Objective
To evaluate the 4-year risk of high intraocular pressure (IOP) and associated factors in a black population without glaucoma at baseline.
Design
Population-based incidence study.
Participants
Random sample of Barbados residents aged 40 to 84 years. After 4 years, 3427 (85%) were reexamined.
Main Outcome Measures
Development of elevated IOP (using percentile-based definitions) among individuals with an IOP of 21 mm Hg or lower and no glaucoma at baseline. Associations were evaluated using polychotomous logistic regression.
Results
At baseline, 2856 participants did not have glaucoma or suspected glaucoma: 361 had an IOP higher than 21 mm Hg or received treatment, and 2495 had an IOP of 21 mm Hg or lower and no treatment. At follow-up, only 58% of the 361 participants remained free of glaucoma and had an IOP higher than 21 mmHg, whereas 30% had an IOP of 21 mm Hg or lower. Among the remaining 2495 participants, the incidence of IOP higher than 21 mm Hg or treatment (80th percentile) was 12.9% (95% confidence interval, 11.7%-14.3%). Using other definitions of elevated IOP, estimates ranged from 1.5% to 11%. Incidence increased with age, with rates 2.5 times higher at 70 years or older than at ages 40 to 49 years. Factors associated with high IOP included age, baseline IOP, hypertension, and blood pressure. Whereas participants with an IOP between 21 mm Hg and 28 mm Hg had higher blood pressure readings, those with an IOP of 21 mm Hg or lower or an IOP higher than 28 mm Hg had similar values.
Conclusions
Definitions of high IOP based on percentiles may be more applicable than those based on arbitrary values. Older individuals with a higher baseline IOP were more likely to develop elevated IOP after 4 years. Although blood pressure was also associated with high IOP, the relationship may be nonlinear.
ELEVATED INTRAOCULAR pressure (IOP) is often associated with open-angle glaucoma (OAG) and was formerly included among the criteria for defining OAG.1 Although individuals with high IOP are at increased risk for OAG, most will never develop the disease.1,2 In addition, a growing body of evidence indicates that the risk factors for high IOP are not necessarily the same as for OAG, 3,4 further suggesting that these conditions have separate etiologic mechanisms.
Factors reported to be associated with elevated IOP include older age, 3,5-13 sex, 3,6,7,10,12,14,15 African ancestry, 3,11 blood pressure (BP), 1,3,5,7,10,11,13-17 pulse rate, 3 diabetes, 1,3,11,13,18-22 obesity, 3,8,10,14,23,24 use of alcohol, 3,4,17 smoking, 3 seasonality, 3 myopia, 4 iris color, 4 nuclear sclerosis, 4 and a family history of glaucoma.3,4,6,10 These factors have been identified primarily through cross-sectional studies, with few analyses based on longitudinal data. To our knowledge, there have been no reports on the incidence of high IOP and its risk factors among populations of African descent.
An important issue concerns the definition of high IOP; the traditional cutoff of higher than 21 mmHg1 used in many studies may not be suitable for all populations. This study used percentile-based cutoff values to evaluate the 4-year incidence and respective risk factors for elevated IOP (in the absence of glaucoma) in a predominantly black population.
The Barbados Eye Study25 (BES) (1988-1992) was a population-based study aimed at determining the prevalence and risk factors for the major causes of visual loss in the predominantly Afro-Caribbean population of Barbados. As presented in detail previously, the cohort was identified through a simple random sample of the country's adult population, which included people aged 40 to 84 years. Four years later, survivors were reexamined in the Barbados Incidence Study of Eye Diseases (BISED) (1992-1997), 26 and 3427 (85%) of those eligible participated: 3193 were of African descent, 139 were of mixed descent (black and white), and 95 were white or of another self-reported racial background. Our results are based on black participants only, given the small number of subjects in other racial or ethnic groups. The studies were funded by the National Eye Institute(Bethesda, Md) and included a Coordinating Center (School of Medicine at Stony Brook, Stony Brook, NY), Data Collection Center (Bridgetown, Barbados), and Fundus Photography Reading Center (The Johns Hopkins University, Baltimore, Md).
