July 2013
Volume 54, Issue 7
Free
Glaucoma  |   July 2013
The Prevalence and Types of Glaucoma in an Urban Indian Population: The Singapore Indian Eye Study
Author Affiliations & Notes
  • Arun Narayanaswamy
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
  • Mani Baskaran
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
  • Yingfeng Zheng
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
    State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
  • Raghavan Lavanya
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
  • Renyi Wu
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
  • Wan-Ling Wong
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
    Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore
  • Seang-Mei Saw
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
    Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
    Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore
  • Ching-Yu Cheng
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
    Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
    Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore
  • Tien-Yin Wong
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
    Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
    Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore
  • Tin Aung
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
    Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore
  • Correspondence: Tin Aung, Singapore National Eye Centre, 11 Third Hospital Avenue, Singapore 168751; aung.tin@snec.com.sg
Investigative Ophthalmology & Visual Science July 2013, Vol.54, 4621-4627. doi:10.1167/iovs.13-11950
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      Arun Narayanaswamy, Mani Baskaran, Yingfeng Zheng, Raghavan Lavanya, Renyi Wu, Wan-Ling Wong, Seang-Mei Saw, Ching-Yu Cheng, Tien-Yin Wong, Tin Aung; The Prevalence and Types of Glaucoma in an Urban Indian Population: The Singapore Indian Eye Study. Invest. Ophthalmol. Vis. Sci. 2013;54(7):4621-4627. doi: 10.1167/iovs.13-11950.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose.: To determine the prevalence and types of glaucoma in an urban Singaporean Indian population.

Methods.: The Singapore Indian Eye Study (SINDI) was a population-based, cross-sectional survey that examined 3400 (75.6% response) persons aged 40 to 80 years. Participants underwent a standardized examination including slit-lamp biomicroscopy, Goldmann applanation tonometry, and dilated optic disc assessment. Participants suspected to have glaucoma also underwent visual field examination (24-2 SITA standard, Humphrey Visual Field Analyzer II), gonioscopy, and repeat applanation tonometry. Glaucoma was defined according to International Society for Geographical and Epidemiologic Ophthalmology criteria.

Results.: Of the 3400 participants, 78 (2.29%) had diagnosed glaucoma, giving an age-standardized prevalence of 1.95% (95% confidence interval [CI], 1.5%–2.5%). The age-standardized prevalence of primary open-angle glaucoma (POAG) was 1.25% (95% CI, 0.89%–1.73%), primary angle-closure glaucoma (PACG) 0.12% (95% CI, 0.04%–0.33%), and secondary glaucoma 0.55% (95% CI, 0.35%–0.86%). The mean IOP among the participants in the normal group in the study population was 15.6 ± 2.6 mm Hg and 17.7 ± 6.1 mm Hg in subjects with glaucoma (P = 0.003). The mean central corneal thickness (CCT) in the normal study population was 540.31 ± 33.79; the mean CCT in subjects with POAG (529.8 ± 30.8 μm) was statistically different from the normal study group (P = 0.003).

Conclusions.: The prevalence of glaucoma among Singaporean Indians 40 years of age and older in Singapore was 1.95%, approximately half that of the Chinese and the Malay persons in Singapore. As in other Asian studies, POAG was the main form of glaucoma accounting for nearly 60% of cases.

