September 2003
Volume 44, Issue 9
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Glaucoma  |   September 2003
Determinants of Intraocular Pressure and Its Association with Glaucomatous Optic Neuropathy in Chinese Singaporeans: The Tanjong Pagar Study
Author Affiliations
  • Paul J. Foster
    From the Singapore National Eye Centre and Singapore Eye Research Institute; the
    Institute of Ophthalmology, University College London, United Kingdom; the
    Glaucoma Research Unit, Moorfields Eye Hospital, London, United Kingdom; the
  • David Machin
    Division of Clinical Trials and Epidemiological Sciences, National Cancer Centre, Singapore; the
  • Tien-Yin Wong
    From the Singapore National Eye Centre and Singapore Eye Research Institute; the
    Departments of Ophthalmology and
  • Tze-Pin Ng
    Community, Occupational and Family Medicine, National University, Singapore.
  • Jim F. Kirwan
    Institute of Ophthalmology, University College London, United Kingdom; the
  • Gordon J. Johnson
    Institute of Ophthalmology, University College London, United Kingdom; the
  • Peng T. Khaw
    Institute of Ophthalmology, University College London, United Kingdom; the
    Glaucoma Research Unit, Moorfields Eye Hospital, London, United Kingdom; the
  • Steve K. L. Seah
    From the Singapore National Eye Centre and Singapore Eye Research Institute; the
    Departments of Ophthalmology and
Investigative Ophthalmology & Visual Science September 2003, Vol.44, 3885-3891. doi:10.1167/iovs.03-0012
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      Paul J. Foster, David Machin, Tien-Yin Wong, Tze-Pin Ng, Jim F. Kirwan, Gordon J. Johnson, Peng T. Khaw, Steve K. L. Seah; Determinants of Intraocular Pressure and Its Association with Glaucomatous Optic Neuropathy in Chinese Singaporeans: The Tanjong Pagar Study. Invest. Ophthalmol. Vis. Sci. 2003;44(9):3885-3891. doi: 10.1167/iovs.03-0012.

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      © 2016 Association for Research in Vision and Ophthalmology.

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Abstract

purpose. To examine the relationship between intraocular pressure (IOP), anthropomorphic, demographic, socioeconomic, systemic, and ocular factors and glaucomatous optic neuropathy (GON) in Chinese people.

methods. Chinese people (n = 2000), aged 40 to 79 years, were selected from the Singapore electoral register. Of the 1717 considered eligible for examination, 1232 participated, representing a response rate of 71.8%. IOP was estimated with Goldmann applanation tonometry. The drainage angle was assessed with static and dynamic gonioscopy. The optic nerve was examined at high magnification through a dilated pupil with a fundus contact lens or a +78-D lens. Static automated visual field testing was performed on subjects with suspected glaucoma. GON was diagnosed on the basis of structural and functional abnormalities of the optic nerve.

results. The main independent determinants of higher IOP were higher systolic blood pressure (P < 0.001), quadrants of any peripheral anterior synechiae (PAS, P = 0.02) and width of the drainage angle (P = 0.049). A 100-μm increase in corneal thickness was associated with an increase in mean IOP of 1.5 to 1.8 mm Hg (P < 0.001). Odds of GON increased 1.2 times per 1-mm Hg increase in screening IOP. A clear association between corneal thickness and GON was not identified.

conclusions. Clinical IOP estimates are related to systolic blood pressure and corneal thickness. Variation in IOP with angle width may suggest that trabecular compaction significantly contributes to causes of the increase in IOP, independent of angle-closure. GON is an IOP-related phenomenon among Chinese Singaporeans.