The protocols for both the BES and BISED have been described in detail elsewhere.25,26 To summarize, the examinations included anthropometric and BP measurements, best-corrected visual acuity measurements with a Ferris-Bailey chart, 27 Humphrey automated perimetry (Allergan-Humphrey, San Leandro, Calif), lens gradings(Lens Opacities Classification System II), 28 venipuncture for glycated hemoglobin, bilateral color stereo fundus photography of the optic disc and macula, and an extensive interview including demographic information and medical, ocular, and family histories as well as other risk factor data. A Goldmann applanation tonometer was used to record the IOP, and the IOP data presented are based on the average of 3 measurements (highest value in either eye). Individuals with an IOP higher than 21 mmHg, abnormal perimetry results, a history of ocular abnormalities, incomplete lens gradings and/or photographic data, and a systematic 10% sample (regardless of ocular abnormalities) were referred for a comprehensive ophthalmologic evaluation.25,26 All participants provided informed consent for the examinations.
Definite OAG was defined by the presence of both visual field and optic disc pathologic characteristics after the exclusion of other possible causes.25,26 The IOP measurements were not considered in the definition of glaucoma. Individuals categorized as glaucoma suspects(GS) met some but not all of the criteria for OAG. The population at risk for developing elevated IOP included individuals without any type of glaucoma(OAG, GS, or other glaucoma), with an IOP of 21 mm Hg or lower OU, and who had received no IOP-lowering treatment at baseline. The 4-year incidence rate of high IOP was defined as the number of participants meeting various percentile-based IOP criteria (in at least 1 eye) at their BISED visit divided by the population at risk. In addition to the traditional cutoff value of 21 mm Hg (approximately the 80th percentile), elevated IOP was determined using the 95th, 90th, and 85th percentiles of the distribution of baseline IOP measurements among black participants. Personal, medical, and other characteristics were evaluated to determine possible associations with high IOP.
Personal characteristics included age, sex, religion, complexion pigmentation(ordinal scale from 1, very light, to 4, very dark), years of education, lifetime occupation, body mass index, and waist-hip ratio.
Medical factors included systolic and diastolic blood pressures (average of 2 measurements using a Hawksley random zero sphygmomanometer29), hypertension (average systolic blood pressure [SBP] of 140 mm Hg or higher and/or diastolic blood pressure [DBP] of 90 mm Hg or higher and/or antihypertensive treatment), history of cardiovascular symptoms (heart attack, stroke, a major decrease in BP, or another heart condition), migraine history, glycated hemoglobin level, history of diabetes and treatment, smoking and alcohol use, regular use of nutritional supplements, corticosteroids, and aspirin.
Other variables investigated were family history of glaucoma, sunlight exposure, use of hats or sunglasses, and seasonal and diurnal effects on IOP.
Polychotomous logistic regression models were used to identify factors potentially associated with various levels of elevated IOP (representing the 80th to 95th percentiles). Participants with an IOP of 21 mm Hg or lower OU at follow-up served as the reference group for such comparisons. Factors found to be significant (P<.05) in at least 1 group in the initial univariate analysis were included in the subsequent multivariate models. Relative risks (RRs) and 95% confidence intervals (CIs) are presented based on the final polychotomous logistic regression model that included significant variables (P<.05) in any study group.
Of the 3193 black participants who attended the follow-up visit, 2856 were free of glaucoma or suspected glaucoma in either eye at baseline. Of these, 361 (12.6%) had an IOP higher than 21 mm Hg in at least 1 eye or were receiving IOP-lowering treatment; the remaining 2495 (87.4%) had lower IOP values in the absence of treatment. Incidence rates are based on these 2495 individuals. Among participants without glaucoma who had an IOP higher than 21 mm Hg or treatment at baseline, only 58% retained their original classification. Approximately 12% had glaucoma-related diagnoses at follow-up: 5% met the criteria for OAG, and 7% were classified as GS. However, 30% now had an IOP of 21 mm Hg or lower and were not receiving treatment.
