To determine correlates of central corneal thickness (CCT) and its relationship to intraocular pressure (IOP) in a Burmese population.
We performed a population-based survey of inhabitants 40 years or older in Myanmar; of 2076 participants, data from 1909 nonglaucomatous subjects who underwent ultrasound pachymetry and Goldmann applanation tonometry were analyzed. Linear mixed effects models adjusting for nonindependence of right and left eye data were constructed.
Mean (SD) CCT was 521.9 (33.3) μm, and the mean (SD) IOP was 14.5 (3.4) mm Hg. Intraocular pressure and spherical equivalent were significant predictors of CCT (P < .001 and P = .01, respectively). Age, sex, body mass index, and corneal curvature were not significant predictors. Central corneal thickness was the only significant predictor of IOP (ie, an increase of 100 μm in CCT predicted an increase of 1.3 mm Hg in IOP). The Spearman correlation between CCT and IOP for the right and left eyes was highly significant (P < .001), but the Spearman rank correlation values (R2 = 0.016 and R2 = 0.017, respectively) were weak.
The CCT in this Burmese population was significantly associated with IOP and spherical equivalent. The weak association between CCT and IOP is consistent with that of other population-based studies. Other corneal factors are likely to influence Goldmann applanation tonometry.
The theoretical influence1 of central corneal thickness (CCT) on intraocular pressure (IOP) measurement by Goldmann applanation tonometry (GAT) has been demonstrated in several studies,2-12 and pachymetry has become an established part of glaucoma practice, despite lack of a clear understanding of the relationship between CCT and IOP.6,13,14
There is considerable racial variation in CCT.6,10,12 Although most studies have reported a significant positive correlation between CCT and IOP,6 the relationship is often weak. In the Barbados Eye Studies, no significant correlation between CCT and IOP was found.15
Although glaucoma, particularly angle-closure glaucoma, is a major ophthalmic problem in East Asia,16,17 data about CCT and its relationship to IOP in East Asian populations are limited.4,5,18 There is evidence that CCT varies within Asian subgroups (Chinese, Filipino, and Japanese).12 Foster et al4 reported a significant association between CCT and IOP in a Mongolian population and, more recently, Suzuki et al18 reported a significant but weak correlation in a Japanese population.
Herein, we report data concerning factors associated with CCT and IOP and explore the relationship between these 2 variables in a nonglaucomatous Burmese population.
The Meiktila Eye Survey was a population-based, cross-sectional ophthalmic survey of the residents of rural villages in the Meiktila district of central Myanmar. The district is arbitrarily divided into 6 zones served by a centrally located eye hospital in Meiktila. Participants were selected using a randomized, stratified, cluster sampling process. A sampling frame consisting of a list of all villages in the Meiktila district and their populations was obtained from the Ministry of Health. For logistical reasons, sampling was restricted to villages within a 3-hour drive from Meiktila (an area encompassing approximately 80% of the district).
All persons 40 years or older within each selected village were eligible for inclusion. Health care workers from Meiktila Township enumerated the selected villages (and advertised and promoted the survey) before commencement of the survey. All eligible subjects belonged to the Burman ethnic group (the majority ethnic group in Myanmar).
