September 2003
Volume 44, Issue 9
Free
Clinical and Epidemiologic Research  |   September 2003
Risk Factors Associated with the Incidence of Open-Angle Glaucoma: The Visual Impairment Project
Author Affiliations
  • Anhchuong Le
    From the Centre for Eye Research Australia, University of Melbourne, Victoria, Australia; the
  • Bickol N. Mukesh
    From the Centre for Eye Research Australia, University of Melbourne, Victoria, Australia; the
    Peter MacCallum Cancer Institute, East Melbourne, Victoria, Australia; and the
  • Catherine A. McCarty
    From the Centre for Eye Research Australia, University of Melbourne, Victoria, Australia; the
    Marshfield Medical Research Foundation, Marshfield, Wisconsin.
  • Hugh R. Taylor
    From the Centre for Eye Research Australia, University of Melbourne, Victoria, Australia; the
Investigative Ophthalmology & Visual Science September 2003, Vol.44, 3783-3789. doi:10.1167/iovs.03-0077
  • Views
  • PDF
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Anhchuong Le, Bickol N. Mukesh, Catherine A. McCarty, Hugh R. Taylor; Risk Factors Associated with the Incidence of Open-Angle Glaucoma: The Visual Impairment Project. Invest. Ophthalmol. Vis. Sci. 2003;44(9):3783-3789. doi: 10.1167/iovs.03-0077.

      Download citation file:


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

      ×
  • Supplements
Abstract

purpose. To assess the relationship between potential risk factors and the development of open-angle glaucoma (OAG) in Australian residents aged 40 and or more years.

methods. A total of 3271 participants were recruited at baseline from nine urban areas through cluster random sampling and subjected to comprehensive standardized interviews and ophthalmic examination, both at baseline and at 5-year follow-up. The participation rate at follow-up was 85% of the surviving baseline cohort. OAG was diagnosed with definite, probable, or possible certainty by a consensus panel of six ophthalmologists. Potential risk factors identified at baseline included various sociodemographic, anthropometric, dietary, familial, medical, and ocular characteristics of the participants. Risk factor analyses were performed for development of at least possible OAG (possible, probable, and definite OAG) and then at least probable OAG (probable and definite OAG) to represent a higher level of certainty. Univariate and multivariate analyses were performed.

results. Increased age and increased intraocular pressure (IOP) were associated with increased risk of development of OAG, according to multivariate analyses. A family history of glaucoma (relative risk [RR] = 2.1, 95% confidence interval [CI] = 1.03–4.2), the presence of age-related macular degeneration (RR = 2.2, 95% CI = 1.2–3.9), the presence of pseudoexfoliation (RR = 9.4, 95% CI = 2.6–34.4), and a cup-disc ratio (CDR) greater than 0.7 (RR = 7.9, 95% CI = 4.4–14.1) were associated with greater risk of development of at least possible OAG. Having ever taken α-blockers (RR = 4.8, 95% CI = 1.2–18.8), the presence of pseudoexfoliation (RR = 11.2, 95% CI = 2.0–63.3), and a CDR higher than 0.7 (RR = 11.0, 95% CI = 4.6–26.8) also indicated significant risk of development of at least probable OAG.

conclusions. Certain nonmodifiable risk factors may be used to identify high-risk individuals, and increased IOP remains an important modifiable risk factor for OAG. However, more prospective studies on risk factors are required to clarify further the etiological picture of OAG.