Table 1 lists similar data for the 2495 black participants without glaucoma or treatment and for those with an IOP of 21 mm Hg or lower at baseline, stratifying by IOP and treatment status at follow-up. Overall, approximately 84% retained the same classification 4 years later. About 3% had new glaucoma diagnoses: 18 participants (0.7%) were found to have OAG (most with an IOP>21 mmHg), and 57 (2.3%) were diagnosed as GS (approximately half with an IOP>21 mmHg). Of the remaining individuals without glaucoma, 12.9% had an IOP higher than 21 mm Hg and received treatment. Including participants with a diagnosis of glaucoma at follow-up, a total of 14.8% (369/2495) had an IOP higher than 21 mm Hg or were receiving IOP-lowering treatment 4 years later.
The distribution of IOP among black participants at baseline was as follows: mean ± SD, 18.7 ± 5.1 mmHg; median, 18 mmHg. The 95th percentile corresponded to an approximate mean IOP of 28 mmHg, the 90th percentile to an IOP of 24 mmHg, the 85th percentile to an IOP of 22 mmHg, and the 80th percentile to an IOP of 21 mmHg. Table 2 indicates the 4-year risk of developing various percentile-based definitions of high IOP (after rounding the cutoff measurements) among the reference population; that is, the 2495 participants with an IOP of 21 mm Hg or lower who were not receiving IOP-lowering treatment at baseline. After 4 years, 38 (1.5%) were found to have an IOP higher than 28 mm Hg (not attributable to glaucoma), a percentage that rises slightly after including the 7 individuals without glaucoma who received IOP-lowering treatment. A total of 144 (5.8%) reached an IOP level higher than 24 mm Hg at follow-up or were receiving treatment, yielding half of the rate for the often-used criterion of an IOP higher than 21 mmHg. The estimates based on high IOP alone vs high IOP or treatment were similar for all cutoff levels because of the low number of BISED participants receiving IOP-lowering treatment.
Table 3 provides the age- and sex-specific rates of elevated IOP using cutoffs of 21 mm Hg and 28 mm Hg (approximately 80th and 95th percentiles, respectively). For IOP higher than 21 mmHg, no differences were seen in the overall incidence rates by sex (13.3% vs 12.7%), although the age-specific rates tended to be slightly higher among men than women with the exception of the youngest age group. The incidence estimates also increased steadily with age. The rates almost doubled from ages 40 to 49 years and 50 to 59 years (7.4% vs 14.0%) and were 2.5 times higher among participants 70 years and older (18.7%). When IOP lower than 28 mm Hg was used as a cutoff, the overall rates were 2.3% and 1.5% for men and women, respectively, with an overall rate of 1.8%; rates were higher among men in all age groups. Among participants with an IOP lower than 28mmHg, the rates tripled from ages 40 to 49 years and 50 to 59 years (0.7% vs 2.3%) and were approximately 6 times higher among those 70 years and older(4.1%). Although a decrease was noted (in both men and women) for participants aged 60 to 69 years compared with those aged 50 to 59 years, this rate was based on small numbers.