Introduction
The impact of migrant communities on disease prevalence is gaining importance in the current era of globalization. 14 Sustained migration between disparate health environments also affects the longer-term epidemiology of chronic noninfectious diseases, and it has been suggested that this could have an impact on health services at migrant destinations. 5 This impact needs to be recognized, and establishing data on migrant population disease statistics would help unravel some of the environmental and socioeconomic effects on disease prevalence, and it may aid the development of effective strategic and operational approaches to health care delivery. 68  
The urbanized society of Singapore has an amalgam of immigrants predominantly from China, Malaysia, and India. The Singaporean Indians are the third largest population subset in the island, accounting for 9.2% of the population and also comprise nearly 10.0% of the total population in neighboring Malaysia. 9 This migrant Indian community set foot into the region during the late 18th century and early 19th century and in the initial few decades, this migration predominantly occurred from the southern states of India. 10 Currently available population-based data from the Indian subcontinent with regard to glaucoma prevalence has shown significant variations based on geographic location and has also been reported to be largely influenced by urbanization. 1114 Since the record of immigration of Indians has been documented to be close to 130 years, 10,15 we found this subset of Singaporean Indian population to be an ideal sample to evaluate the impact of migration on disease prevalence. The Singapore Indian Eye Study (SINDI) 16 was designed to document the prevalence, risk factors, and impact of the major eye diseases in ethnic Indian residents of Singapore, most of whom were migrants from South India. 
In this study, we describe the prevalence, type, and visual impact of glaucoma among Indian persons aged 40 to 80 years residing in Singapore. 
Methods
Study Design
SINDI was a population-based, cross-sectional study of 3400 Indian adults aged ≥40 years conducted between the years 2007 and 2009. Details of the study design, sampling plan, and methodology have been reported. 16 In brief, the study was conducted in the southwestern part of Singapore, using the same study protocol as the Singapore Malay Eye Study. 17 On the basis of an age-stratified random sampling strategy, 6350 names were selected. Of these, 4497 individuals were deemed eligible to participate. The term “Singaporean Indians” refers to persons of Indian descent who migrated to Singapore. The study adhered to the Declaration of Helsinki, ethics approval was obtained from the Singapore Eye Research Institute Institutional Review Board, and written informed consent was obtained from all participants. 
Clinical Assessment
All subjects recruited in the study were examined at a research clinic established at the Singapore Eye Research Institute. An interviewer-administered questionnaire was used to collect demographic data, socioeconomic information, lifestyle factors, and medical, ophthalmic, and family history. The presenting visual acuity with habitual correction and best corrected visual acuity with subjective refraction were recorded using an Early Treatment Diabetic Retinopathy Study (EDTRS) logarithm of the minimal angle of resolution (log MAR) number chart (Lighthouse International, New York, NY) at a distance of 4 m. 17 Central corneal thickness (CCT) was measured using ultrasound pachymetry (Nidek Echoscan Model US-1800, Nidek Co., Ltd., Gamagori, Japan). Ocular assessment was performed by a team of two ophthalmologists (YZ and RL) with extensive experience in population-based studies. Slit lamp biomicroscopy (model BQ-900; Haag-Streit, Koniz, Switzerland) was performed to identify abnormalities of the anterior segment specifically, evaluating for any evidence of secondary glaucoma. Peripheral anterior chamber depth (ACD) was determined by using the modified Van Herick technique, 18 with the temporal peripheral anterior chamber examined under optical section at ×16 magnification. Intraocular pressure (IOP) was measured with a Goldmann applanation tonometer (Haag-Streit) before pupil dilation. One reading was taken from each eye. If the IOP reading was greater than 21 mm Hg, a repeat reading was taken, and the second reading was used for analysis. 
Gonioscopy was performed with a Goldmann two-mirror lens (Ocular Instruments, Inc., Bellevue, WA) under standard dark illumination in three groups of participants: those suspected to have glaucoma (definition provided later), all participants with peripheral ACD of Van Herick grade 2 or less, and one in five randomly selected participants who did not meet the first two criteria. A narrow vertical beam of 1 mm in length was offset vertically for superior and inferior quadrants, horizontally for nasal and temporal quadrants. Dynamic indentation gonioscopy with a four-mirror Sussman gonioscope (Ocular Instruments, Inc., Bellevue, WA) was used to determine the presence of peripheral anterior synechiae. Angle width, iris angle insertion, iris profile, and presence of peripheral anterior synechiae were documented according to classification systems by Spaeth 19 and Scheie. 20  
The optic disc was evaluated with a 78-D lens, at ×16 magnification, with measuring graticule during dilated funduscopy. The vertical cup to disc ratio (VCDR) was calculated and morphological features such as disc hemorrhage, notching of the neuroretinal rim (NRR), and defects of the retinal nerve fiber layer were documented. Finally, automated perimetry (SITA 24-2; Humphrey Visual Field Analyzer II; Carl Zeiss Meditec, Inc., Oberkochen, Germany) was performed with near refractive correction on 1 in 10 participants and in all participants suspected to have glaucoma (definition in the next section). The visual field test was repeated if the test reliability was not satisfactory (fixation loss > 20%; false positive > 33%; and/or false negative > 33%) or if there was a glaucomatous visual field defect (definition in the next section). Data from participants with normal perimetry (429 of 438 normal subjects; nine subjects had unreliable visual fields) were used to define normative values for VCDR and IOP for the population. 
Diagnostic Definitions.