Glaucoma is one of the leading causes of blindness worldwide 1 2 and open-angle glaucoma (OAG) is the most common form of glaucoma in the Western world. 2 OAG is a neurodegenerative condition that is multifactorial in origin. 3 4 Increased intraocular pressure (IOP) remains an important primary and prognostic risk factor for OAG, 4 5 6 7 but other IOP-independent risk factors may be involved in the pathogenesis and progression of OAG. 4 8 9  
Consideration of other IOP-independent risk factors have led to speculation that optic nerve fiber sensitivity to damage and its tolerance to presenting IOP, even in a normal range, may be the major concept in the pathogenesis of OAG. 9 10 A clear understanding of risk factors would also promote greater public and medical awareness for prevention and early recognition of this insidious disease. In addition, the decision to treat and the complete management of OAG require consideration of all potential risk factors, which may provide the possibility of halting progression of glaucomatous field damage, despite IOP normalization. 3 11 Indeed, any elimination of modifiable risk factors could be viewed as part of the neuroprotective strategy with which to tackle this neurodegenerative disease. 3  
However, there is still inconclusive evidence regarding many proposed risk factors, and, for the most part, assessment of risk factors has been based on retrospective or cross-sectional studies. 12 13 The purpose of this study was to add significantly to the current body of evidence by providing a collective report on associations of various potential risk factors with the development of OAG, in the context of a well-designed, population-based prospective follow-up study. 
Methods
The detailed methods used in the Visual Impairment Project (VIP) have been published previously. 14 The VIP baseline examination was conducted from 1992 to 1994. Residents aged 40 or more years who had resided in the district address for at least 6 months were recruited by door-to-door survey from nine randomly selected adjacent pairs of census collection districts within metropolitan Melbourne. The 3271 residents who participated were representative of the Victorian and Australian population. 15 All attended the standardized eye examination and interview at locally established test centers. Information regarding sociodemographic, anthropometric, dietary, familial, medical, and ocular characteristics, including sunlight exposure was obtained. Interpreters were used for non–English-speaking participants, and home visits were conducted when participants were unable to attend the local examination center. 
A standardized 5-year follow-up examination and an interview were conducted from 1997 to 1999. All available participants from the baseline study were invited to take part. To promote participation, every effort was made to ensure the same examination site or the one closest to that used in the baseline study. Nonparticipants in the follow-up study were those who moved overseas or interstate, those who refused to participate, and those who died before the commencement of the 5-year follow-up. Those who died were confirmed through the National Death Index at the Australian Institute of Health and Welfare in Canberra. The study protocol was approved by the Human Research and Ethics Committee of the Royal Victorian Eye and Ear Hospital and adheres to the Declaration of Helsinki for research involving human subjects. 
Similar standardized ophthalmic examinations were conducted at baseline and follow-up. Presenting and best corrected visual acuities were measured with a 4-m logarithm of the minimum angle of resolution (logMAR) chart. Visual field assessment was performed with a visual field perimeter (Humphrey Field Analyzer, using the 24-2 Fastpac statistical program; Zeiss Humphrey Systems, Dublin, CA). If participants were unable to perform the threshold visual field test, a Bjerrum tangent screen visual field was attempted, with confrontational visual field being the final option. IOP was measured after 1 drop of oxybuprocaine hydrochloride (0.4%) was instilled in each eye. Initial measurement was performed with an electronic handheld tonometer (Oculab tonopen; Mentor O&O, Inc., Norwell, MA), and repeated measurements were taken if results were greater than 21 mm Hg or unreliable. Persistent measurements of greater than 21 mm Hg were confirmed with the Goldmann applanation tonometer, and this measurement was considered final. 
A standardized slit lamp biomicroscopic examination was performed by experienced ophthalmic research fellows. The participant’s anterior chamber depth was examined before instillation of dilation drops—that is, 1 drop of tropicamide (0.5%) followed in 5 minutes by 1 drop of phenylephrine hydrochloride (10%). A 90-D convex lens was used for general fundus examination, and the vertical cup-disc ratio (CDR) was measured. Indirect ophthalmoscopy was conducted with a 28-D lens on eyes with suspected peripheral retinal abnormalities. Paired color fundal photographs were taken with a retinal camera (TRC FET; Topcon, Paramus, NJ) and subsequently assessed through stereo viewers. Other structures of the eye were also examined and recorded systematically as part of the complete ophthalmic examination. 
Glaucoma was assessed by a consensus panel of six ophthalmologists, two of whom were glaucoma specialists. 16 Participants who had IOP greater than 21 mm Hg, possible glaucomatous visual field defect (nasal step >5 dB in three adjacent points or >10 dB in two adjacent points, any bundle-type defect, or any enlarged blind spot), or CDR higher than 0.7 or who reported a history of glaucoma were considered to have suspected glaucoma and their examination records and stereo photographs were submitted to the panel for evaluation. Suspected glaucoma was classified as OAG, angle-closure glaucoma (ACG), secondary glaucoma, ocular hypertension (OH), or no glaucoma. 16 OAG was diagnosed on an ascending scale of possible, probable, or definite certainty, based on the clinical judgment of each of the ophthalmologists, and no fixed criteria were used. Stereo disc photographs of participants were examined in a masked fashion as normal, possible, probable, or definite glaucoma, or abnormal due to other causes. Visual fields were then classified into one of five categories. Finally case notes of the participants, which included the participant’s full medical history and IOP measurements were provided to the examiners, and an overall classification of the participant was made. Each examiner made this assessment independently for each selected participant. For those participants in whom the classification by any observer varied by more than two steps, adjudication by the six examiners was conducted until consensus was reached. The same process was used for baseline and follow-up assessment. The rate of agreement using this method has been outlined. 16  
Risk factor analysis was performed for the development of at least possible OAG (possible, probable, and definite OAG) and at least probable OAG (probable and definite OAG) separately. These represent OAG diagnoses based on two different levels of certainty, which reflects levels of strictness in diagnosing OAG. Analysis of definite OAG alone was not performed because of the limited number of participants who experienced development of the disease. However, using at least probable OAG as the outcome is a reasonable predictor for definite OAG alone, because our 5-year follow-up data showed that in 50% of the participants with probable OAG at baseline, the disease progressed to definite OAG. 17 Participants in whom at least possible OAG developed were compared with participants who remained free of any OAG. Therefore participants with a diagnosis of possible OAG at baseline and in whom probable or definite OAG had not developed at follow-up were excluded from the analyses. Participants diagnosed with at least probable OAG at baseline and participants with secondary and ACG were also excluded from the analyses. 