Table 4 lists factors found to be significant (P<.05) in a univariate polychotomous analysis stratified by 5 levels of elevated IOP. Age, baseline IOP, BP, BP treatment, pulse rate, diabetes history, level of education, and the use of a hat and/or umbrella were found to be significant. Significant differences(P<.05) between individual (elevated) IOP strata and the reference group (IOP≤21 mmHg) are indicated in Table 4. Participants with an elevated IOP were 3 to 6 years older(based on mean values) than those with an IOP of 21 mm Hg or lower (reference group). Likewise, the mean baseline IOP wasapproximately1.5 mm Hg higher in the groups with an elevated IOP compared with the reference group. Interestingly, the mean SBP and DBP measurements as well as hypertension and the presence of a diabetes history produced an inverted U pattern as the IOP increased. The SBP and DBP blood pressure measurements were higher for participants with an intermediate IOP (21 mmHg<IOP≤28 mmHg) than among those with an IOP of 21 mm Hg or higher than 28 mmHg. Approximately one quarter to one third of all participants self-reported their treatment for high BP, with less reported treatment in the groups with an IOP of 21mmHg or lower (26.3%) or an IOP higher than 28 mm Hg (26.3%) than in the others (range, 33.3%-36.6%). The use of a hat or umbrella was significantly higher among participants with an IOP higher than 28 mm Hg or an IOP higher than 21 mm Hg but lower than or equal to 22 mm Hg compared with the reference group (IOP≤21 mmHg). This outcome may be attributable to sample size considerations because the result was based on few individuals. Additionally, in the BES population, older women were more likely to wear hats or carry umbrellas (P<.001). Therefore, the finding may also be related to an age-sex effect, a hypothesis supported by the nonsignificant associations in the following multivariate analysis.
Table 5 gives the results of the multivariate polychotomous model, with RRs and 95% CIs provided for each IOP stratum and significant factor (P<.05). Age, baseline IOP, and SBP and DBP measurements were maintained in the final models, with age and baseline IOP yielding significant differences from the reference group for all levels of IOP higher than 21 mmHg. Hypertension also yielded a significant result (RR = 1.87; 95% CI, 1.25-2.79) when comparing the group with an IOP higher than 22 mm Hg but less than or equal to 24 mm Hg with the reference group. The group with an IOP higher than 21 mm Hg but less than or equal to 28 mm Hg tended to have an increased number of participants with hypertension compared with the reference group, whereas that with an IOP higher than 28 mm Hg did not. Comparable findings were noted for SBP and DBP. There were no significant differences in SBP or DBP between participants with an IOP higher than 28 mm Hg and the reference group, a comparison based on small numbers. There is little variability in the RRs, regardless of the IOP cutoff levels, for all factors provided in Table 5 except hypertension.
To our knowledge, this is the first report that has investigated the 4-year incidence and related risk factors associated with elevated IOP in a black population according to various definitions. The results contribute to our knowledge of the natural history of individuals with and without an IOP higher than 21 mmHg. They highlight the issues involved in defining high IOP and provide incidence estimates according to percentile-based cutoffs(Table 2). Our findings support the roles of age (Table 3), baseline IOP, and BP as factors influencing the 4-year risk of developing high IOP(Table 4 and Table 5). Of these factors, age and baseline IOP were significant(P<.05) regardless of IOP strata, whereas the BP variables were not significant among participants with an IOP higher than 28 mm Hg at follow-up (Table 4). A discussion of these findings follows.
In individuals without glaucoma, ocular hypertension is often defined by a standard cutoff of IOP higher than 21 mmHg. Using this cutoff, only 58% of participants retained the same classification after 4 years, indicating that this IOP threshold had a low specificity for defining high IOP in this study. This finding is partly explained by the fact that approximately 12% of the group progressed to GS or OAG in contrast to about 3% in the group with a lower IOP (Table 1), confirming the increased glaucoma risk (about 1% per year). To a larger extent, it was due to a lowering of the original IOP; 30% of participants were subsequently found to have an IOP of 21 mm Hg or lower without treatment, a finding at least partly explained by regression to the mean. Therefore, although this classification identified a group at increased risk for glaucoma, almost one third of these individuals did not maintain these IOP levels after 4 years of follow-up.
The applicability of the cutoff of 21 mm Hg to define ocular hypertension is particularly questionable for our cohort because this value approximated the 80th percentile of the baseline IOP measurements, and the 4-year incidence of those with an IOP higher than 21 mm Hg or receiving treatment was rather high (Table 2). Perhaps a more appropriate definition would be based on participants with an IOP in the 95th percentile of the distribution, leading to a lower incidence rate. Other levels such as the 90th or 85th percentiles may also be appropriate for the purposes of defining high IOP in this population and others. The rationale is similar to that suggested by Wolfs et al30 for defining OAG; that is, using the upper percentiles for changes in visual field and optic disc pathologic characteristics because such criteria establish a quantitative basis for defining disease.