Mean intraocular pressure (IOP) in the white population of Europe and North America is higher than that of East Asian populations by some 2 to 5 mm Hg. 1 2 3 4 5 6 7 Based on cross-sectional data, it is has been reported that IOP tends to increase with age in Europeans, 1 2 whereas the opposite appears to occur in Asians. 8 Glaucomatous optic neuropathy (GON) in East Asians reportedly occurs at lower levels of IOP than is typical among European whites. 4  
Both ocular and systemic factors influence clinical estimates of IOP. Central corneal thickness (CCT) correlates with measured IOP in populations. 9 10 Studies comparing manometric IOP measurements with estimates obtained using tonometers have shown an error related to CCT. 11 12 The clinical implications of this phenomenon are underlined by the finding that patients with ocular hypertension (OHT) have significantly thicker corneas than do patients with glaucoma and people with normal eyes. 13 A decrease in CCT with age has been documented in people of East Asian origin, 10 14 15 offering an attractive explanation for the decrease in IOP with age in East Asians. A recent longitudinal study suggested that CCT was a significant, independent predictor of transition from OHT to definite glaucoma, raising the question of exactly how CCT, OHT, and glaucoma are related. 16  
Systolic blood pressure (sBP), age, female gender, the use of alcohol or tobacco smoking, family history of glaucoma, and higher body mass index (BMI) have been found to be positively associated with IOP. 17 18 A modest association between POAG and BP has been described, although the effect is modified by age, with a stronger correlation in older people. When the perfusion pressure (BP minus IOP) was calculated, a strong inverse correlation was found with POAG. This is regarded as an indication that a failure of autoregulation is partially responsible for the development of POAG. 19  
In light of the reported differences between Europeans and East Asians in distribution of IOP and the relationship between IOP and GON, we sought to characterize the distribution of IOP in a Chinese population, with particular reference to ocular features such as CCT. 
Methods
This study was performed in accordance with the World Medical Association’s Declaration of Helsinki. The Ethics Review Board of Singapore National Eye Centre approved the study. The sampling strategy has been described previously. 20 21 In brief, 2000 Chinese Singaporeans aged 40 to 79 years residing in Tanjong Pagar district were selected from the electoral register (13% of the total of 15,082), using a disproportionate, stratified, clustered, random sampling procedure. A total of 1717 were considered eligible for examination, after exclusion of those who were ill, had moved from the area, or had died. Of these, 1090 people were examined in the research clinic (63.5% of the total). A further 142 people were examined in their homes, bringing the total number of participants to 1232. These people underwent a modified and abbreviated examination. Data described in the analysis of determinants of IOP are drawn from examinations performed in the 1090 subjects who underwent a full examination in the clinic. Data on the association between GON and cross-sectional IOPs are drawn from examination of all 1232 subjects. 
A slit lamp (Model BQ 900; Haag-Streit, Bern, Switzerland) was used to examine the anterior segment for evidence of secondary glaucoma and to detect ischemic sequelae of primary angle closure. IOP was estimated with an applanation tonometer (Goldmann model; Haag-Streit). The cornea was anesthetized with 0.5% amethocaine hydrochloride mixed with 1 drop of 2% sodium fluorescein (Minims; Chauvin Pharmaceuticals, Romford, UK). Three readings were made, and the median taken as the pressure for that eye. Gonioscopy was performed with a Goldmann-type one-mirror lens (Model 902; Haag-Streit) at ×25 magnification with low ambient illumination. The width of the iridotrabecular recess was graded according to the angle subtending between the plane of the trabecular surface and a tangent extended from the junction between the outer and middle thirds of the iris. The estimate of the angle was divided into five categories: 0°, 10°, 20°, 30°, and 40° or more, recorded as grades 0 to 4 in each quadrant. Peripheral anterior synechiae (PAS) were recorded as present or absent in four quadrants after either dynamic examination with a Goldmann-type gonioscope. If a high pressure gradient across the iris was encountered, an indentation examination was performed with a four-mirror gonioscope (Sussmann model; Ocular Instruments, Bellevue, WA). A cumulative angle width score was derived by summing the grade in four quadrants to give a total score of 0 to 16. 
CCT was measured with an optical pachymeter (Device I; Haag-Streit) mounted on the slit lamp. The touch method of measuring CCT was used throughout. CCT was measured from the anterior to the posterior endothelial surface using ×1.6 objective magnification with +2.5-D eyepiece addition, read to the nearest 0.01 mm. CCT was measured three times in each eye and the median taken as the representative value for that eye. The subject was instructed to maintain a steady gaze in the primary position. The brightest, narrowest illumination beam possible was used. The measurements of axial CCT were made, with the pupil margin used as a point of reference to ensure accurate centration. Anterior chamber depth (ACD), lens thickness (LT), and axial length (AL) of the globe were measured by A-mode ultrasound (Compuscan LT; Storz, St. Louis, MO). The mean of sixteen individual measurements for each parameter was taken. If the SD was less than or equal to 0.13 mm, the measurements were repeated up to three times. 
Systemic blood pressure was measured in the right arm of seated subjects by a nurse using a mercury sphygmomanometer. Subject’s height was measured without shoes, and weight in kilograms recorded using bathroom scales with a digital display. BMI was calculated as (height in m)2/weight in kilograms. Demographic and socioeconomic data were recorded with a standardized questionnaire that has been described. 21  