All potential risk variables that were assessed were initially independently selected and have been summarized in Table 1 . The initial value of the factors at baseline was used as the important predictor of glaucoma. Cardiovascular medications were grouped into β-blockers, α-blockers, angiotensin-converting enzyme inhibitors, thiazide diuretics, loop diuretics, calcium channel blockers, and peripheral vasodilators. Information on medications was obtained from the interview at the test centers, and participants were recontacted when possible for further clarification. Duration was deterined for all dietary supplements, medications, and medical illnesses. Pack-years of smoking, total years of smoking, and number of years since cessation of smoking were explored, in addition to cigarette smoking status (never, current, or past). The number of standard alcohol drinks was also considered in addition to alcohol status (never, current, or past). The model used to quantify lifetime ocular exposure to UV-B has been described, 18 annual ocular sun exposure was calculated by taking the logarithm of lifetime exposure divided by the age of the participant. 
Interview data were entered directly into a database (Paradox; Borland International, Scotts Valley, CA), and clinical data were entered twice. All data entry had internal consistency checks. A computer was used for statistical analysis (SAS statistical software, ver. 6.10; SAS Institute Inc, Cary, NC). The χ2 or Fisher exact test was performed for categorical variables, and the Mantel-Haenszel test was used for ordinal variables and the t-test for continuous variables. Age-adjusted relative risks with 95% confidence intervals were also presented. Risk variables with statistical significance of less than 0.10 were included in multivariate modeling. Multivariate analysis was performed using backward multiple logistic regression. 
Results
There were 3271 participants examined in the baseline study, 231 of whom died before the 5-year follow-up examination and 446 of whom migrated from Victoria, lost contact, or refused to attend the follow-up examination. Therefore, 2594 participants (85% of the surviving cohort) attended the follow-up. Of these, 105 participants who had incomplete data on IOP, CDR, and visual fields, either at baseline or at follow-up, and 52 participants who received a diagnosis of probable or definite OAG at baseline were excluded from the analyses. After all exclusions, 2415 participants were at risk for development of OAG, which represents 93% of those who participated in the follow-up examination (Fig. 1) . Those who did not participate in the follow-up study were more likely to be older (P < 0.01), male (P = 0.01), or of Greek or Italian background (P < 0.01) and to have visual acuity of less than 6/12 (P < 0.01), IOP greater than 21 mm Hg (P < 0.01), and a CDR higher than 0.7 (P < 0.01). 
The mean age of the participants at baseline was 58.7 ± 11.4 years (SD; range, 40–98) and 54% were women. The mean duration between baseline and follow-up examinations was 4.5 ± 0.64 years (range, 4–7 years). At the 5-year follow-up examination, there were 12 participants with definite diagnosis of OAG, 15 participants with probable OAG, and 39 participants with definite OAG (Fig. 1) . The overall incidence of at least possible OAG was 2.7% (95% confidence interval [CI] = 1.8–3.7), and that of at least probable OAG was 1.1% (95% CI = 0.8–1.4). 17  
Significant age-adjusted risk factors for development of at least possible OAG were past cigarette smokers, family history of glaucoma, the presence of age-related macular degeneration (AMD), the presence of pseudoexfoliation, and a baseline CDR higher than 0.7 (Table 2) . The variables significantly associated with development of at least probable OAG after adjustment for age were past cigarette smokers, having ever taken α-blockers, the presence of pseudoexfoliation, and a baseline CDR higher than 0.7 (Table 3)
The mean baseline IOP of participants who had at least possible OAG or at least probable OAG was marginally (1.2–1.5 mm Hg) but significantly higher (P < 0.05) than that of those who remained free of OAG (Tables 2 3) . This remained significant when adjusted for age (Tables 2 3) . The overall mean IOP at baseline was 15.1 ± 3.1 mm Hg (SD), and 2.5% of participants had IOP greater than 21 mm Hg. However, having an IOP higher than 21 mm Hg was not significantly associated in univariate analyses with increased risk. Only 6.1% of participants who had at least possible OAG and 7.4% of those who had at least probable OAG had a baseline IOP of greater than 21 mm Hg. Comparison between the handheld and Goldmann applanation tonometers used in the VIP has been presented, 16 and it showed no statistically significant difference between the two methods. 
After multivariate analyses, the factors significantly associated with the development of at least possible OAG were increased age, increased IOP, having a family history of glaucoma, the presence of pseudoexfoliation, the presence of AMD, and a baseline CDR higher than 0.7. The factors significantly associated with development of at least possible OAG were increased age, increased IOP, the presence of pseudoexfoliation, a baseline CDR higher than 0.7, and having ever taken α-blockers (Table 4)
Discussion
The present study follows on from the report on the 5-year incidence of OAG from the VIP. 17 Despite all that is known about OAG and its causing blindness worldwide, the epidemiology of OAG is still not well understood. 19 At present, the VIP, 17 the Barbados Incidence Eye Study, 20 the Dalby Sweden (incidence) Study, 21 and the Tierp Sweden (incidence) Glaucoma Survey 22 have reported incidence rates through prospective population-based surveys and the Collaborative Glaucoma Study 23 through a prospective clinic-based survey. However, potential risk factors have predominantly been evaluated through prevalence data. Prospective data provide better evidence on which to base inferences on causation, because of ascertainment of temporality, which is one of the major causative criteria 24 and has always been an inherent problem in studying a disease with low incidence. 
The present study showed that there was a significant risk of OAG after 60 years of age and the risk increased with each subsequent decade of life. A similar age-related trend was shown in the Barbados Incidence Eye Study 20 and numerous prevalence studies, 20 25 26 27 28 29 but not in the Dalby Sweden Study. 21 Increased age may reflect the cumulative effects of some other factors that cause the aging optic nerve head to be more vulnerable to IOP, even of normal range. 8 11 The present study also showed that development of OAG was not gender related. The Barbados Incidence Eye Study 20 had shown a higher incidence in men, whereas the Dalby Sweden Study 21 showed a higher incidence in women. This inconsistency was reflected in previous prevalence studies. 27 28 29  