Using IOP cutoffs of 21 mmHg, 22 mmHg, 24 mmHg, and 28 mm Hg (representing approximately the 80th, 85th, 90th, and 95th percentiles, respectively), the final multivariate models identified age, baseline IOP, hypertension, and BP variables as being associated with IOP at follow-up (Table 5). These results are consistent with a longitudinal analysis of changes in IOP in the BES cohort during a 4-year period.11 Although diabetes history was a significant predictor of IOP changes in that study and was also significant in our univariate analysis (Table 4), it was not maintained in the final model. The difference is most likely related to the use of absolute cutoffs in the analyses in this study vs factors linked to IOP change in the previous analyses. Although OAG was more common in men than women in the BES25 and the incidence of high IOP tended to be higher among men (Table 3), sex was not found to be a significant factor in the regression analyses (Table 4 and Table 5). The association between baseline IOP and subsequent incidence of high IOP is an expected finding.
Most studies report a positive relationship between increasing age and elevated IOP.3,5,7,11,13,31,32 However, some studies have found a negative association4,8,10,15,23 or no association at all between age and IOP.33 It has been hypothesized that these inconsistent findings may be attributable to population differences or other factors relating to the accuracy of the tonometry measurements. Foster et al34 point out that applanation tonometry may underestimate IOP in Asian populations, possibly resulting in a compromised ability to detect elevations in IOP with age. Racial differences in IOP4,6-10,12,15,29,35 as well as measurement differences in IOP relating to central corneal thickness36 may also play a role in explaining the discrepant findings. This study supports the findings from the population-based BES3,11 and others in which a positive association between increasing age and IOP was reported. Physiological factors such as a reduced production of aqueous humor in elderly individuals and the onset of structural changes in the trabecular meshwork have been proposed to explain the positive relationship with IOP in older age groups.37,38 These may not be the only explanations, however. Although mean IOP increased with age in the Health and Nutrition Examination Survey, 7 SBP was the variable most highly correlated with IOP, followed by age. Additionally, increases in IOP among older individuals were attributed to a concomitant elevation in systemic BP in a Swedish population, 16 thus raising questions about the mechanisms by which age and BP contribute to a rise in IOP.
Although several studies have reported an association between BP and elevated IOP, the true relationship is still not well understood. The Framingham Eye Study, 39 Health and Nutrition Examination Survey, 7 and others14 reported that SBP represented the greatest contribution (among all variables included in the models) to IOP in multiple regression analyses. Numerous other studies have corroborated the association between IOP and SBP.3,5,10,11,16,32,33 Fewer studies have reported an association between DBP and IOP.1,10,11,14,17 Although most of these reports were based on cross-sectional or case-control studies, longitudinal increases in systemic BP have been documented.11,31,33
Findings from this study indicate that both SBP and DBP are associated with elevated IOP. This analysis differs from others by investigating these BP variables at various levels of IOP. We found that although SBP and DBP are generally higher among individuals with elevated IOP (as opposed to those with an IOP≤21 mmHg), the group representing the highest percentile (IOP>28mmHg) had hypertension and BP values similar to the reference group (IOP≤21mmHg). Thus, whereas 64% to 69% of participants with an IOP between 21 mm Hg and 28 mm Hg were found to have hypertension, the frequency of hypertension was lower and comparable in those with an IOP higher than 28 mm Hg and in the reference group (45% and 47%, respectively). A similar inverted U–shaped distribution for SBP and DBP, respectively, was noted among the groups with increasing IOP. This finding may be the result of a sample size issue because the group with an IOP higher than 28 mm Hg included only 38 individuals. However, the decrease in BP at the highest level of IOP may also represent a true finding. It is unclear, however, why hypertension would be less frequent and BP lower among individuals with the highest IOP measurements at follow-up. This finding could possibly be the result of a survivor effect; that is, these individuals probably are older, have less diabetes and hypertension than expected, and are healthier than their similarly aged peers who have died. Nevertheless, this finding requires further investigation in other populations.