Suspected glaucoma was defined as participants' fulfilling any of the following criteria: (1) IOP > 21 mm Hg, (2) VCDR > 0.6 or VCDR asymmetry > 0.2, (3) abnormal anterior segment deposit consistent with pseudo-exfoliation or pigment dispersion syndrome, (4) narrow anterior chamber angle (defined in the next section), (5) peripheral anterior synechiae, (6) other findings consistent with secondary glaucoma, and (7) known history of glaucoma. As indicated, these participants underwent visual field testing, gonioscopy, and a second IOP measurement, usually on another day. 
Glaucoma cases were defined according to the International Society of Geographical and Epidemiologic Ophthalmology (ISGEO) criteria based on three categories. 21 Category 1 cases were defined as optic disc abnormality (VCDR/VCDR asymmetry ≥ 97.5 percentile of the normal population or NRR width between 11 and 1 o'clock or 5 and 7 o'clock reduced to ≤ 0.1 VCDR), with a corresponding glaucomatous visual field defect. Category 2 cases were defined as having a severely damaged optic disc (VCDR or VCDR asymmetry ≥ 99.5 percentile) in the absence of adequate performance in a visual field test. In diagnosing category 1 or 2 glaucoma, it was required that there be no other explanation for the VCDR finding (dysplastic disc or marked anisometropia) or visual field defect (retinal vascular disease, macular degeneration, or cerebrovascular diseases). Category 3 cases were defined as subjects without visual field or optic disc data who were blind (corrected visual acuity < 3/60) and who had previous glaucoma surgery or had IOP ≥ 99.5 percentile. A glaucomatous visual field defect was considered to be present if the following were found: (1) glaucoma hemifield test result outside normal limits, and (2) a cluster of three or more nonedge, contiguous points, not crossing the horizontal meridian, with a probability of <5% of the age-matched normal group on the pattern deviation plot on two separate occasions. A narrow anterior chamber angle was diagnosed if the posterior trabecular meshwork was seen for 180° or less of the angle circumference during static gonioscopy. Primary angle-closure glaucoma (PACG) was defined as an eye with glaucoma as defined in the presence of narrow angles, and features of trabecular obstruction by peripheral iris (such as peripheral anterior synechiae, elevated IOP, iris whorling, “glaukomflecken” lens opacities, or excessive pigment deposition on the trabecular surface). Subjects with glaucoma and an open, normal drainage angle with no identifiable secondary pathologic processes were said to have primary open-angle glaucoma (POAG). Other cases in which it was difficult to accurately assess the underlying cause of the glaucoma, were termed unclassifiable. Final identification, adjudication, and classification of glaucoma cases were reviewed by the senior author (TA) , along with two glaucoma fellowship trained ophthalmologists (MB and YFZ). 
Other Variables.
Systolic and diastolic blood pressures were taken using an automated sphygmomanometer (Dinamap GE Pro 100V2; GE Health Care, Milwaukee, WI). Nonfasting blood samples were drawn from all participants to determine levels of serum glucose and glycosylated hemoglobin (HbA1c). A subject was labeled hypertensive if the systolic BP ≥ 140 mm Hg or diastolic BP ≥ 90 mm Hg or physician diagnosis or self-reported history of hypertension. Diabetes mellitus was diagnosed in a subject who had a nonfasting glucose level ≥ 200 mg/dL (11.1 mmol/L) at examination, or had a physician diagnosis of diabetes and was using diabetic medications. 
Statistical Analysis
Statistical analysis was performed with commercial software (SPSS; ver. 20, SPSS Inc., Chicago, IL). Prevalence estimate of glaucoma was performed for the whole cohort and in age- and sex-stratified groups. Prevalence rates were standardized to the population distribution from the 2010 Singapore Indian Census, 9 using the direct method of adjustment. Logistic regression was used to assess the odds of glaucoma with increasing age. Independent t-test was used for comparison of means and chi-square or Fisher's exact test was used for comparison of proportions between groups. P-value < 0.05 was considered as statistically significant. We also performed a comparative analysis of the age-specific prevalence of POAG from prior reports among South Indian subjects aged 40 years and above. 1214,22  
Results
There were 3400 participants in SINDI (75.6% participation rate). Of the nonparticipants, 1021 (22.7%) refused to participate and 76 (1.7%) were not contactable. Nonparticipants on average were slightly older than participants (P = 0.001), and there were no sex differences (P = 0.28) between the two groups. 
The mean age of the study population was 57.8 ± 10.1 years, and 49.8% were women. Mean IOP (right eye) was 15.75 mm Hg, with 97.5 and 99.5 percentiles of 21.0 and 24.0 mm Hg, respectively. Mean VCDR in the normal study group (right eye) was 0.41, with 97.5 and 99.5 percentiles of 0.60 and 0.62, respectively. Mean VCDR asymmetry was 0.03 with 97.5 and 99.5 percentiles of 0.13 and 0.20, respectively. Of the 3400 participants, 365 (10.7%) were classified as having suspected glaucoma. Of these, 78 (2.29%) had glaucoma, of which 46 (58.97%) had POAG, 6 (7.69%) had PACG, and 26 (33.3%) had secondary glaucoma. Table 1 shows the overall crude and age-standardized prevalence of glaucoma, POAG, and PACG. The age-standardized prevalence rate of glaucoma was 1.95% (95% confidence interval [CI], 1.51–2.50) with a POAG prevalence of 1.25% (95% CI, 0.89–1.73) and PACG prevalence of 0.12% (95% CI, 0.04–0.33). The prevalence of glaucoma increased with age (P for trend = 0.006) and was higher in participants aged 60 to 69 years (odds ratio [OR], 2.66; 95% CI, 1.35–5.25; P = 0.005) and 70 to 80+ (3.43; 1.66–7.08; P = 0.001) compared with those aged 40 to 49 years. The standardized prevalence of secondary glaucoma was 0.55% (95% CI, 0.35%–0.86%). The mean IOP among the normal subjects in the study population was 15.6 ± 2.6 mm Hg and 17.7 ± 6.1 mm Hg in subjects with glaucoma (P = 0.003). Of the 46 participants with POAG, 38 (82.6%) of subjects with IOP ≤ 21.0 mm Hg and three (50.0%) of the six participants with PACG had an IOP ≤ 21.0 mm Hg. The mean CCT in the normal study population was 540.31 ± 33.79 μm. The mean CCT in subjects with POAG (529.8 ± 30.8 μm) was statistically lower than the normal study group (P = 0.003). 
Table 1
 