The method of diagnosing glaucoma has been described. 20 22 In this analysis, the cases of glaucoma reported herein were diagnosed according to both characteristic structural and functional evidence of optic neuropathy, or (if visual function was affected to the extent that automated field testing was not feasible) evidence of severe structural disc damage. After pharmacological dilation of the pupils, The optic disc was examined at a slit lamp with a fundus contact lens and ×40 magnification. The vertical dimensions of the disc and cup were measured with an eyepiece graticule etched in 0.1-mm units (Haag-Streit). A threshold central 30° visual field (30-2 pattern) test was performed (Model 750; Humphrey Instruments, San Leandro, CA). A glaucoma hemifield test (GHT) result outside normal limits and a cluster of four contiguous points on the pattern deviation plot (P < 5% of occurring in age-matched normal subjects) not crossing the horizontal meridian were considered compatible with glaucoma. 
Backward linear regression analysis was used to assess the relationship between demographic factors (age and gender), systemic variables (sBP, dBP, height and weight), and ocular factors (CCT, ACD and LT) and the estimates of IOP. Multiple logistic regression was used to examine the relationship between GON and screening IOP, corrected for age and gender. 
Results
Table 1 shows the mean right-eye IOP in men and women by decade age groups. In a univariate linear regression model, mean IOP increased by 0.3 mm Hg per decade age increase (P < 0.001). Mean age- and gender-specific CCT in right eyes is summarized in Table 2 . Mean CCT decreased with age in both men and women (men: 6 μm per decade; women: 4 μm per decade, both P ≤ 0.001). There was no significant difference in mean CCT between genders (P = 0.78). Table 3 shows age- and gender-specific mean sBP and dBP. Multiple linear regression (BP on age and gender) shows that mean sBP increased by 11 mm Hg per decade (P < 0.001) and had a tendency to be higher (2.8 mm Hg) in women than in men, although this was not statistically significant (P = 0.057). By contrast, dBP did not increase significantly with age (0.7 mm Hg/decade, P = 0.07), but was higher in men than women by 2.5 mm Hg (P = 0.003). 
Table 4 gives regression coefficients and probabilities of the null hypothesis for regression models of single anthropomorphic, socioeconomic, systemic, and ocular factors on IOP estimates. Nine factors were significantly associated with IOP: age (P < 0.001), sBP (P < 0.001), dBP (P < 0.001), height (P = 0.004), individual income (P = 0.015), corneal thickness (P < 0.001), quadrants of PAS (P < 0.001), width of the drainage angle (P = 0.024), and previous glaucoma surgery (P < 0.001). A multiple regression model was then calculated including all nine variables, in which age (P = 0.795), income (P = 0.849), diastolic BP (P = 0.969), height (P = 0.401), and previous glaucoma surgery (P = 0.393) were not statistically significant. A final regression model was calculated using sBP, CCT, quadrants with any PAS, and angle width. In this model, a 10-μm increase in CCT would be associated with a 0.15 mm Hg increase in measured IOP (P < 0.001). A 10-mm Hg increase in systolic BP would be associated with a 0.3-mm Hg increase in IOP. A mean increase in IOP of 0.6 mm Hg would be expected per quadrant of drainage angle with any PAS. A very small increase in IOP was associated with narrowing angle width. This remained significant even after controlling for manifestations of angle-closure (presence of PAS). The magnitude of the difference would be on the order of 0.2 mm Hg per 10° change in width in all four quadrants (P = 0.049). The final regression model accounted for 8.6% of all variation in IOP in this data set (adjusted R 2 = 0.086). Very similar results were obtained when the analysis was repeated for left eyes. Table 5 summarizes the multiple regression models. The absolute magnitude of the standardized regression coefficient indicates the relative importance of a variable as a determinant of IOP. sBP appears to be the most important variable in our models. 
Table 6 shows the number and proportion of people with GON according to mean CCT. The rate of GON appeared lower in people with thinner corneas; CCT 520 μm or less, GON 0.8% (95% CI: 0.2, 2.8); CCT 530 to 560 μm, GON 2.6% (95% CI: 1.6, 4.3); and CCT 570 μm or more, GON 2.9% (95% CI: 1.4, 5.9). Mean corneal thickness was not significantly different between people with and without GON (respectively, 551 μm and 542 μm, P = 0.15). 
Sixty eyes of 45 people were classified as having GON. Among these, 35 eyes were untreated. IOP estimates were obtained in 2163 eyes, with a mean IOP of 14.6 mm Hg. Among the 35 untreated eyes, 17 (49%) had a screening IOP of 19 mm Hg or less, representing 0.8% of the total number (2029) in this IOP range. There were 134 eyes with a screening IOP of more than 19 mm Hg, 18 of which (13%) had GON. Figure 1 is a histogram showing the distribution of screening IOP in all eyes against the rate of GON in six IOP categories. There was a clear increase in the rate of GON with screening IOP: IOP 20 to 24 mm Hg, 6%; IOP 25 to 29 mm Hg, 50%, IOP 30 to 34 mm Hg, 60%; and IOP more than 35 mm Hg, 67%. Figure 2 is another frequency histogram showing number of eyes newly diagnosed with GON at different levels of screening IOP. To further quantify the association between IOP and GON, we excluded previously diagnosed cases of glaucoma from the analysis. Multiple logistic regression suggested that the odds of GON increased by 1.20 (P = 0.0003, 95% CI: 1.09, 1.32) times per 1 mm Hg increase in IOP, after correction for age and gender. 
Discussion
The nature of the relationship between IOP and GON has enjoyed a resurgence of interest recently, with the role of CCT being the catalyst for further debate. A recent study suggested that a thinner CCT is a powerful predictor of development of POAG. 16 As a consequence, we thought it was important to include CCT in this analysis. However, we were not able to detect any similar association between thinner CCT and GON attributable to POAG, primary angle-closure glaucoma (PACG), or secondary disease. 