A single survey team conducted the entire study in November 2005. Each team member was assigned specific tasks and was well trained in the appropriate area before the commencement of the study. All equipment and personnel were transported to each village, and the data collection occurred on site. A tonometrist obtained 2 IOP readings using GAT (calibrated at each site) and recorded the average. Another observer then measured CCT (calibrated at each site) with the use of an ultrasonic pachymeter (Pocket II Precision pachymeter; Quantel Medical Inc, Bozeman, Montana) and recorded the average of 5 readings (standard practice for this instrument). As quality assurance, the IOP and CCT measurements were regularly verified by one of the attending ophthalmologists (R.J.C.). The mean (SD) intraobserver variability for the GAT was 1.13 (0.74) mm Hg (n = 40). The intraclass correlation coefficient for the GAT was 0.94 (n = 50) and for the pachymetry, 0.96 (n = 50). Subjects meeting the diagnostic criteria for glaucoma defined by the International Society of Geographic and Epidemiologic Ophthalmology (ISGEO)19 in 1 or both eyes were excluded on the grounds that the IOP in most of these subjects was elevated as a component of the disease, a factor that would mask any underlying relationship between CCT and GAT-measured IOP in this population. For consistency, subjects with glaucoma and normal IOP were also excluded. Similarly, subjects meeting the ISGEO definition of primary angle closure with an IOP of greater than 22 mm Hg were excluded. The methods used to diagnose glaucoma, which included stereoscopic examination of the optic discs and comparison with standard disc photographs, have been previously reported.20 The possible association of thinner CCTs with glaucoma was not a hypothesis in this report. Subjects with central corneal scarring were also excluded. Those with ocular hypertension (no glaucoma but an IOP of >22 mm Hg) were not excluded.
The Meiktila Eye Survey was approved by the Ministry of Health in Myanmar and had ethical approval from the Royal Adelaide Hospital Ethics Committee. Consent for participation was obtained from the head of each village before commencement of the survey; written, informed consent in the participants' own language was obtained after verbal instruction from all participants. The study was conducted in accordance with the Declaration of Helsinki.
To estimate mean CCT and IOP and to identify predictor variables associated with these outcomes, linear mixed effects models were fitted to the data. This type of analysis does not assume independence of data; the correlation between observations of the right and left eyes can be accounted for by fitting the participant as a random effect in the model. Demographic and biometric predictor variables for each model were chosen a priori on the basis of biological plausibility and prior knowledge. For CCT as the outcome, the predictor variables included age, IOP, sex, spherical equivalent, corneal curvature, and body mass index. For IOP as the outcome, they included age, CCT, and sex.
Linear mixed effects models suffer the disadvantage that, unlike a multivariate coefficient of determination value in a general linear model, there is no overall measure of the proportion of variance explained by the model. Hence, the strength of association between significant predictors and the outcome variable in the models were calculated using uniocular data. Initial exploration of the data indicated that parametric assumptions for correlation analyses between CCT and IOP may not be met; hence, a Spearman rank correlation was calculated.
We considered P < .05 to be statistically significant. Unless otherwise indicated, data are expressed as mean (SD).
A total of 2481 subjects were eligible, and 2076 were examined (836 men and 1240 women [participation rate, 83.7%]). The mean age was 56.2 (11.5) years. We excluded 101 subjects with glaucoma. An IOP measurement and a corresponding pachymetry recording from at least 1 eye were available in 1909 subjects (76.9%), of whom 756 (39.6%) were men and 1153 (60.4%) were women.
Allowing for clustering of data, the overall mean IOP was 14.5 (3.4) mm Hg, and the mean CCT was 521.9 (33.3) (range, 409-640) μm. The mean IOP in men (14.6 [3.6] mm Hg) was not significantly different from that in women (14.5 [3.8] mm Hg) (P = .68). The mean CCT in men (522.0 [32.8] μm) was not significantly different from the mean CCT in women (521.9 [33.2] μm) (P = .86). One hundred twenty-one nonglaucomatous eyes had an IOP of greater than 22 mm Hg (the 97.5th percentile), with a range of 23 to 40 mm Hg. This group of ocular hypertensive eyes had a significantly higher mean CCT of 536 (41.8) μm compared with eyes that had IOPs within the reference range (P < .001).
Figure 1 shows the scatterplot of CCT vs IOP for the right eyes (a plot for the left eyes was similar). The results yielded no convincing pattern, linear or otherwise. Although the Spearman rank correlation, which assumes neither linearity nor homoscedasticity, was low for the right (R2 = 0.016; n = 1880) and left eyes (R2 = 0.017; n = 1873), it was highly significant (P < .001), owing to the large number of eyes.