Prevalence of Glaucoma by Age and Sex Among Singaporean Indians
Table 1
 
Prevalence of Glaucoma by Age and Sex Among Singaporean Indians
All Persons Males Females
N n (%) N n (%) N n (%)
All glaucoma
 40–49 y 957 12 (1.25) 465 9 (1.94) 492 3 (0.61)
 50–59 y 1077 17 (1.58) 529 10 (1.89) 548 7 (1.28)
 60–69 y 887 29 (3.27) 464 16 (3.45) 423 13 (3.07)
 70+ y 479 20 (4.18) 248 9 (3.63) 231 11 (4.76)
P for trend 0.006 0.191 0.005
Crude total 3400 78 (2.29) 1706 44 (2.58) 1694 34 (2.01)
Adjusted total* 1.95 (1.51–2.50) 2.29 (1.59–3.24) 1.66 (1.14–2.41)
POAG
 40–49 y 957 11 (1.15) 465 8 (1.72) 492 3 (0.61)
 50–59 y 1077 9 (0.84) 529 7 (1.32) 548 2 (0.36)
 60–69 y 887 15 (1.69) 464 9 (1.94) 423 6 (1.42)
 70+ y 479 11 (2.30) 248 4 (1.61) 231 7 (3.03)
P for trend 0.042 0.870 0.003
Crude total 3400 46 (1.35) 1706 28 (1.64) 1694 18 (1.06)
Adjusted total* 1.25 (0.89–1.73) 1.62 (1.02–2.49) 0.93 (0.54–1.55)
PACG
 40–49 y 957 0 (0.00) 465 0 (0.00) 492 0 (0.00)
 50–59 y 1077 2 (0.19) 529 1 (0.19) 548 1 (0.18)
 60–69 y 887 4 (0.45) 464 3 (0.65) 423 1 (0.24)
 70+ y 479 0 (0.00) 248 0 (0.00) 231 0 (0.00)
P for trend 0.329 0.367 0.709
Crude total 3400 6 (0.18) 1706 4 (0.23) 1694 2 (0.12)
Adjusted total* 0.12 (0.04–0.33) 0.14 (0.04–0.55) 0.09 (0.01–0.45)
Table 2 shows the characteristics of subjects with specific types of glaucoma. Among the attributable causes of secondary glaucoma (0.81%), glaucoma with pseudophakia (0.38%) and neovascular glaucoma (0.12%) were the most common diagnoses. ISGEO categorization of the glaucomas (Table 3) revealed a predominance of categories 1 (53.8%) and 2 (42.3%) in this population. Of the 78 glaucoma cases, 13 (16.6%) had low-vision (logMAR, >0.30 to <1.00) and eight (10.2%) were blind (logMAR, ≥1.00), according to the primary definition. The proportion of subjects with low vision was equal (30.7%) among POAG and PACG subjects. Blindness due to glaucoma was noted to be associated with POAG in two subjects (2.56%) and from secondary causes in the remaining six subjects (7.69%). 
Table 2
 
Characteristics and Subtypes of Glaucoma
Table 2
 
Characteristics and Subtypes of Glaucoma
All Median Age, y Males Females M:F Ratio
Any glaucoma 78 (2.29) 63.23 44 (2.58) 34 (2.01) 22:17
Primary glaucoma  52 (1.53) 61.74 32 (1.88) 20 (1.18) 8:5
Secondary glaucoma 26 (0.76) 66.04 12 (0.74) 14 (0.89) 6:7
Types of glaucoma
 POAG 46 (1.35) 61.11 28 (1.64) 18 (1.06) 14:9
 PACG 6 (0.18) 63.50 4 (0.23) 2 (0.12) 2:1
 PXF glaucoma 2 (0.06) 58.94 0 (0.00) 2 (0.12) 0:1
 Neovascular glaucoma 4 (0.12) 56.18 2 (0.12) 2 (0.12) 1:1
 Pigment dispersion glaucoma 1 (0.03) 70.64 1 (0.06) 0 (0.00) 1:0
 Steroid-induced glaucoma 1 (0.03) 61.92 1 (0.06) 0 (0.00) 1:0
 Glaucoma with pseudophakia 13 (0.38) 69.48 7 (0.41) 6 (0.35) 7:6
 Unspecified glaucoma 5 (0.15) 65.85 1 (0.06) 4 (0.24) 1:4
Table 3
 