Both CCT and sBP were found to have a significant positive association with measured IOP. Of the two of these, sBP appears to be the more important factor in determining the measured IOP. We did not detect a consistent relationship between age, height, weight, or BMI and IOP, after correcting for other factors. The finding of an association between CCT and IOP estimates suggests a measurement error caused by variation in corneal thickness. We have documented a positive association between CCT and IOP in Mongolians. An increase of 10 μm in CCT was associated with an increase of 0.19 mm Hg and 0.24 mm Hg in right and left eyes, respectively. 10 The corresponding figures for Chinese Singaporeans were 0.15 and 0.19 mm Hg. These data initially do not seem very indicative. To appreciate the implication of the data fully, they must be considered in the context of the interindividual variation in CCT in this population. The SD of corneal thickness in each decade of our study population was fairly uniform at approximately 30 μm. Hence, 95% of the members of a decade age-group would be encompassed within a range of 120 μm (and, necessarily, 5% of the population would lie outside this range). This suggests that, in Chinese Singaporeans, a variations of between 1.8 mm Hg (from right eye data) and 2.3 mm Hg (from left eye data) in IOP estimates made with the Goldmann tonometer are attributable to the variation in CCT among people of the same age. There was a small but highly significant decrease in CCT with age, being equivalent to 23 μm between the ages of 40 and 80 years. This age-related difference, superimposed on the interindividual differences in CCT within each age group, may result in a difference in IOP estimates of up to 2.7 mm Hg between a 40-year-old man with a CCT of 2 SD above the mean (i.e., upper end of the normal range) and an 80-year-old whose CCT was 2 SD below the mean (i.e., lower end of the normal range). 
In a random, population-based sample of residents of Rotterdam, The Netherlands, Wolfs et al. 9 found that an increase in CCT of 10 μm was associated with an increase in population mean IOP of 0.19 mm Hg. Although the Dutch study and our work in Mongolia and Singapore used different methods of measuring CCT, the similarity in the calculated effect of CCT on IOP measurements is striking. In the Dutch cohort, with a mean age of 72 years, the mean CCT was 537 μm. 9 In subjects in Mongolia aged 70 or more years (mean, 75.1), the mean CCT was 475 μm right eye and 493 μm left eye. Among the Singapore cohort, mean CCT was 535 μm among people in their 70s, a negligible difference from the Dutch. 
It appears that variation in IOP estimates obtained by applanation tonometry is significantly influenced by interindividual variation in CCT. The relationship between IOP and GON in East Asian people is probably impossible to understand fully without recourse to manometric investigation. In just such a study, we found that both applanation and handheld tonometry (Tonopen; Mentor, Norwell, MA) significantly underestimate true IOP. However, there was no demonstrable association between ocular dimensions or corneal thickness and IOP in the small number of subjects examined. It was assumed that the relatively small effect of ocular biometric factors was masked by a larger effect, probably attributable to the mechanical properties of ocular tissues (most likely an index of rigidity/deformability). 23  
To the best of our knowledge, the finding of a small but statistically significant inverse association between IOP and width of the drainage angle is unique in population studies. Eyes with wider angles have a lower IOP, probably reflecting a greater outflow facility in wider angles, attributable to altered microarchitecture of the trabecular beams. Trabecular compaction caused by increasing lens thickness and reduced zonular traction on the ciliary body is one possible explanation. This is biologically plausible, given the decline in IOP that often occurs after cataract surgery 24 and the effect of pilocarpine on IOP through traction on the scleral spur. 
There seems to be no doubt that an elevated IOP confers an increased risk of glaucoma. Cross-sectional studies in European whites estimate the prevalence of GON as 7% in the range of 25 to 29 mm Hg, and 14% in the 30 to 34 mm Hg. 25 Among otherwise normal subjects with an IOP more than mean + 2 SD, the incidence of glaucomatous visual field loss is approximately 1% per year. 26 27 The risk of POAG damage increases nonlinearly at higher IOP; compared with an IOP less than 22 mm Hg, the relative risk (RR) with an IOP of 22 to 29 mm Hg is 12.9 and with IOP of 30 mm Hg or more, the RR is 40. 5 Between 30% and 50% of GON in a population occurs in those individuals with a screening IOP of population mean + 2 SD or less. This is not difficult to reconcile, when considering the large number of people with IOP in the normal range and, proportionally, the much smaller number of people with GON. The ratio reverses at higher levels of IOP (Fig. 1) , although this observation emphasizes the weakness of an approach that considers IOP to be a diagnostic criterion for glaucoma. 
A relationship between cross-sectional IOP measurements and the presence of glaucoma has also been shown in Japanese people. 4 The findings in this study are intriguing when one considers that, first, open-angle glaucoma is the main form of GON in Japanese people and second that mean IOP in this large population study was found to be 13.3 mm Hg (measured by air-puff tonometer). Cases diagnosed as normal-tension glaucoma outnumbered POAG by a ratio of 4.5:1. However, the division between high and normal IOP was placed at 21 mm Hg. This figure was derived from a European population and was obtained by taking an IOP 2 SD above the mean. If the same approach were adopted for the Japanese population, an IOP of 18 or 19 mm Hg would seem more appropriate. Our data suggest that Chinese Singaporean people have an IOP that is typically slightly lower than that in persons of white European background. However, we also found a clear association between cross-sectional IOP measurements and glaucoma in Chinese Singaporeans. Figure 3 shows the relationship between screening IOP and prevalence of GON in selected clinic- and population-based studies. 
In summary, we found that IOP estimates were related to systolic blood pressure and corneal thickness. Variation in IOP with angle width may suggest that trabecular compaction significantly contributes to causes of increased IOP, independent of angle-closure. We believe GON is an IOP-related phenomenon among Chinese Singaporeans. Any statements regarding the role of IOP must be made with the caveat that estimation of this parameter is subject to considerable error. However, the prevalence of glaucoma as a cause of visual morbidity in Asia means this field warrants further study, given that glaucoma is the leading cause of irreversible blindness. 
 