Hypertension, high SBP, and high DBP were not positively associated with OAG in the BES or its 4-year follow-up.40,41 Therefore, although there is a known relationship between OAG and IOP and there is evidence of an association between BP/hypertension and elevated IOP, the interrelationship requires further elucidation. It has been proposed that an increase in BP may induce an increase in aqueous humor production, thus explaining the relationship between BP and IOP.14,42 Another explanation is that elevated IOP may be thought of as a physical equilibrium state in response to high BP, a relationship that does not exist in glaucoma, and may involve a compromised vascular autoregulation mechanism.8,39 The involvement of perfusion pressure (BP minus IOP) has also been proposed to explain some of these findings; high BP may protect against glaucoma by causing adequate perfusion pressure.17 Longitudinal analyses of the BES cohort suggest a decreased OAG risk with hypertension as well as a strong relationship between low perfusion pressure and OAG risk.42 Although these results are consistent with the role of vascular factors, the interaction between BP, IOP, and OAG remains unclear and requires additional investigation.
This longitudinal study provides information on IOP during a 4-year period and documents the challenges of defining high IOP. Definitions based on percentile values may be used more frequently in future studies; a cutoff of 21 mm Hg (80th percentile in this population) may not be the most appropriate threshold for all populations. Regardless of the definition, age, baseline IOP, and BP variables were the main factors associated with the risk of developing elevated IOP during a 4-year period. The nonlinear relationship found between BP and IOP requires further investigation. Additional studies are needed to help elucidate the complex interrelationship between SBP, DBP, and IOP because the true mechanism for the development of high IOP with respect to BP remains unclear.
Corresponding author and reprints: M. Cristina Leske, MD, MPH, Department of Preventive Medicine, Stony Brook University, HSC L3 086, Stony Brook, NY 11794-8036 (e-mail: cleske@notes.cc.sunysb.edu).
Submitted for publication February 6, 2002; final revision received August 30, 2002; accepted September 26, 2002.
This study was supported by grants EY07625 and EY07617 from the National Eye Institute, Bethesda, Md.
We thank the Barbados Eye Studies participants and the Ministry of Health, Bridgetown, Barbados, for their role in the study.
The Barbados Eye Studies Group
Principal Investigator
M. Cristina Leske, MD, MPH
Coordinating Center
Stony Brook University, Stony Brook, NY: M. Cristina Leske, MD, MPH; Barbara Nemesure, PhD; Suh-Yuh Wu, MA; Leslie Hyman, PhD; Xiaowei Li, PhD; Shu-Hong Xie, MS; Lixin Jiang, MS; Kasthuri Sarma; Melinda Santoro; Koumudi Manthani.
Data Collection Center
Ministry of Health, Bridgetown, Barbados: Anthea M. S. Connell, FRCS, FRCOphth; Anselm Hennis, MRCP(UK), PhD; Ann Bannister, MB, BS, DO; Muthu A. Thangaraj, MB, BS, DO; Coreen Barrow; Patricia Basdeo; Kim Bayley; Anthanette Holder.
Fundus Photography Reading Center
The Johns Hopkins University, Baltimore, Md: Andrew P. Schachat, MD; Judith A. Alexander; Noreen B. Javornik, MS; Cheryl J. Hiner; Deborah A. Phillips; Reva Ward; Terry W. George.
Local Advisory Committee
School of Clinical Medicine and Research, University of the West Indies, Barbados: Trevor Hassell, MBBS, FRCP, FACC, GCM(Department of Cardiology); Henry Fraser, FACP, FRCP(UK), PhD, GCM (Chronic Diseases Research Centre). Department of Ophthalmology, Queen Elizabeth Hospital, Barbados: Clive Gibbons, FRCS(Ed), FRCP, FRCOphth(UK).