Glaucoma Diagnosis Based on ISGEO Categorization
Table 3
 
Glaucoma Diagnosis Based on ISGEO Categorization
Glaucoma Subtype Category 1 (%) Category 2 (%) Category 3 (%)
POAG 29 (31.17) 17 (21.79)
PACG 3 (3.84) 3 (3.84)
PXF glaucoma 2 (2.56)
Neovascular glaucoma 1 (1.28) 1 (1.28) 2 (2.56)
Pigment dispersion glaucoma 1 (1.28)
Steroid-induced glaucoma 1 (1.28)
Glaucoma with pseudophakia 5 (6.41) 8 (10.25)
Unspecified glaucoma 2 (2.56) 2 (2.56) 1 (1.28)
Total 43 (55.12) 32 (41.02) 3 (3.84)
The distribution of males compared with females was similar in all categories of glaucoma. The associations of age, sex, IOP, CCT, myopia, hypertension, and diabetes mellitus with POAG were evaluated by logistic regression and the data are presented in Table 4. Subjects with POAG were associated with a higher IOP and lower CCT. Out of 78 subjects with glaucoma, 56 (71.8%) were not aware that they had glaucoma. 
Table 4
 
Multiple Logistic Regressions for Risk Factors for POAG Among Singaporean Indians
Table 4
 
Multiple Logistic Regressions for Risk Factors for POAG Among Singaporean Indians
N OR (95% CI) P
Age group, y
 40–49 911 Ref
 50–59 1000 0.76 (0.31–1.87) 0.543
 60–69 803 1.37 (0.58–3.24) 0.480
 70+ 404 1.83 (0.71–4.72) 0.213
Sex
 Male 1581 Ref
 Female 1538 0.60 (0.32–1.11) 0.104
IOP, mm Hg 3119 1.11 (1.03–1.20) 0.006
CCT, μm 3119 0.99 (0.98–0.99) 0.019
Myopia
 Yes 856 1.14 (0.59–2.20) 0.696
 No 2263 Ref
Hypertension
 Yes 1746 0.91 (0.46–1.77) 0.772
 No 1373 Ref
Diabetes
 Yes 1064 1.13 (0.59–2.18) 0.705
 No 2055 Ref
Analysis estimating the pooled prevalence of POAG (Figure) from 17,258 South Indian subjects aged 40 years and above from three major studies 12,14,22 revealed that an overall prevalence of POAG of 2.04% (95% CI, 1.30%–2.78%). Further, this estimate was 2.53% (95% CI, 0.97%–4.08%) in urban subset of the population and 1.41 (95% CI, 1.04%–2.78%) among the rural subset of the population. 
Figure
 
Pooled prevalence of POAG in South Indians aged 40 years and older (using crude prevalence figures). APEDS, Andhra Pradesh Eye Disease Study 14 ; CGS, Chennai Glaucoma Study 12 ; SINDI, Singapore Indian Eye Study; ACES, Aravind Comprehensive Eye Survey. 22
Figure
 