Table 1.
 
IOP in Chinese Singaporeans
Table 1.
 
IOP in Chinese Singaporeans
Mean (95% CI) SD n Missing
Men
 40–49 14.4 (13.8, 14.9) 3.0 119 6
 50–59 15.2 (14.5, 15.8) 3.2 108 9
 60–69 15.7 (14.9, 16.5) 5.1 153 20
 70–79 15.6 (14.8, 16.3) 4.0 107 23
 80+ 15.6 (12.6, 18.7) 3.6 8 4
Women
 40–49 14.5 (14.0, 15.0) 2.9 140 11
 50–59 15.5 (15.1, 16.0) 3.0 176 13
 60–69 15.2 (14.7, 15.7) 2.9 143 26
 70–79 16.1 (15.4, 16.7) 3.8 126 29
 80+ 17.8 (13.0, 22.5) 5.7 8 3
Men and women
 40–49 14.5 (14.1, 14.8) 3.0 259 17
 50–59 15.4 (15.0, 15.7) 3.1 284 22
 60–69 15.5 (15.0, 16.0) 4.2 296 46
 70–79 15.8 (15.3, 16.3) 3.9 233 52
 80+ 16.7 (14.2, 19.2) 4.7 16 7
Table 2.
 
Central Corneal Thickness in Chinese Singaporeans
Table 2.
 
Central Corneal Thickness in Chinese Singaporeans
Mean CCT (95% CI) SD n Missing
Men
 40–49 548.6 (543, 554) 28.5 117 4
 50–59 543.7 (538, 550) 32.4 107 1
 60–69 535.1 (530, 540) 30.5 151 2
 70–79 532.8 (526, 540) 34.7 101 6
 80+ 528.6 (490, 567) 41.4 7 1
Women
 40–49 545.8 (540, 552) 34.8 138 2
 50–59 539.9 (536, 544) 27.8 175 1
 60–69 536.5 (531, 542) 30.7 141 2
 70–79 536.2 (531, 542) 31.2 122 4
 80+ 521.3 (506, 536) 18.1 8 0
Men and women
 40–49 547.1 (543, 551) 32.1 255 6
 50–59 541.4 (538, 545) 29.7 282 2
 60–69 535.8 (532, 539) 30.6 292 4
 70–79 534.7 (530, 539) 32.8 223 10
 80+ 524.7 (508, 541) 30.2 15 1
Table 3.
 
Systolic and Diastolic Blood Pressure in Singaporean Chinese
Table 3.
 
Systolic and Diastolic Blood Pressure in Singaporean Chinese
Mean Systolic BP (95% CI) SD Mean Diastolic BP (95% CI) SD n Missing
Men
 40–49 125.5 (121.9, 128.6) 18.7 86.1 (83.5, 88.8) 14.5 120 1
 50–59 137.5 (133.0, 141.9) 23.3 86.8 (84.1, 89.5) 14.0 107 1
 60–69 145.5 (141.7, 149.3) 23.6 88.2 (86.0, 90.4) 13.8 152 1
 70–79 151.6 (146.0, 157.1) 29.9 84.1 (81.5, 86.8) 14.2 113 2
Women
 40–49 122.5 (119.4, 125.7) 18.9 80.4 (78.0, 82.8) 14.4 140 0
 50–59 139.2 (135.1, 143.3) 27.6 83.5 (81.4, 85.6) 13.9 176 0
 60–69 147.2 (143.1, 151.4) 25.1 86.6 (84.4, 88.7) 13.0 142 1
 70–79 162.0 (157.5, 166.5) 26.2 84.9 (82.3, 87.4) 14.7 132 2
Men and women
 40–49 123.8 (121.5, 126.1) 18.8 83.1 (81.3, 84.9) 14.7 260 1
 50–59 138.6 (135.5, 141.6) 26.0 84.8 (83.1, 86.4) 14.0 283 1
 60–69 146.3 (143.5, 149.1) 24.3 87.4 (85.9, 89.0) 13.4 294 2
 70–79 157.2 (153.6, 160.7) 28.4 84.5 (82.7, 86.4) 14.5 245 4
Table 4.
 
An Exploratory Regression Analysis of Factors Associated with IOP Estimates
Table 4.
 