1.Leske
MC The epidemiology of open-angle glaucoma: a review.
Am J Epidemiol. 1983;118166- 191
Google Scholar 2.Sommer
A Intraocular pressure and glaucoma.
Am J Ophthalmol. 1989;107186- 188
Google Scholar 3.Wu
SYLeske
MCand the Barbados Eye Study Group, Associations with intraocular pressure in the Barbados Eye Study.
Arch Ophthalmol. 1997;1151572- 1576
Google ScholarCrossref 4.Weih
LMMukesh
BNMcCarty
CATaylor
HR Association of demographic, familial, medical, and ocular factors with intraocular pressure.
Arch Ophthalmol. 2001;119875- 880
Google ScholarCrossref 5.Carel
RSKorczyn
ADRock
MGoya
I Association between ocular pressure and certain health parameters.
Ophthalmology. 1984;91311- 314
Google ScholarCrossref 6.Leske
MCConnell
AMSWu
S-Y
et al. Distribution of intraocular pressure.
Arch Ophthalmol. 1997;1151051- 1057
Google ScholarCrossref 7.Klein
BEKKlein
R Intraocular pressure and cardiovascular risk factors.
Arch Ophthalmol. 1981;99837- 839
Google ScholarCrossref 8.Shiose
YKawase
Y A new approach to stratified normal intraocular pressure in a general population.
Am J Ophthalmol. 1986;101714- 721
Google Scholar 9.Mason
RPKososo
OWilson
MR
et al. National survey of the prevalence and risk factors of glaucoma in St Lucia, West Indies.
Ophthalmology. 1989;961363- 1368
Google ScholarCrossref 10.Klein
BEKKlein
RLinton
KLP Intraocular pressure in an American community: the Beaver Dam Eye Study.
Invest Ophthalmol Vis Sci. 1992;332224- 2228
Google Scholar 11.Hennis
AWu
SYNemesure
BLeske
MC Hypertension, diabetes and longitudinal changes in intraocular pressure.
Ophthalmology. 2003;110908- 914
Google ScholarCrossref 12.Bonomi
LMarchini
GMarraffa
M
et al. Prevalence of glaucoma and intraocular pressure distribution in a defined population.
Ophthalmology. 1998;105209- 215
Google ScholarCrossref 13.Bonomi
LMarchini
GMarraffa
M
et al. Vascular risk factors for primary open angle glaucoma: the Egna-Neumarkt Study.
Ophthalmology. 2000;1071287- 1293
Google ScholarCrossref 14.Bulpitt
CJHodes
CEveritt
MG Intraocular pressure and systemic blood pressure in the elderly.
Br J Ophthalmol. 1975;59717- 720
Google ScholarCrossref 15.Dielemans
IVingerling
JRAlgra
D
et al. Primary open-angle glaucoma, intraocular pressure, and systemic blood pressure in the general elderly population.
Ophthalmology. 1995;10254- 60
Google ScholarCrossref 16.Bengtsson
B Some factors affecting the distribution of intraocular pressure in a population.
Acta Ophthalmol (Copenh). 1972;5033- 46
Google ScholarCrossref 17.Leske
MCWarheit-Roberts
LWu
S-Y Open-angle glaucoma and ocular hypertension: the Long Island Glaucoma Case-Control Study.
Ophthalmic Epidemiol. 1996;385- 96
Google ScholarCrossref 19.Klein
BEKKlein
RJensen
SC Open-angle glaucoma and older-onset diabetes: the Beaver Dam Eye Study.
Ophthalmology. 1994;1011173- 1177
Google ScholarCrossref 20.Tielsch
JMKatz
JQuigley
HA
et al. Diabetes, intraocular pressure and primary open-angle glaucoma in the Baltimore Eye Survey.
Ophthalmology. 1995;10248- 53
Google ScholarCrossref 21.Dielemans
Ide Jong
PTStolk
R
et al. Primary open-angle glaucoma, intraocular pressure, and diabetes mellitus in the general elderly population.
