3) 244- 248
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Taylor  HR LXIII Edward Jackson Memorial Lecture: eye care: dollars and sense. Am J Ophthalmol 2007;143 (1) 1- 8
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Varma  RYing-Lai  MKlein  RAzen  SPLos Angeles Latino Eye Study Group, Prevalence and risk indicators of visual impairment and blindness in Latinos: the Los Angeles Latino Eye Study. Ophthalmology 2004;111 (6) 1132- 1140
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Tielsch  JMSommer  AKatz  JQuigley  HEzrine  SBaltimore Eye Survey Research Group, Socioeconomic status and visual impairment among urban Americans. Arch Ophthalmol 1991;109 (5) 637- 641
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Liu  JHCheng  CYChen  SJLee  FL Visual impairment in a Taiwanese population: prevalence, causes, and socioeconomic factors. Ophthalmic Epidemiol 2001;8 (5) 339- 350
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Iwano  MNomura  HAndo  FNiino  NMiyake  YShimokata  H Visual acuity in a community-dwelling Japanese population and factors associated with visual impairment. Jpn J Ophthalmol 2004;48 (1) 37- 43
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Cackett  PTay  WTAung  T  et al.  Education, socio-economic status and age-related macular degeneration in Asians: the Singapore Malay Eye Study. Br J Ophthalmol 2008;921312- 1315
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Wong  TYMitchell  P The eye in hypertension. Lancet 2007;369 (9559) 425- 435
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Cheung  NWong  TY Obesity and eye diseases. Surv Ophthalmol 2007;52 (2) 180- 195
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Guymer  RHChong  EW Modifiable risk factors for age-related macular degeneration. Med J Aust 2006;184 (9) 455- 458
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Foong  AWSaw  SMLoo  JL  et al.  Rationale and methodology for a population-based study of eye diseases in Malay people: the Singapore Malay eye study (SiMES). Ophthalmic Epidemiol 2007;14 (1) 25- 35
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Wong  TYChong  EWWong  WL  et al. Singapore Malay Eye Study Team, Prevalence and causes of low vision and blindness in an urban Malay population: the Singapore Malay Eye Study. Arch Ophthalmol 2008;126 (8) 1091- 1099
PubMed
Tielsch  JMSommer  AWitt  KKatz  JRoyall  RM Blindness and visual impairment in an American urban population: the Baltimore Eye Survey. Arch Ophthalmol 1990;108 (2) 286- 290
PubMed
Varma  RFraser-Bell  STan  SKlein  RAzen  SPLos Angeles Latino Eye Study Group, Prevalence of age-related macular degeneration in Latinos: the Los Angeles Latino Eye Study. Ophthalmology 2004;111 (7) 1288- 1297
PubMed
Wong  TYCheung  NTay  WT  et al.  Prevalence and risk factors for diabetic retinopathy: the Singapore Malay Eye Study. Ophthalmology 2008;115 (11) 1869- 1875
American Diabetes Association, Diagnosis and classification of diabetes mellitus. Diabetes Care 2007;30 ((suppl 1)) S42- S47
PubMed
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Figures

Tables

Table Graphic Jump LocationTable 1. Participants' Characteristics Stratified by Age
Table Graphic Jump LocationTable 2. Analysis of Risk Factors for Unilateral and Bilateral Visual Impairment, Based on Presenting Visual Acuity Adjusted for Age and Sex
Table Graphic Jump LocationTable 3. Multivariate Models for Unilateral and Bilateral Visual Impairment Based on Presenting Visual Acuity