The pressure theory of OAG is supported by the fact that IOP has been found consistently to be associated with OAG. 8 20 22 25 29 However, there is considerable individual variation in the level of pressure that is necessary to cause damage. 3 8 9 In this study, there was no significant risk obtained for IOP greater than 21 mm Hg but there was a significant risk with increasing IOP. Only 6.1% of those in whom at least possible OAG developed had baseline IOP greater than 21 mm Hg, which differed from the Barbados Incidence Eye Study (52.2%) 20 and the Tierp Sweden Glaucoma Survey (61.5%). 22 Previous prevalence studies revealed 25% to 70% with IOP of more than 21 mm Hg. 8 27 28 29 Such a large variation may be due to differences in IOP distribution among the various study populations and the substantial overlap within normal and OAG populations. The results in this study could also be influenced by the lower participation rate among those with IOP greater than 21 mm Hg. However, it highlights the arbitrary nature of distinguishing high- and low-tension glaucoma based on a certain IOP cutoff level, although these entities seem to exist morphologically and clinically. 9 10  
The high risk of OAG associated with a preexisting CDR higher than 0.7 was consistent with the Barbados Incidence Eye Study. 20 The prevalence study in the Baltimore Eye Survey 8 also reported larger cups and discs in the black population, which had a higher prevalence of OAG. A high CDR may indicate adverse variation in the organization of optic nerve head connective tissue, which has been shown to have some heritability 30 and racial influence, 8 suggesting that some individuals are born with high CDRs. However there is subjectivity involved in CDR measurements, and detection bias could occur by including it as a marker for diagnosis of OAG. Also an increased CDR could be considered part of the causal pathway toward clinically evident OAG, rather than an independent risk factor. 
This study showed approximately double the risk for development of at least possible OAG in individuals who reported a family history of glaucoma. No other incidence data are available to confirm this finding, but previous prevalence and case–control studies 31 32 33 34 have supported this association. However, as outlined in the Baltimore Eye Study, participants with previously diagnosed glaucoma tend to have greater awareness of family history. 8 33 The lower positive association in population-based studies compared with clinic-based studies is due to less recall bias, 35 which is further expected in this study, because it is also a prospective study. There was no distinction between family members in this study, but siblings have consistently been shown to have higher association with OAG. 33 34 Further characterization of hereditary factors lie in genetic studies, which recently linked several genes to adult-onset OAG. 35  
The vasogenic theory of OAG proposes that hemodynamic alterations may directly cause ischemic damage to the optic nerve head or act in concert with presenting IOP. 36 In this study, having ever taken α-blockers was shown to be a significant risk factor for development of at least probable OAG after multivariate adjustment. The result could have been spurious because of the small number of participants who had ever taken α-blockers. The specific reasons for the use of α-blockers was not obtained, but all participants who had ever taken α-blockers also reported a history of hypertension. The medication was used more by women (59%). Catecholamine receptors in the retina have been documented and α-adrenoreceptor agonists such as brimonidine have recently been shown to be neuroprotective in rat experimental models of the optic nerve. 37 However, whether α-blockers have any hemodynamic influence on the optic nerve head remains to be elucidated, given that no other antihypertensive medications were a significant risk. 
Other cardiovascular-related factors—in particular, smoking, cardiovascular disease, hypertension, and diabetes—failed to show any risk for OAG. The null result for smoking was similar to many other cross-sectional and retrospective surveys. 29 31 38 39 A weak correlation between smoking and increased IOP has been shown, 40 41 suggesting smoking may alternatively have an indirect relationship with glaucoma. 42 A recent case–control study showed cardiovascular disease to be associated more with the senile sclerotic subgroup of glaucomatous disc appearance, 43 but an association with OAG in general has not yet been demonstrated. 23 25 29 38 In contrast, systolic or diastolic hypertension has been shown to be associated with OAG in several studies, 38 44 45 but not in others. 25 29 31 It may be that perfusion pressure (systolic or diastolic blood pressure minus IOP) or hypotension are more appropriate variables for assessing optic nerve head ischemia, and both have been shown to be associated with OAG. 29 36 38 44 There is also no convincing association between diabetes and OAG, 29 46 47 and those studies that have revealed an association 48 49 may have inherent selection bias, because individuals with previously diagnosed glaucoma were more likely to know whether they have diabetes. 46  
Pseudoexfoliation of the lens capsule was shown to have 9 and 11 times the risk of development of at least possible OAG and at least probable OAG, respectively. Similar results have been reported in the Tierp Sweden Eye (incidence) Survey (RR = 9.8) 22 and the Blue Mountains Eye (prevalence) Study (odds ratio [OR] = 5.0). 50 The mechanism could be due to elevated IOP caused by exfoliation material obstructing the trabecular meshwork, but its level of risk was unaffected when adjusted for IOP. However, the result could be spurious, due to the low number of pseudoexfoliation cases, and studies in Australian aborigines showed that pseudoexfoliation is not always associated with an increased risk of glaucoma. 51 This study also showed that AMD may be a risk factor for at least possible OAG, although a prevalence study of AMD showed no association with OAG. 52 Both diseases, however, may have a common vascular pathogenesis. 
The present study is valuable from several perspectives. Although chance could play a role in some of the significant associations, given the multiple comparisons performed, this study has deliberately chosen all relevant potential risk factors based on previous studies and has analyzed all factors within the one study. This allows more complete multivariate adjustments, reflecting the heterogeneity of etiology and clinical manifestation of OAG. Also the results in this study can be generalized to the Victorian and Australian population, 15 and the study has provided prospective data with a high follow-up participation rate (85% of the surviving cohort), in which the risk of a given factor can be directly measured. However, there are certain limitations in this study, including having no data at intervening time points, and given that the VIP has shown that visual impairment increases mortality, 53 an underestimate of the incidence rate could arise. Also the small number of participants in whom OAG developed and the small number of participants exposed to certain risk factors analyzed could affect the stability of risk estimates due to wide confidence limits. 
In conclusion, this study has provided greater evidence to support certain risk factors for the development of OAG. However, we still should be cautious when interpreting the results unless further prospective epidemiologic studies on risk factors and physiological studies on pathomechanisms lend greater support and physiological correlation. 
 