Ophthalmology. 1996;1031271- 1275
Google ScholarCrossref 22.Mitchell
PSmith
WChey
THealey
PR Open-angle glaucoma and diabetes: the Blue Mountains Eye Study, Australia.
Ophthalmology. 1997;104712- 718
Google ScholarCrossref 24.Mori
KAndo
FNimura
H
et al. Relationship between intraocular pressure and obesity in Japan.
Int J Epidemiol. 2000;29661- 666
Google ScholarCrossref 25.Leske
MCConnell
AMSSchachat
AP
et al. The Barbados Eye Study: prevalence of open-angle glaucoma.
Arch Ophthalmol. 1994;112821- 829
Google ScholarCrossref 26.Leske
MCConnell
AMSWu
S-Y
et al. Incidence of open-angle glaucoma.
Arch Ophthalmol. 2001;11989- 95
Google Scholar 27.Ferris
FL
IIIKassoff
ABresnick
GHBailey
I New visual acuity charts for clinical research.
Am J Ophthalmol. 1982;9491- 96
Google Scholar 28.Chylack
LT
JrLeske
MCMcCarthy
D
et al. Lens Opacities Classification System II (LOCS II).
Arch Ophthalmol. 1989;107991- 997
Google ScholarCrossref 29.Hypertension Detection and Follow-up Program Cooperative Group, Race, education, and prevalence of hypertension.
Am J Epidemiol. 1977;106351- 361
Google Scholar 30.Wolfs
RCBorger
PHRamrattan
RS
et al. Changing views on open-angle glaucoma: definition and prevalences: the Rotterdam Study.
Invest Ophthalmol Vis Sci. 2000;413309- 3321
Google Scholar 31.Nomura
HShimokata
HAndo
F
et al. Age-related changes in intraocular pressure in a large Japanese population.
Ophthalmology. 1999;1062016- 2022
Google ScholarCrossref 32.Hiller
RSperduto
RDKrueger
DE Race, iris pigmentation and intraocular pressure.
Am J Epidemiol. 1982;115674- 683
Google Scholar 33.McLeod
SDWest
SKQuigley
HAFozard
JL A longitudinal study of the relationship between intraocular and blood pressures.
Invest Ophthalmol Vis Sci. 1990;312361- 2366
Google Scholar 34.Foster
PJWong
J-SWong
E
et al. Accuracy of clinical estimates of intraocular pressure in Chinese eyes.
Ophthalmology. 2000;1071816- 1821
Google ScholarCrossref 35.Sommer
ATielsch
JMKatz
J
et al. Relationship between intraocular pressure and primary open angle glaucoma among white and black Americans: the Baltimore Eye Survey.
Arch Ophthalmol. 1991;1091090- 1095
Google ScholarCrossref 36.Foster
PJBaasanhu
JAlsbirk
PH
et al. Central corneal thickness and intraocular pressure in a Mongolian population.
Ophthalmology. 1998;105969- 973
Google ScholarCrossref 37.Brubaker
RFNagataki
STownsend
DJBurns
RRHiggins
RGWentworth
W The effect of age on aqueous humor formation in man.
Ophthalmology. 1981;88283- 288
Google ScholarCrossref 38.Miyazaki
MSegawa
KUrakawa
Y Age-related changes in the trabecular meshwork in the normal human eye.
Jpn J Ophthalmol. 1987;31558- 569
Google Scholar 39.Leske
MCPodgor
MJ Intraocular pressure, cardiovascular risk variables, and visual field defects.
Am J Epidemiol. 1983;118280- 287
Google Scholar 40.Leske
MCConnell
AMSWu
SY
et al. Risk factors for open-angle glaucoma.
Arch Ophthalmol. 1995;113918- 924
Google ScholarCrossref 41.Leske
MCWu
SYNemesure
BHennis
A Incident open-angle glaucoma and blood pressure.
Arch Ophthalmol. 2002;120954- 959
Google ScholarCrossref