An Exploratory Regression Analysis of Factors Associated with IOP Estimates
Variable Coding Regression Coefficient 95% CI P R 2
Age (decade) 0.372 0.18, 0.57 <0.001 0.012
Gender Men = 1, women = 2 0.28 −0.16, 0.72 0.21 0.001
Height (10 cm) −0.39 −0.65, −0.13 0.004 0.008
Weight (kg) 0.0007 −0.002, 0.004 0.618 0.000
BMI (m2/kg) 0.0003 −0.002, 0.003 0.832 0.000
Systolic BP (mm Hg) 0.031 0.023, 0.039 <0.001 0.052
Diastolic BP (mm Hg) 0.031 0.016, 0.047 <0.001 0.015
History of MI No = 0, yes = 1 −0.023 −0.561, 0.515 0.934 0.000
History of stroke No = 0, yes = 1 0.177 −0.496, 0.851 0.606 0.000
History of diabetes No = 0, yes = 1 0.025 −0.035, 0.087 0.407 0.001
Self-reported smoker No = 0, yes = 1 −0.432 −0.961, 0.097 0.109 0.002
Cigarettes/day −0.012 −0.062, 0.037 0.618 0.001
Blood pressure medication No = 0, Diuretic or β-blocker = 1 0.093 −0.243, 0.429 0.588 0.000
Calcium channel-blocker = 2
Educational level (see footnote) −0.219 −0.454, 0.016 0.068 0.003
Housing type (see footnote) −0.029 −0.317, 0.259 0.844 0.000
Individual income (see footnote) −0.218 −0.393, −0.043 0.015 0.005
Household income (see footnote) −0.115 −0.301, 0.702 0.227 0.002
AC Depth (mm) −0.149 −0.742, 0.445 0.623 0.000
Axial length (mm) −0.101 −0.272, 0.069 0.244 0.000
Corneal thickness (10 μm) 0.120 0.05, 0.189 =0.001 0.010
Spherical refraction (D) −0.026 −0.11, 0.057 0.540 0.000
Quadrants of PAS 0 to 4 0.66 0.318, 1.005 <0.001 0.012
Drainage angle width 0 to 4 −0.061 −0.115, −0.008 0.024 0.004
Pseudophakic No = 0, yes = 1 −0.18 −0.92, 0.56 0.634 0.000
Topical glaucoma No = 0, yes = 1 1.89 −1.333, 5.105 0.251 0.001
Medication
Glaucoma surgery No = 0, yes = 1 6.017 3.33, 8.698 <0.001 0.018
Table 5.
 
Multiple Linear Regression Models of Significant Determinants of IOP
Table 5.
 
Multiple Linear Regression Models of Significant Determinants of IOP
Right Eyes Left Eyes
Un-standardized Coefficient Standardized Coefficient P Un-standardized Coefficient Standardized Coefficient P
Systolic BP (per 10 mm Hg) 0.31 (0.23, 0.38) 0.241 <0.001 0.31 (0.24, 0.38) 0.254 <0.001
CCT (per 100 μm) 1.5 (0.9, 2.1) 0.137 <0.001 1.8 (1.3, 2.5) 0.174 <0.001
Quadrants with any PAS 0.58 (0.23, 0.94) 0.096 =0.001 0.37 (0.05, 0.69) 0.066 =0.025
Cumulative gonioscopic angle width (10° change in each quadrant) −0.05 (−0.10, 0.00) −0.059 =0.049 −0.07 (−0.12, −0.02) −0.081 =0.006
Model summary P < 0.001; adjusted R 2 = 0.086 P < 0.001; adjusted R 2 = 0.11
Table 6.
 
Number and Proportion of Cases with Definite GON by CCT
Table 6.
 
Number and Proportion of Cases with Definite GON by CCT
≤500 501–520 521–540 541–560 561–580 ≥581 Total
No GON 80 170 272 281 158 75 1036
GON 1 1 9 6 5 2 24
%GON (95% CI) 1.2 (0.2, 6.7) 0.6 (0.1, 3.2) 3.2 (1.7, 6.0) 2.1 (1.0, 4.5) 3.1 (1.3, 7.0) 2.6 (0.7, 9.0) 2.3 (1.5, 3.3)
Figure 1.
 
Population distribution of IOP and rate of GON in Chinese Singaporeans. Frequency histogram shows the screening IOP distribution of both eyes of Singaporean subjects (left axis) and the rate of previously undiagnosed GON (number of eyes, right axis) in six IOP categories.
Figure 1.
 
Population distribution of IOP and rate of GON in Chinese Singaporeans. Frequency histogram shows the screening IOP distribution of both eyes of Singaporean subjects (left axis) and the rate of previously undiagnosed GON (number of eyes, right axis) in six IOP categories.
Figure 2.
 
Absolute number of previously undiagnosed eyes with GON, given in seven IOP categories.
Figure 2.
 
Absolute number of previously undiagnosed eyes with GON, given in seven IOP categories.
Figure 3.
 
The relationship between screening IOP and prevalence of GON in selected clinic-based (Finland 25 and Norway 28 ) and population-based (Baltimore, 5 Japan, and 4 Singapore, current) studies.
Figure 3.
 