Pooled prevalence of POAG in South Indians aged 40 years and older (using crude prevalence figures). APEDS, Andhra Pradesh Eye Disease Study 14 ; CGS, Chennai Glaucoma Study 12 ; SINDI, Singapore Indian Eye Study; ACES, Aravind Comprehensive Eye Survey. 22
Discussion
This study is the first epidemiological study to evaluate the prevalence of ocular disease in a migrant Indian population. The overall prevalence of glaucoma among Singaporean Indians was 1.95%, with POAG being the most predominant form at 1.25%. The prevalence of PACG was noted to be rather low at 0.12%. There was a significant increase in glaucoma prevalence with age, and this was higher among females. The glaucoma prevalence in the Singaporean Indian population was significantly lower than that of their Chinese (3.4%) and Malay (3.2%) counterparts in the Tanjong Pagar Eye Study 23 and the Singapore Malay Eye Study, 24 respectively, which used the same definitions and classification criteria. 
The census from year 2000 recorded that Singaporean Indians are predominantly persons with ancestry traced to the southern region of India (from the states of Tamil Nadu and Kerala) and account for 66.6% of the Indian community in Singapore. 25 A detailed analysis of our study sample revealed that the proportion of subjects with a South Indian ancestry was close to 90%. This aspect has important implications because our data become directly comparable to recent studies on subjects from this region in India, such as the Aravind Comprehensive Eye Survey (ACES), 22 Chennai Glaucoma Study (CGS), 12,13 and the Andhra Pradesh Eye Disease Study (APEDS). 14 A compilation of comparative data from glaucoma prevalence from various parts of southern India is shown in Table 5. The POAG prevalence in our study has a close match to the prevalence noted in ACES with both reporting a prevalence of 1.2%. 22 An important aspect of this data is that the population sample in ACES was derived from a predominantly rural setting. In comparison, the CGS reported age-standardized POAG prevalence of 1.57% in the rural arm of their study and APEDS reported a prevalence of 1.6%. 12,14 Although the prevalence of POAG in our sample was lower, the trend follows that of the rural arms of the CGS and APEDS and of note, there is an overlap of the confidence intervals (95% CI, 0.89–1.73 vs. 1.19–1.95 [CGS]; 1.13–2.06 [APEDS]). 12,14 The overall prevalence of POAG in our study samples correspond to the prevalence noted in the rural samples of the ACES, CGS, and APEDS, which is intriguing. Though the Singaporean Indians by all means would be considered highly urbanized, the prevalence of POAG did not match the urban South Indians of the CGS (3.46%) and the APEDS (4.0%). The authors from the CGS study attributed the discrepancy of POAG prevalence between their rural and urban populations to significant socioeconomic and lifestyle differences. 12 Interestingly, these aspects of urbanization did not seem to affect the prevalence of POAG among the Singaporean Indians, who may be considered to have a higher socioeconomic status compared to the rural and urban counterparts in the CGS or the APEDS. The prevalence of PACG was also low at 0.12% and matched that of the Malay subjects in Singapore but was far lower than that reported in native southern Indian population (0.5%–1.8%). 13,14,22 The urban subjects in the CGS 13 and APEDS 14 reported rates of 0.80% and 1.8%, respectively, whereas the prevalence in the rural subjects of ACES, 22 CGS, 13 and APEDS 14 study was 0.5%, 0.85%, and 0.7%, respectively. We have to acknowledge the likelihood of the disparities between the urban glaucoma prevalence rates noted between CGS, APEDS, and our study could be due to differences in methodologies. The definitions of glaucoma in our study and the CGS were based on the ISGEO 18 ; however, in the CGS, gonioscopy and automated perimetry were done for every patient, and this could have contributed to a higher yield of suspected glaucoma cases. Further, factors that could contribute to this large variation could be subjective differences in gonioscopic assessment and the proportion and mean age of nonresponders. We noted that there were 1094 (32.1%) nonresponders for the study; these subjects had a significantly higher mean age than the responders (61.1 vs. 57.8 years; P < 0.001), and this could have also partially contributed to the low prevalence rate. We also considered the possibility of a higher cataract surgery rate in Singapore as a potential cause for lower prevalence of PACG but found that the age-adjusted cataract surgery rates were marginally lower compared to CGS (9.7% vs. 10.16%) 26 and far lower than that reported in APEDS (9.7% vs. 14.6%). 27  
Table 5
 
Age-Standardized Rates of POAG and PACG in Comparative Population Subsets from India and Singapore
Table 5
 