However, with IOP grouped into different ranges, a more convincing relationship emerged, with each successively higher IOP range associated with a significantly thicker CCT than the preceding range (Figure 2). In the mixed linear model analysis, which included all eyes (Table 1), the IOP was significantly (P < .001) associated with CCT. This relationship was stronger when the IOP was analyzed as a categorical rather than a continuous variable (as determined by the difference in the Akaike information criterion). The spherical equivalent was also a significant predictor of CCT (P = .009), but age, body mass index, corneal curvature, and sex were not. There was a trend toward a thinner CCT in the group aged 40 to 49 years compared with the group 70 years or older (P = .07). The Spearman rank correlation between the CCT and the spherical equivalent (the only other significant predictor) for the right eyes was only 0.089.
In the mixed linear model analysis with IOP as the outcome variable, CCT was the only significant predictor (P < .001; Table 2). There was an upward trend in IOP from ages 40 to 69 years, with a reduction in the oldest group. An increase of 100 μm in CCT predicted an increase of 1.3 mm Hg in IOP.
The mean CCT in this Burmese population was thinner than that generally found in white populations.8 This is consistent with the preponderance of evidence that indicates that there is considerable racial variation in CCT; however, the use of different measuring devices in various epidemiological studies makes comparisons difficult (Table 3).6,12,21 Cho and Lam5 reported a mean CCT of 575 (32) μm in Hong Kong Chinese, but Foster et al,4 using optical pachymetry, reported considerably thinner CCTs in a Mongolian population. In a refractive surgery clinic–based population, Shimmyo et al10 reported that the mean CCT in Asian eyes was 550 (32) μm.
Reports of a sex-specific difference in CCT have been inconsistent.6 Several studies of nonwhite populations have found a small but statistically significant sex difference, with men tending to have slightly thicker CCTs.4,5,10,18 In the present study, the difference was not statistically significant. Similarly, reports of an age-dependent effect on CCT are inconsistent, but most of the data from Asian populations4,5,12,18 and from the Barbados Eye Studies15 indicate a tendency for the CCT to decrease with age. However, in the present study, CCT was not significantly associated with age.
The relationship between CCT and IOP measured by GAT is complex.6,14 Imbert22 and Fick23 (publishing independently and shortly after Malakoff24) are jointly credited with the Imbert-Fick Law, developed specifically for applanation tonometry, which states that the weight on a fluid-filled sphere divided by the area flattened equals the pressure within the sphere. The 1957 treatise by Goldmann and Schmidt1 on applanation tonometry highlighted the fact that there were ocular factors that undermine the assumptions inherent in this “law.” Goldmann and Schmidt maintained that, when a corneal diameter of 3.0 to 3.5 mm was applanated in normal human corneas, the elastic and surface tension forces canceled each other and the resultant measurement was virtually the original undisturbed IOP. They recognized that, theoretically, CCT affected applanation tonometry, but it appears they believed it would be insignificant under physiologic conditions. The CCT in their calibration experiments was assumed to be 500 μm.
In 1975, using in vivo manometry, Ehlers et al2 found a statistically significant linear relationship between CCT (measured optically) and the error in the IOP measured by GAT (Perkins tonometer) in human eyes (and in rabbit eyes). More recently, in a series of Chinese eyes undergoing manometry and GAT, Foster et al25 found no significant relationship between CCT and IOP.
A number of studies in nonglaucomatous, ocular hypertensive, and glaucomatous populations have reported a positive relationship between IOP measured by GAT and CCT.4,5,7-9,11,18 In a meta-analysis in which the IOP had been measured using a variety of applanation techniques and the CCT using optical or ultrasonic pachymetry, Doughty and Zaman6 described a weak (R2 = 0.096) but statistically significant (P = .03) relationship between IOP and CCT. We also found a weak but positive association between IOP and CCT in this population. Although IOP was included as a predictor with CCT as the outcome variable, it is clear that the direction of causality is reversed. Analyses from several studies have reported that the difference in the GAT-measured IOP per 100-μm difference in CCT ranges from 1.1 to 3.2 mm Hg,3,9,26,27 consistent with the finding from the present study, where an increase of 1.3 mm Hg was predicted.