The relationship between screening IOP and prevalence of GON in selected clinic-based (Finland 25 and Norway 28 ) and population-based (Baltimore, 5 Japan, and 4 Singapore, current) studies.
The authors thank Uma Rajan, BM, BS, for providing, with the late Sek-Jin Chew, FRCS(Ed), MSc, PhD, supplementary resources; Judy Hall, COT, for training technical staff and providing quality assurance services; the Clinical Audit Department Singapore National Eye Centre for data management; Rachel Ng & Bernie Poh for coordinating community volunteer assistance; and Jason Jong for technical assistance. 
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Figure 1.
 
Population distribution of IOP and rate of GON in Chinese Singaporeans. Frequency histogram shows the screening IOP distribution of both eyes of Singaporean subjects (left axis) and the rate of previously undiagnosed GON (number of eyes, right axis) in six IOP categories.
Figure 1.
 
Population distribution of IOP and rate of GON in Chinese Singaporeans. Frequency histogram shows the screening IOP distribution of both eyes of Singaporean subjects (left axis) and the rate of previously undiagnosed GON (number of eyes, right axis) in six IOP categories.
Figure 2.
 
Absolute number of previously undiagnosed eyes with GON, given in seven IOP categories.
Figure 2.
 
Absolute number of previously undiagnosed eyes with GON, given in seven IOP categories.
Figure 3.
 
The relationship between screening IOP and prevalence of GON in selected clinic-based (Finland 25 and Norway 28 ) and population-based (Baltimore, 5 Japan, and 4 Singapore, current) studies.
Figure 3.
 
The relationship between screening IOP and prevalence of GON in selected clinic-based (Finland 25 and Norway 28 ) and population-based (Baltimore, 5 Japan, and 4 Singapore, current) studies.
Table 1.
 
IOP in Chinese Singaporeans
Table 1.
 
IOP in Chinese Singaporeans
Mean (95% CI) SD n Missing
Men
 40–49 14.4 (13.8, 14.9) 3.0 119 6
 50–59 15.2 (14.5, 15.8) 3.2 108 9
 60–69 15.7 (14.9, 16.5) 5.1 153 20
 70–79 15.6 (14.8, 16.3) 4.0 107 23
 80+ 15.6 (12.6, 18.7) 3.6 8 4
Women
 40–49 14.5 (14.0, 15.0) 2.9 140 11
 50–59 15.5 (15.1, 16.0) 3.0 176 13
 60–69 15.2 (14.7, 15.7) 2.9 143 26
 70–79 16.1 (15.4, 16.7) 3.8 126 29
 80+ 17.8 (13.0, 22.5) 5.7 8 3
Men and women
 40–49 14.5 (14.1, 14.8) 3.0 259 17
 50–59 15.4 (15.0, 15.7) 3.1 284 22
 60–69 15.5 (15.0, 16.0) 4.2 296 46
 70–79 15.8 (15.3, 16.3) 3.9 233 52
 80+ 16.7 (14.2, 19.2) 4.7 16 7
Table 2.
 
Central Corneal Thickness in Chinese Singaporeans
Table 2.
 
Central Corneal Thickness in Chinese Singaporeans
Mean CCT (95% CI) SD n Missing
Men
 40–49 548.6 (543, 554) 28.5 117 4
 50–59 543.7 (538, 550) 32.4 107 1
 60–69 535.1 (530, 540) 30.5 151 2
 70–79 532.8 (526, 540) 34.7 101 6
 80+ 528.6 (490, 567) 41.4 7 1
Women
 40–49 545.8 (540, 552) 34.8 138 2
 50–59 539.9 (536, 544) 27.8 175 1
 60–69 536.5 (531, 542) 30.7 141 2
 70–79 536.2 (531, 542) 31.2 122 4
 80+ 521.3 (506, 536) 18.1 8 0
Men and women
 40–49 547.1 (543, 551) 32.1 255 6
 50–59 541.4 (538, 545) 29.7 282 2
 60–69 535.8 (532, 539) 30.6 292 4
 70–79 534.7 (530, 539) 32.8 223 10
 80+ 524.7 (508, 541) 30.2 15 1
Table 3.
 
Systolic and Diastolic Blood Pressure in Singaporean Chinese
Table 3.
 
Systolic and Diastolic Blood Pressure in Singaporean Chinese
Mean Systolic BP (95% CI) SD Mean Diastolic BP (95% CI) SD n Missing
Men
 40–49 125.5 (121.9, 128.6) 18.7 86.1 (83.5, 88.8) 14.5 120 1
 50–59 137.5 (133.0, 141.9) 23.3 86.8 (84.1, 89.5) 14.0 107 1
 60–69 145.5 (141.7, 149.3) 23.6 88.2 (86.0, 90.4) 13.8 152 1
 70–79 151.6 (146.0, 157.1) 29.9 84.1 (81.5, 86.8) 14.2 113 2
Women
 40–49 122.5 (119.4, 125.7) 18.9 80.4 (78.0, 82.8) 14.4 140 0
 50–59 139.2 (135.1, 143.3) 27.6 83.5 (81.4, 85.6) 13.9 176 0
 60–69 147.2 (143.1, 151.4) 25.1 86.6 (84.4, 88.7) 13.0 142 1
 70–79 162.0 (157.5, 166.5) 26.2 84.9 (82.3, 87.4) 14.7 132 2
Men and women
 40–49 123.8 (121.5, 126.1) 18.8 83.1 (81.3, 84.9) 14.7 260 1
 50–59 138.6 (135.5, 141.6) 26.0 84.8 (83.1, 86.4) 14.0 283 1
 60–69 146.3 (143.5, 149.1) 24.3 87.4 (85.9, 89.0) 13.4 294 2
 70–79 157.2 (153.6, 160.7) 28.4 84.5 (82.7, 86.4) 14.5 245 4
Table 4.
 