Age-Standardized Rates of POAG and PACG in Comparative Population Subsets from India and Singapore
Study POAG, % (95% CI) PACG, %
Aravind Comprehensive Eye Survey (Rural)24; 1997 1.26 (0.9–1.5) 0.5(0.3–0.7)
Chennai Glaucoma Study (Rural)12,13; 2001* 1.58 (1.19–1.95) 0.87 (0.58–1.16)
Chennai Glaucoma Study (Urban)12,13; 2003* 3.46 (2.9–4.1) 0.88 (0.60–1.16)
Andhra Pradesh Eye Disease Study (Urban)14; 2000* 4.0 (2.74–5.25) 1.8 (0.88–2.70)
Andhra Pradesh Eye Disease Study (Rural)14; 2000* 1.6 (1.13–2.06) 0.7 (0.4–1.1)
Singapore Indian Eye Study (Urban); 2009* 1.25 (0.89–1.73) 0.12 (0.04–0.33)
Singapore Malay Eye Study (Urban)24; 2006* 2.5 (2.4–2.6) 0.12 (0.10–0.14)
Tanjong Pagar Eye Study (Urban)23; 1998* 2.4 (1.6–3.2) 0.8 (0.4–1.3)
The trend of POAG increasing with age 12,14,22,28,29 has been substantiated in our sample as well, and similarly, the risk of glaucoma was twice as much in subjects older than 70 years. Our study noted a higher male preponderance for both POAG and PACG, but this variation in sex distribution was not significant and was similar to the findings noted in the urban subset of APEDS. The CGS also reported equal prevalence of PACG across the sexes in the urban population (17:17) and a female preponderance among the rural population (7:27); however, the authors concluded that this did not translate to significantly higher prevalence of PACG among the rural women. 13 The mean age of our study population was slightly higher at 57.8 ± 10.1 years compared with 54.8 ± 10.6 years in CGS and 53.2 ± 10.9 in APEDS. Despite this, the glaucoma prevalence in our population was lower, and this could be partly attributed to differing study methodologies. 
Glaucoma with pseudophakia was the predominant category of secondary glaucoma at 0.38%, closely matching the reports from APEDS (0.21%), ACES (0.30%), and SIMES (0.42%). 22,24,30 The CGS reported a fairly high prevalence rate of glaucoma associated with aphakia and pseudophakia (urban arm, 0.99%; rural arm, 1.38%). 26,31 The authors of CGS attributed this to inadequate preoperative assessment and poor quality of surgery especially with these zones of the country being served by large-scale rural mass camp surgery programs. 31  
Glaucoma and eye diseases awareness continues to be a major public health issue even in the most developed countries and health care systems. 32,33 More than 70% of subjects in this study were not aware of their glaucoma. Though this is better than the rate of >80% reported in the urban population of CGS, 34 it did not translate to a lower rate of POAG-related visual morbidity among the Singaporean Indians (SINDI, 2.56% versus CGS, 2.2%). In general higher awareness could lead to improved detection because the health-seeking pattern of an aware population is likely to be more robust. The current level of awareness does not seem to translate into this ideal state, and reasons for this could be due to failure of subjects to report for routine eye health screenings, high health care costs, or failure of strategy used in public awareness programs. This indicates that there is a specific need to look into the strategies and approaches that could help overcome this deficit. 
The SINDI study involved a large number of subjects with a long history of migration and had a good response rate (75.6%). The limitations of our study include the lack of visual field and gonioscopy assessments in all subjects, which could have contributed to some underestimation of disease, specifically angle closure. Furthermore, the single reading approach used for IOP measurements and older age of the nonresponders could also have led to underestimation of glaucoma prevalence among the Singaporean Indians. 
In summary, the prevalence of glaucoma among Indian Singaporean persons 40 years of age and older in Singapore was 1.95%, far lower than the Chinese and the Malay cohorts of the same population. POAG was the main form of glaucoma, accounting for 58.9% of disease. Our study involved a large number of subjects with a long history of migration and had a good response rate (75.6%). The prevalence of POAG matched the rural cohorts of the native Southern Indian population and in contrast, the PACG rate was far lower. The effects of urban environment on glaucoma prevalence were not obvious among the Singaporean Indians compared with their South Indian counterparts. 
Acknowledgments
Supported by the Biomedical Research Council (08/1/35/19/550) and the National Medical Research Council, STaR/0003/2008, Singapore. 
Disclosure: A. Narayanaswamy, None; M. Baskaran, None; Y. Zheng, None; R. Lavanya, None; R. Wu, None; W.-L. Wong, None; S.-M. Saw, None; C.-Y. Cheng, None; T.-Y. Wong, None; T. Aung, None 
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Figure
 
Pooled prevalence of POAG in South Indians aged 40 years and older (using crude prevalence figures). APEDS, Andhra Pradesh Eye Disease Study 14 ; CGS, Chennai Glaucoma Study 12 ; SINDI, Singapore Indian Eye Study; ACES, Aravind Comprehensive Eye Survey. 22
Figure
 
Pooled prevalence of POAG in South Indians aged 40 years and older (using crude prevalence figures). APEDS, Andhra Pradesh Eye Disease Study 14 ; CGS, Chennai Glaucoma Study 12 ; SINDI, Singapore Indian Eye Study; ACES, Aravind Comprehensive Eye Survey. 22
Table 1
 
Prevalence of Glaucoma by Age and Sex Among Singaporean Indians
Table 1
 
Prevalence of Glaucoma by Age and Sex Among Singaporean Indians
All Persons Males Females
N n (%) N n (%) N n (%)
All glaucoma
 40–49 y 957 12 (1.25) 465 9 (1.94) 492 3 (0.61)
 50–59 y 1077 17 (1.58) 529 10 (1.89) 548 7 (1.28)
 60–69 y 887 29 (3.27) 464 16 (3.45) 423 13 (3.07)
 70+ y 479 20 (4.18) 248 9 (3.63) 231 11 (4.76)
P for trend 0.006 0.191 0.005
Crude total 3400 78 (2.29) 1706 44 (2.58) 1694 34 (2.01)
Adjusted total* 1.95 (1.51–2.50) 2.29 (1.59–3.24) 1.66 (1.14–2.41)
POAG
 40–49 y 957 11 (1.15) 465 8 (1.72) 492 3 (0.61)
 50–59 y 1077 9 (0.84) 529 7 (1.32) 548 2 (0.36)
 60–69 y 887 15 (1.69) 464 9 (1.94) 423 6 (1.42)
 70+ y 479 11 (2.30) 248 4 (1.61) 231 7 (3.03)
P for trend 0.042 0.870 0.003
Crude total 3400 46 (1.35) 1706 28 (1.64) 1694 18 (1.06)
Adjusted total* 1.25 (0.89–1.73) 1.62 (1.02–2.49) 0.93 (0.54–1.55)
PACG
 40–49 y 957 0 (0.00) 465 0 (0.00) 492 0 (0.00)
 50–59 y 1077 2 (0.19) 529 1 (0.19) 548 1 (0.18)
 60–69 y 887 4 (0.45) 464 3 (0.65) 423 1 (0.24)
 70+ y 479 0 (0.00) 248 0 (0.00) 231 0 (0.00)
P for trend 0.329 0.367 0.709
Crude total 3400 6 (0.18) 1706 4 (0.23) 1694 2 (0.12)
Adjusted total* 0.12 (0.04–0.33) 0.14 (0.04–0.55) 0.09 (0.01–0.45)
Table 2
 