Table 1.
 
Potential Risk Factors for Open-Angle Glaucoma
Table 1.
 
Potential Risk Factors for Open-Angle Glaucoma
Sociodemographic
 Age
 Gender
 Country of birth
 Educational level
 Occupation
 Private health insurance status
Behavioral
 Cigarette smoking
 Alcohol intake
Anthropometric
 Height
 Weight
 Body mass index
Dietary
 Regular vitamin intake
 Vitamin A intake
 Vitamin C intake
 Vitamin E intake
 β-Carotine intake
 Zinc intake
 Retinol intake
Familial
 Family history of glaucoma
Medical
 Hypertension
 Diabetes
 Cardiovascular disease
 Cardiovascular medications
 Corticosteroid
 Aspirin/NSAIDs
 Oral contraceptive pill
 HRT
Ocular
 Iris color
 Intraocular pressure
 Cup-disc ratio
 Refractive status
 Previous cataract surgery
 Age-related macular degeneration
 Previous eye injury
 Pseudoexfoliation
Other
 Sunlight exposure
 Early menarche
 Early menopause
Figure 1.
 
Flow chart showing participation, exclusions, and inclusions.
Figure 1.
 
Flow chart showing participation, exclusions, and inclusions.
Table 2.
 
Univariate Risk Factors for Development of at Least Possible OAG
Table 2.
 
Univariate Risk Factors for Development of at Least Possible OAG
Risk Variables Glaucoma* No Glaucoma* Crude RR (95% CI) Age-Adjusted RR (95% CI)
Age at baseline (n = 2415)
 40–49 3/66 (4.6) 639/2349 (27.2) 1.0
 50–59 12/66 (18.2) 770/2349 (32.8) 3.3 (0.93, 11.8)
 60–69 26/66 (39.4) 609/2349 (25.9) 9.1 (2.7, 30.2)
 70–79 17/66 (25.8) 270/2349 (11.5) 13.4 (3.9, 46.2)
 80+ 8/66 (12.1) 65/2349 (2.7) 26.6 (6.9, 103)
Smoking status (n = 2412)
 Never 24/66 (36.4) 1153/2346 (49.2) 1.0 1.0
 Current 10/66 (15.2) 398/2346 (17.0) 1.2 (0.57, 2.5) 1.4 (0.66, 3.0)
 Past 32/66 (48.5) 795/2346 (33.9) 1.9 (1.1, 3.3) 1.7 (1.01, 3.0)
Family history (n = 2385) 12/66 (18.2) 203/2319 (8.8) 2.3 (1.2, 4.3) 2.3 (1.2, 4.5)
AMD present (n = 2387) 22/66 (33.3) 328/2321 (14.1) 3.0 (1.8, 5.0) 2.0 (1.1, 3.4)
Pseudoexfoliation present (n = 2384) 4/63 (6.4) 11/2321 (0.5) 14.2 (5.8, 34.8) 7.9 (2.7, 22.7)
Previous cataract surgery (n = 2396) 5/66 (7.6) 50/2330 (2.2) 3.7 (1.5, 9.1) 1.6 (0.56, 4.7)
CDR more than 0.7 (n = 2386) 24/66 (36.4) 129/2320 (5.6) 9.7 (6.2, 15.1) 8.6 (5.3, 13.8)
IOP (mean mm) Hg ± SD (16.3 ± 3.3) (15.1 ± 3.1) 1.1 (1.04, 1.2) 1.1 (1.05, 1.2)
Table 3.
 
Univariate Risk Factors for Development of at Least Probable OAG
Table 3.
 
Univariate Risk Factors for Development of at Least Probable OAG
Risk Variables Glaucoma* No Glaucoma* Crude RR (95% CI) Age-Adjusted RR (95% CI)
Age at baseline (n = 2376)
 40–49 1/27 (3.7) 639/2349 (27.2) 1.0
 50–59 3/27 (11.1) 770/2349 (32.8) 2.5 (0.26, 24.0)
 60–69 11/27 (40.7) 609/2349 (25.9) 11.5 (1.5, 89.7)
 70–79 8/27 (29.6) 270/2349 (11.5) 19.0 (2.4, 152)
 80+ 4/27 (14.8) 64/2349 (2.7) 39.9 (4.4, 362)
Smoking status (n = 2373)
 Never 8/27 (29.6) 1153/2346 (49.2) 1.0 1.0
 Current 4/27 (14.8) 398/2346 (17.0) 1.5 (0.43, 4.8) 1.8 (0.52, 5.9)
 Past 15/27 (55.6) 795/2346 (33.9) 2.7 (1.1, 6.4) 2.5 (1.03, 5.9)
Family history (n = 2346) 3/27 (11.1) 203/2319 (8.8) 1.3 (0.39, 4.4) 1.3 (0.40, 4.5)
α-Blocker use (n = 2369) 3/27 (11.1) 48/2342 (2.1) 6.0 (2.0, 17.7) 3.5 (1.04, 11.9)
AMD present (n = 2348) 8/27 (29.6) 328/2321 (14.1) 2.6 (1.1, 5.7) 1.5 (0.64, 3.3)
Pseudoexfoliation present (n = 2346) 2/25 (8.0) 11/2321 (0.47) 18.3 (5.9, 56.5) 9.5 (2.4, 36.9)
Previous cataract surgery (n = 2357) 3/27 (11.1) 50/2330 (2.2) 5.7 (1.9, 17.0) 2.5 (0.51, 11.9)
CDR more than 0.7 (n = 2347) 11/27 (40.7) 129/2320 (5.6) 11.7 (6.2, 21.9) 10.1 (5.1, 19.8)
IOP (mean mm) Hg ± SD (16.6 ± 3.4) (15.1 ± 3.1) 1.1 (1.03, 1.2) 1.1 (1.04, 1.2)
Table 4.
 
Multivariate Risk Factors for Development of OAG
Table 4.
 