An Exploratory Regression Analysis of Factors Associated with IOP Estimates
Table 4.
 
An Exploratory Regression Analysis of Factors Associated with IOP Estimates
Variable Coding Regression Coefficient 95% CI P R 2
Age (decade) 0.372 0.18, 0.57 <0.001 0.012
Gender Men = 1, women = 2 0.28 −0.16, 0.72 0.21 0.001
Height (10 cm) −0.39 −0.65, −0.13 0.004 0.008
Weight (kg) 0.0007 −0.002, 0.004 0.618 0.000
BMI (m2/kg) 0.0003 −0.002, 0.003 0.832 0.000
Systolic BP (mm Hg) 0.031 0.023, 0.039 <0.001 0.052
Diastolic BP (mm Hg) 0.031 0.016, 0.047 <0.001 0.015
History of MI No = 0, yes = 1 −0.023 −0.561, 0.515 0.934 0.000
History of stroke No = 0, yes = 1 0.177 −0.496, 0.851 0.606 0.000
History of diabetes No = 0, yes = 1 0.025 −0.035, 0.087 0.407 0.001
Self-reported smoker No = 0, yes = 1 −0.432 −0.961, 0.097 0.109 0.002
Cigarettes/day −0.012 −0.062, 0.037 0.618 0.001
Blood pressure medication No = 0, Diuretic or β-blocker = 1 0.093 −0.243, 0.429 0.588 0.000
Calcium channel-blocker = 2
Educational level (see footnote) −0.219 −0.454, 0.016 0.068 0.003
Housing type (see footnote) −0.029 −0.317, 0.259 0.844 0.000
Individual income (see footnote) −0.218 −0.393, −0.043 0.015 0.005
Household income (see footnote) −0.115 −0.301, 0.702 0.227 0.002
AC Depth (mm) −0.149 −0.742, 0.445 0.623 0.000
Axial length (mm) −0.101 −0.272, 0.069 0.244 0.000
Corneal thickness (10 μm) 0.120 0.05, 0.189 =0.001 0.010
Spherical refraction (D) −0.026 −0.11, 0.057 0.540 0.000
Quadrants of PAS 0 to 4 0.66 0.318, 1.005 <0.001 0.012
Drainage angle width 0 to 4 −0.061 −0.115, −0.008 0.024 0.004
Pseudophakic No = 0, yes = 1 −0.18 −0.92, 0.56 0.634 0.000
Topical glaucoma No = 0, yes = 1 1.89 −1.333, 5.105 0.251 0.001
Medication
Glaucoma surgery No = 0, yes = 1 6.017 3.33, 8.698 <0.001 0.018
Table 5.
 
Multiple Linear Regression Models of Significant Determinants of IOP
Table 5.
 
Multiple Linear Regression Models of Significant Determinants of IOP
Right Eyes Left Eyes
Un-standardized Coefficient Standardized Coefficient P Un-standardized Coefficient Standardized Coefficient P
Systolic BP (per 10 mm Hg) 0.31 (0.23, 0.38) 0.241 <0.001 0.31 (0.24, 0.38) 0.254 <0.001
CCT (per 100 μm) 1.5 (0.9, 2.1) 0.137 <0.001 1.8 (1.3, 2.5) 0.174 <0.001
Quadrants with any PAS 0.58 (0.23, 0.94) 0.096 =0.001 0.37 (0.05, 0.69) 0.066 =0.025
Cumulative gonioscopic angle width (10° change in each quadrant) −0.05 (−0.10, 0.00) −0.059 =0.049 −0.07 (−0.12, −0.02) −0.081 =0.006
Model summary P < 0.001; adjusted R 2 = 0.086 P < 0.001; adjusted R 2 = 0.11
Table 6.
 
Number and Proportion of Cases with Definite GON by CCT
Table 6.
 
Number and Proportion of Cases with Definite GON by CCT
≤500 501–520 521–540 541–560 561–580 ≥581 Total
No GON 80 170 272 281 158 75 1036
GON 1 1 9 6 5 2 24
%GON (95% CI) 1.2 (0.2, 6.7) 0.6 (0.1, 3.2) 3.2 (1.7, 6.0) 2.1 (1.0, 4.5) 3.1 (1.3, 7.0) 2.6 (0.7, 9.0) 2.3 (1.5, 3.3)
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