Characteristics and Subtypes of Glaucoma
Table 2
 
Characteristics and Subtypes of Glaucoma
All Median Age, y Males Females M:F Ratio
Any glaucoma 78 (2.29) 63.23 44 (2.58) 34 (2.01) 22:17
Primary glaucoma  52 (1.53) 61.74 32 (1.88) 20 (1.18) 8:5
Secondary glaucoma 26 (0.76) 66.04 12 (0.74) 14 (0.89) 6:7
Types of glaucoma
 POAG 46 (1.35) 61.11 28 (1.64) 18 (1.06) 14:9
 PACG 6 (0.18) 63.50 4 (0.23) 2 (0.12) 2:1
 PXF glaucoma 2 (0.06) 58.94 0 (0.00) 2 (0.12) 0:1
 Neovascular glaucoma 4 (0.12) 56.18 2 (0.12) 2 (0.12) 1:1
 Pigment dispersion glaucoma 1 (0.03) 70.64 1 (0.06) 0 (0.00) 1:0
 Steroid-induced glaucoma 1 (0.03) 61.92 1 (0.06) 0 (0.00) 1:0
 Glaucoma with pseudophakia 13 (0.38) 69.48 7 (0.41) 6 (0.35) 7:6
 Unspecified glaucoma 5 (0.15) 65.85 1 (0.06) 4 (0.24) 1:4
Table 3
 
Glaucoma Diagnosis Based on ISGEO Categorization
Table 3
 
Glaucoma Diagnosis Based on ISGEO Categorization
Glaucoma Subtype Category 1 (%) Category 2 (%) Category 3 (%)
POAG 29 (31.17) 17 (21.79)
PACG 3 (3.84) 3 (3.84)
PXF glaucoma 2 (2.56)
Neovascular glaucoma 1 (1.28) 1 (1.28) 2 (2.56)
Pigment dispersion glaucoma 1 (1.28)
Steroid-induced glaucoma 1 (1.28)
Glaucoma with pseudophakia 5 (6.41) 8 (10.25)
Unspecified glaucoma 2 (2.56) 2 (2.56) 1 (1.28)
Total 43 (55.12) 32 (41.02) 3 (3.84)
Table 4
 
Multiple Logistic Regressions for Risk Factors for POAG Among Singaporean Indians
Table 4
 
Multiple Logistic Regressions for Risk Factors for POAG Among Singaporean Indians
N OR (95% CI) P
Age group, y
 40–49 911 Ref
 50–59 1000 0.76 (0.31–1.87) 0.543
 60–69 803 1.37 (0.58–3.24) 0.480
 70+ 404 1.83 (0.71–4.72) 0.213
Sex
 Male 1581 Ref
 Female 1538 0.60 (0.32–1.11) 0.104
IOP, mm Hg 3119 1.11 (1.03–1.20) 0.006
CCT, μm 3119 0.99 (0.98–0.99) 0.019
Myopia
 Yes 856 1.14 (0.59–2.20) 0.696
 No 2263 Ref
Hypertension
 Yes 1746 0.91 (0.46–1.77) 0.772
 No 1373 Ref
Diabetes
 Yes 1064 1.13 (0.59–2.18) 0.705
 No 2055 Ref
Table 5
 
Age-Standardized Rates of POAG and PACG in Comparative Population Subsets from India and Singapore
Table 5
 
Age-Standardized Rates of POAG and PACG in Comparative Population Subsets from India and Singapore
Study POAG, % (95% CI) PACG, %
Aravind Comprehensive Eye Survey (Rural)24; 1997 1.26 (0.9–1.5) 0.5(0.3–0.7)
Chennai Glaucoma Study (Rural)12,13; 2001* 1.58 (1.19–1.95) 0.87 (0.58–1.16)
Chennai Glaucoma Study (Urban)12,13; 2003* 3.46 (2.9–4.1) 0.88 (0.60–1.16)
Andhra Pradesh Eye Disease Study (Urban)14; 2000* 4.0 (2.74–5.25) 1.8 (0.88–2.70)
Andhra Pradesh Eye Disease Study (Rural)14; 2000* 1.6 (1.13–2.06) 0.7 (0.4–1.1)
Singapore Indian Eye Study (Urban); 2009* 1.25 (0.89–1.73) 0.12 (0.04–0.33)
Singapore Malay Eye Study (Urban)24; 2006* 2.5 (2.4–2.6) 0.12 (0.10–0.14)
Tanjong Pagar Eye Study (Urban)23; 1998* 2.4 (1.6–3.2) 0.8 (0.4–1.3)
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