Multivariate Risk Factors for Development of OAG
Risk Variables At Least Possible OAG RR (95% CI) At Least Probable OAG RR (95% CI)
Age at baseline
 40–49 1.0 1.0
 50–59 2.6 (0.73–9.4) 2.0 (0.21–19.5)
 60–69 7.0 (2.1–23.8) 8.4 (1.1–66.6)
 70–79 8.3 (2.3–29.9) 12.2 (1.5–103)
 80+ 10.0 (2.2–46.0) 8.6 (0.63–116)
Family history 2.1 (1.03–4.2) 1.1 (0.29–4.0)
α-Blocker use 1.7 (0.45–6.1) 4.8 (1.2–18.8)
Pseudoexfoliation present 9.4 (2.6–34.4) 11.2 (2.0–63.3)
AMD present 2.2 (1.2–3.9) 1.7 (0.67–4.2)
IOP (mm Hg) 1.1 (1.03–1.2) 1.1 (1.04–1.2)
CDR more than 0.7 7.9 (4.4–14.1) 11.0 (4.6–26.8)
The authors thank the members of the glaucoma consensus panel, Paul Mitchell, Anne Brooks, Ivan Goldberg, Laurie Hirst, and Paul Healy. 
Coleman, AL. (1999) Glaucoma Lancet 354,1803-1810 [CrossRef] [PubMed]
Quigley, HA. (1996) Number of people with glaucoma worldwide Br J Ophthalmol 80,389-393 [CrossRef] [PubMed]
Schwartz, M, Yoles, E. (2000) Neuroprotection: a new treatment modality for glaucoma? Curr Opin Ophthalmol 11,107-111 [CrossRef] [PubMed]
Douglas, GR. (1998) Pathogenetic mechanisms of glaucoma not related to intraocular pressure Curr Opin Ophthalmol 9,34-38 [CrossRef] [PubMed]
Ritch, R. (2000) Neuroprotection: is it already applicable to glaucoma therapy? Curr Opin Ophthalmol 11,78-84 [CrossRef] [PubMed]
Palmberg, P. (2001) Risk factors for glaucoma progression: where does pressure fit in (editorial)? Arch Ophthalmol 119,897-898 [CrossRef] [PubMed]
Stewart, WC, Kolker, AE, Sharpe, ED, et al (2000) Factors associated with long-term progression or stability in primary open-angle glaucoma Am J Ophthalmol 130,274-279 [CrossRef] [PubMed]
Sommer, A. (1996) Glaucoma risk factors observed in the Baltimore Eye Survey Curr Opin Ophthalmol 7,93-98 [CrossRef] [PubMed]
Gramer, E, Tausch, M. (1995) The risk profile of the glaucomatous patient Curr Opin Ophthalmol 6,78-88
Spaeth, GL. (1994) A new classification of glaucoma including focal glaucoma Surv of Ophthalmol 38,S9-S17 [CrossRef]
Eid, TM, Spaeth, GL. (2000) The Glaucomas: Concepts and Fundamentals ,89-103 Lippincott Williams & Wilkins; Philadelphia. 1–8
Musch, DC, Arbor, A. (2001) Insights from incidence. The Barbados Eye Studies Arch Ophthalmol 119,117-118 [PubMed]
Smith, RJH. (1989) Incidence or prevalence (editorial) Br J Ophthalmol 73,481-482 [CrossRef] [PubMed]
Livingston, PM, Carson, CA, Stanislavsky, YL, et al (1994) Methods for a population-based study of eye disease: the Melbourne Visual Impairment Project Ophthalmic Epidemiol 1,139-148 [CrossRef] [PubMed]
Livingston, PM, Lee, SE, McCarty, CA, Taylor, HR. (1997) A comparison of participants with non-participants in a population-based epidemiologic study: the Melbourne Visual Impairment Project Ophthalmic Epidemiol 4,73-81 [CrossRef] [PubMed]
Wensor, MD, McCarty, CA, Stanislavsky, YL, et al (1998) The prevalence of glaucoma in the Melbourne Visual Impairment Project Ophthalmology 105,733-739 [CrossRef] [PubMed]
Mukesh, BN, McCarthy, CA, Rait, JL, Taylor, HR. (2002) Five-year incidence of open angle glaucoma: the Visual Impairment Project Ophthalmology 109,1047-1051 [CrossRef] [PubMed]
McCarty, CA, De Paola, C, Livingston, PM, Taylor, HR. (1996) Ocular exposure to UV-B in sunlight: the Melbourne Visual Impairment Project Bull World Health Organ 74,353-360 [PubMed]
West, SK. (2000) Looking forward to 20/20: A focus on the epidemiology of eye diseases Epidemiol Rev 22,64-70 [CrossRef] [PubMed]
Leske, MC, Connell, AMS, Wu, S, et al (2001) Incidence of open-angle glaucoma: The Barbados Eye Studies Arch Ophthalmol 119,89-95 [PubMed]
Bengtsson, B. (1989) Incidence of manifest glaucoma Br J Ophthalmol 73,483-487 [CrossRef] [PubMed]
Ekstrom, C. (1993) Elevated intraocular pressure and pseudoexfoliation of the lens capsule as risk factors for chronic open-angle glaucoma: a population-based five-year follow-up study Acta Ophthalmol 71,189-195
Armaly, MF, Krueger, DE, Maunder, L, et al (1980) Biostatistical analysis of the Collaborative Glaucoma Study: summary report of the risk factors for glaucomatous visual-field defects Arch Ophthalmol 98,2163-2172 [CrossRef] [PubMed]
Rothman, K, Greenland, S. (1998) Modern Epidemiology 2nd ed. ,23-28 Lippincott-Raven Philadelphia.
Weih, LM, Mukesh, N, McCarty, CA, Taylor, HR. (2001) Prevalence and predictors of open-angle glaucoma: results from the Visual Impairment Project Ophthalmology 108,1966-1972 [CrossRef] [PubMed]
Hollows, FC, Graham, PA. (1966) Intra-ocular pressure, glaucoma, and glaucoma suspects in a defined population Br J Ophthalmol 50,570-585 [CrossRef] [PubMed]