Although the correlation coefficient between IOP and CCT is weak, when the IOP is categorized, a relationship between IOP and CCT becomes more apparent. Almost identical findings were reported by Hahn et al9 using population-based data from the Latino Eye Study, and the Ocular Hypertension Treatment Study reported that individuals with ocular hypertension tend to have thicker corneas than those with an IOP within the reference range.11 This is consistent with the finding in the present study that the mean CCT in ocular hypertensive subjects was significantly thicker than that in the normotensive population.
Studies examining the relationship between refractive error and CCT are limited and the findings are inconsistent. In the Ocular Hypertension Treatment Study, refractive error was significantly associated with CCT in univariate but not multivariate analysis.11 However, Alsbirk28 reported a significant correlation between CCT and refraction in a population of Greenlandic Inuit (thicker CCT was associated with a more hypermetropic refraction). In a multivariate analysis from the Barbados Eye Studies, including age and IOP, a more positive refraction was significantly associated with a thicker cornea.15 In the present study, a more positive spherical equivalent was also significantly associated with a thicker cornea.
Other features of the corneal phenotype that affect applanation are likely to influence GAT-measured IOP. Hysteresis refers to the lag between the change in forces on a body and the resultant effect on that body. Recent reports have indicated that hysteresis is a clinically relevant component of corneal mechanics that can influence GAT.29-33 Kotecha et al33 have indicated that hysteresis describes an IOP-independent biomechanical property of the cornea that increases with thicker CCT and decreases with greater age. It is moderately associated with CCT and yet explains more of the interindividual variation in GAT-measured IOP than does CCT.33
Although CCT is a predictor of conversion from ocular hypertension to glaucoma,34 the underlying reason for this association remains unclear. Furthermore, this relationship may be stronger in the clinical setting rather than at the population level. In addition, nomograms that adjust the IOP on the basis of CCT recordings produce an overcorrection.35
The strengths of this study include its population-based nature and large data set. Limitations include the fact that this was a cross-sectional study with the IOP measured at a single time point only, an inability to comment on the relationship between CCT and IOP in individuals younger than 40 years, relatively small numbers of ocular hypertensive eyes, and that inferences regarding the relationship between IOP and CCT relate to this population only.
Unfortunately, we have no information about the characteristics of the nonparticipants. Owing to the limited time and resources, our enumeration recorded only the total number of people who were 40 years or older in each of the selected villages. There are no reliable census data to determine the identity and characteristics of the nonparticipants; however, given that the participation rate was greater than 80% (as was expected), the lack of data about nonparticipants is unlikely to alter the conclusions of the study.
In conclusion, the CCT in this Burmese population was thinner than that found in white populations. The CCT had a weak but significant correlation with IOP. This relationship was more apparent when the IOP was divided into subgroups and obvious when the CCT in ocular hypertensive subjects was compared with that of normotensive subjects. It seems likely that the relationship between IOP and CCT is influenced by a number of unknown variables.
Correspondence: Robert J. Casson, DPhil, FRANZCO, South Australian Institute of Ophthalmology, Department of Ophthalmology and Visual Sciences, Adelaide University, Royal Adelaide Hospital, Adelaide, South Australia, Australia 5000 (email@example.com).
Submitted for Publication: April 4, 2007; final revision received December 3, 2007; accepted December 6, 2007.
Author Contributions: Dr Casson had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Financial Disclosure: None reported.
Funding/Support: This study was supported by an unrestricted grant from Pfizer Ophthalmic.
Disclaimer: The design of the survey, its execution, analysis, interpretation, and publication were performed independently by the authors.
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