References

Wong  TYLoon  SCSaw  SM The epidemiology of age related eye diseases in Asia. Br J Ophthalmol 2006;90 (4) 506- 511
PubMed
Resnikoff  SPascolini  DEtya'ale  D  et al.  Global data on visual impairment in the year 2002. Bull World Health Organ 2004;82 (11) 844- 851
PubMed
Lamoureux  ELChong  EWang  JJ  et al.  Visual impairment, causes of vision loss, and falls: the Singapore Malay Eye Study. Invest Ophthalmol Vis Sci 2008;49 (2) 528- 533
PubMed
West  SSommer  A Prevention of blindness and priorities for the future. Bull World Health Organ 2001;79 (3) 244- 248
PubMed
Taylor  HR LXIII Edward Jackson Memorial Lecture: eye care: dollars and sense. Am J Ophthalmol 2007;143 (1) 1- 8
PubMed
Varma  RYing-Lai  MKlein  RAzen  SPLos Angeles Latino Eye Study Group, Prevalence and risk indicators of visual impairment and blindness in Latinos: the Los Angeles Latino Eye Study. Ophthalmology 2004;111 (6) 1132- 1140
PubMed
Livingston  PMMcCarty  CATaylor  HR Visual impairment and socioeconomic factors. Br J Ophthalmol 1997;81 (7) 574- 577
PubMed
Tielsch  JMSommer  AKatz  JQuigley  HEzrine  SBaltimore Eye Survey Research Group, Socioeconomic status and visual impairment among urban Americans. Arch Ophthalmol 1991;109 (5) 637- 641
PubMed
Liu  JHCheng  CYChen  SJLee  FL Visual impairment in a Taiwanese population: prevalence, causes, and socioeconomic factors. Ophthalmic Epidemiol 2001;8 (5) 339- 350
PubMed
Iwano  MNomura  HAndo  FNiino  NMiyake  YShimokata  H Visual acuity in a community-dwelling Japanese population and factors associated with visual impairment. Jpn J Ophthalmol 2004;48 (1) 37- 43
PubMed
Klein  RKlein  BEJensen  SCMoss  SECruickshanks  KJ The relation of socioeconomic factors to age-related cataract, maculopathy, and impaired vision: the Beaver Dam Eye Study. Ophthalmology 1994;101 (12) 1969- 1979
PubMed
Wong  TYFoster  PJJohnson  GJSeah  SK Education, socioeconomic status, and ocular dimensions in Chinese adults: the Tanjong Pagar Survey. Br J Ophthalmol 2002;86 (9) 963- 968
PubMed
Yip  JLAung  TWong  TY  et al.  Socioeconomic status, systolic blood pressure and intraocular pressure: the Tanjong Pagar Study. Br J Ophthalmol 2007;91 (1) 56- 61
PubMed
Cackett  PTay  WTAung  T  et al.  Education, socio-economic status and age-related macular degeneration in Asians: the Singapore Malay Eye Study. Br J Ophthalmol 2008;921312- 1315
Salive  MEGuralnik  JChristen  WGlynn  RJColsher  POstfeld  AM Functional blindness and visual impairment in older adults from three communities. Ophthalmology 1992;99 (12) 1840- 1847
PubMed
Wong  TYMitchell  P The eye in hypertension. Lancet 2007;369 (9559) 425- 435
PubMed
Cheung  NWong  TY Obesity and eye diseases. Surv Ophthalmol 2007;52 (2) 180- 195
PubMed
Guymer  RHChong  EW Modifiable risk factors for age-related macular degeneration. Med J Aust 2006;184 (9) 455- 458
PubMed
Foong  AWSaw  SMLoo  JL  et al.  Rationale and methodology for a population-based study of eye diseases in Malay people: the Singapore Malay eye study (SiMES). Ophthalmic Epidemiol 2007;14 (1) 25- 35
PubMed
Wong  TYChong  EWWong  WL  et al. Singapore Malay Eye Study Team, Prevalence and causes of low vision and blindness in an urban Malay population: the Singapore Malay Eye Study. Arch Ophthalmol 2008;126 (8) 1091- 1099
PubMed
Tielsch  JMSommer  AWitt  KKatz  JRoyall  RM Blindness and visual impairment in an American urban population: the Baltimore Eye Survey. Arch Ophthalmol 1990;108 (2) 286- 290
PubMed
Varma  RFraser-Bell  STan  SKlein  RAzen  SPLos Angeles Latino Eye Study Group, Prevalence of age-related macular degeneration in Latinos: the Los Angeles Latino Eye Study. Ophthalmology 2004;111 (7) 1288- 1297
PubMed
Wong  TYCheung  NTay  WT  et al.  Prevalence and risk factors for diabetic retinopathy: the Singapore Malay Eye Study. Ophthalmology 2008;115 (11) 1869- 1875
American Diabetes Association, Diagnosis and classification of diabetes mellitus. Diabetes Care 2007;30 ((suppl 1)) S42- S47
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