Mitchell, P, Smith, W, Attebo, K, Healey, PR. (1996) Prevalence of open-angle glaucoma in Australia: The Blue Mountains Eye Study Ophthalmology 103,1661-1669 [CrossRef] [PubMed]
Dielemans, I, Vingerling, JR, Wolfs, RCW, et al (1994) The prevalence of primary open-angle glaucoma in a population-based study in the Netherlands: The Rotterdam Study Ophthalmology 101,1851-1855 [CrossRef] [PubMed]
Leske, MC, Connell, AMS, Wu, S, et al (1995) Risk factors for open-angle glaucoma: The Barbados Eye Study Arch Ophthalmol 113,918-924 [CrossRef] [PubMed]
Schwartz, JT, Reuling, FH, Feinleib, M. (1975) Size of the physiologic cup of the optic nerve head: hereditary and environmental factors Arch Ophthalmol 93,776-778 [CrossRef] [PubMed]
Kaimbo, DK, Buntinx, F, Missotten, L. (2001) Risk factors for open angle glaucoma: a case-control study J Clin Epidemiol 54,166-171 [CrossRef] [PubMed]
Nemesure, B, He, Q, Mendell, N, et al (2001) Inheritance of open-angle glaucoma in the Barbados Family Study Am J Med Genet 103,36-43 [CrossRef] [PubMed]
Tielsch, JM, Katz, J, Sommer, A, et al (1994) Family history and risk of primary open-angle glaucoma: The Baltimore Eye Survey Arch Ophthalmol 112,69-73 [CrossRef] [PubMed]
Wolfs, RC, Klaver, CCW, Ramrattan, RS, et al (1998) Genetic risk of primary open-angle glaucoma: population-based Familial Aggregation Study Arch Ophthalmol 116,1640-1645 [CrossRef] [PubMed]
Budde, WM. (2000) Heredity in primary open-angle glaucoma Curr Opin Ophthalmol 11,101-106 [CrossRef] [PubMed]
Hayreh, SS. (1994) Progress in the understanding of the vascular etiology of glaucoma Curr Opin Ophthalmol 5,26-35 [CrossRef]
Wheeler, LA, Woldemussie, E. (2001) Alpha-2 adrenergic receptor agonists are neuroprotective in experimental models of glaucoma Eur J Ophthalmol 11,S30-S35 [PubMed]
Bonomi, L, Marchini, G, Marraffa, M, et al (2000) Vascular risk factors for primary open angle glaucoma: The Egna-Neumarkt Study Am Acad Ophthalmol 107,1287-1293
Klein, BE, Klein, R, Ritter, LL. (1993) Relationship of drinking alcohol and smoking to prevalence of open-angle glaucoma: The Beaver Dam Eye Study Ophthalmology 100,1609-1613 [CrossRef] [PubMed]
Carel, RS, Korezyn, AD, Rock, M, et al (1984) Associations between ocular pressure and certain health parameters Ophthalmology 91,311-314 [CrossRef] [PubMed]
Wu, SY, Leske, MC. (1997) Associations with intraocular pressure in the Barbados Eye Study Arch Ophthalmol 115,1572-1576 [CrossRef] [PubMed]
Cheng, ACK, Pang, CP, Leung, ATS, et al (2000) The association between cigarette smoking and ocular diseases Hong Kong Med J 6,195-202 [PubMed]
Broadway, DC, Drance, SM. (1998) Glaucoma and vasospasm Br J Ophthalmol 82,862-870 [CrossRef] [PubMed]
Tielsch, JM, Katz, J, Sommer, A, et al (1995) Hypertension, perfusion pressure, and primary open-angle glaucoma: a population-based assessment Arch Ophthalmol 113,216-221 [CrossRef] [PubMed]
Dielemans, I, Vingerling, JR, Algra, D, et al (1995) Primary open-angle glaucoma, intraocular pressure, and systemic blood pressure in the general elderly population: The Rotterdam Study Ophthalmology 102,54-60 [CrossRef] [PubMed]
Tielsch, JM, Katz, J, Quigley, HA, et al (1995) Diabetes, intraocular pressure and primary open-angle glaucoma in the Baltimore Eye Survey Ophthalmology 102,48-53 [CrossRef] [PubMed]
Ellis, JD, Evans, JMM, Ruta, DA, et al (2000) Glaucoma incidence in an unselected cohort of diabetic patients: is diabetes mellitus a risk factor for glaucoma? Br J Ophthalmol 84,1218-1224 [CrossRef] [PubMed]
Klein, BEK, Klein, R, Jensen, SC. (1994) Open-angle glaucoma and older-onset diabetes: The Beaver Dam Eye Study Ophthalmology 101,1173-1177 [CrossRef] [PubMed]
Dielemans, I, DeJong, PTVM, Stolk, R, et al (1996) Primary open-angle glaucoma, intraocular pressure, and diabetes mellitus in the general elderly population: The Rotterdam Study Ophthalmology 103,1271-1275 [CrossRef] [PubMed]
Mitchell, P, Wang, JJ, Hourithan, F. (1999) The relationship between glaucoma and pseudoexfoliation: The Blue Mountains Eye Study Arch Ophthalmol 117,1319-1324 [CrossRef] [PubMed]
Taylor, HR, Hollows, FC, Moran, D. (1977) Pseudoexfoliation of the lens in Australian Aborigines Br J Ophthalmol 61,473-475 [CrossRef] [PubMed]
Hirvela, H, Luukinen, H, Laara, E, et al (1996) Risk factors of age-related maculopathy in a population 70 years of age or older Ophthalmology 103,871-877 [CrossRef] [PubMed]
McCarty, CA, Nanjan, MB, Taylor, HR. (2001) Vision impairment predicts 5 year mortality Br J Ophthalmol 85,322-326 [CrossRef] [PubMed]
Figure 1.
 
Flow chart showing participation, exclusions, and inclusions.
Figure 1.
 
Flow chart showing participation, exclusions, and inclusions.
Table 1.
 
Potential Risk Factors for Open-Angle Glaucoma
Table 1.
 
Potential Risk Factors for Open-Angle Glaucoma
Sociodemographic
 Age
 Gender
 Country of birth
 Educational level
 Occupation
 Private health insurance status
Behavioral
 Cigarette smoking
 Alcohol intake
Anthropometric
 Height
 Weight
 Body mass index
Dietary
 Regular vitamin intake
 Vitamin A intake
 Vitamin C intake
 Vitamin E intake
 β-Carotine intake
 Zinc intake
 Retinol intake
Familial
 Family history of glaucoma
Medical
 Hypertension
 Diabetes
 Cardiovascular disease
 Cardiovascular medications
 Corticosteroid
 Aspirin/NSAIDs
 Oral contraceptive pill
 HRT
Ocular
 Iris color
 Intraocular pressure
 Cup-disc ratio
 Refractive status
 Previous cataract surgery
 Age-related macular degeneration
 Previous eye injury
 Pseudoexfoliation
Other
 Sunlight exposure
 Early menarche
 Early menopause
Table 2.
 
Univariate Risk Factors for Development of at Least Possible OAG
Table 2.
 
Univariate Risk Factors for Development of at Least Possible OAG
Risk Variables Glaucoma* No Glaucoma* Crude RR (95% CI) Age-Adjusted RR (95% CI)
Age at baseline (n = 2415)
 40–49 3/66 (4.6) 639/2349 (27.2) 1.0
 50–59 12/66 (18.2) 770/2349 (32.8) 3.3 (0.93, 11.8)
 60–69 26/66 (39.4) 609/2349 (25.9) 9.1 (2.7, 30.2)
 70–79 17/66 (25.8) 270/2349 (11.5) 13.4 (3.9, 46.2)
 80+ 8/66 (12.1) 65/2349 (2.7) 26.6 (6.9, 103)
Smoking status (n = 2412)
 Never 24/66 (36.4) 1153/2346 (49.2) 1.0 1.0
 Current 10/66 (15.2) 398/2346 (17.0) 1.2 (0.57, 2.5) 1.4 (0.66, 3.0)
 Past 32/66 (48.5) 795/2346 (33.9) 1.9 (1.1, 3.3) 1.7 (1.01, 3.0)
Family history (n = 2385) 12/66 (18.2) 203/2319 (8.8) 2.3 (1.2, 4.3) 2.3 (1.2, 4.5)
AMD present (n = 2387) 22/66 (33.3) 328/2321 (14.1) 3.0 (1.8, 5.0) 2.0 (1.1, 3.4)
Pseudoexfoliation present (n = 2384) 4/63 (6.4) 11/2321 (0.5) 14.2 (5.8, 34.8) 7.9 (2.7, 22.7)
Previous cataract surgery (n = 2396) 5/66 (7.6) 50/2330 (2.2) 3.7 (1.5, 9.1) 1.6 (0.56, 4.7)
CDR more than 0.7 (n = 2386) 24/66 (36.4) 129/2320 (5.6) 9.7 (6.2, 15.1) 8.6 (5.3, 13.8)
IOP (mean mm) Hg ± SD (16.3 ± 3.3) (15.1 ± 3.1) 1.1 (1.04, 1.2) 1.1 (1.05, 1.2)
Table 3.
 
Univariate Risk Factors for Development of at Least Probable OAG
Table 3.
 
Univariate Risk Factors for Development of at Least Probable OAG
Risk Variables Glaucoma* No Glaucoma* Crude RR (95% CI) Age-Adjusted RR (95% CI)
Age at baseline (n = 2376)
 40–49 1/27 (3.7) 639/2349 (27.2) 1.0
 50–59 3/27 (11.1) 770/2349 (32.8) 2.5 (0.26, 24.0)
 60–69 11/27 (40.7) 609/2349 (25.9) 11.5 (1.5, 89.7)
 70–79 8/27 (29.6) 270/2349 (11.5) 19.0 (2.4, 152)
 80+ 4/27 (14.8) 64/2349 (2.7) 39.9 (4.4, 362)
Smoking status (n = 2373)
 Never 8/27 (29.6) 1153/2346 (49.2) 1.0 1.0
 Current 4/27 (14.8) 398/2346 (17.0) 1.5 (0.43, 4.8) 1.8 (0.52, 5.9)
 Past 15/27 (55.6) 795/2346 (33.9) 2.7 (1.1, 6.4) 2.5 (1.03, 5.9)
Family history (n = 2346) 3/27 (11.1) 203/2319 (8.8) 1.3 (0.39, 4.4) 1.3 (0.40, 4.5)
α-Blocker use (n = 2369) 3/27 (11.1) 48/2342 (2.1) 6.0 (2.0, 17.7) 3.5 (1.04, 11.9)
AMD present (n = 2348) 8/27 (29.6) 328/2321 (14.1) 2.6 (1.1, 5.7) 1.5 (0.64, 3.3)
Pseudoexfoliation present (n = 2346) 2/25 (8.0) 11/2321 (0.47) 18.3 (5.9, 56.5) 9.5 (2.4, 36.9)
Previous cataract surgery (n = 2357) 3/27 (11.1) 50/2330 (2.2) 5.7 (1.9, 17.0) 2.5 (0.51, 11.9)
CDR more than 0.7 (n = 2347) 11/27 (40.7) 129/2320 (5.6) 11.7 (6.2, 21.9) 10.1 (5.1, 19.8)
IOP (mean mm) Hg ± SD (16.6 ± 3.4) (15.1 ± 3.1) 1.1 (1.03, 1.2) 1.1 (1.04, 1.2)
Table 4.
 
Multivariate Risk Factors for Development of OAG
Table 4.
 
Multivariate Risk Factors for Development of OAG
Risk Variables At Least Possible OAG RR (95% CI) At Least Probable OAG RR (95% CI)
Age at baseline
 40–49 1.0 1.0
 50–59 2.6 (0.73–9.4) 2.0 (0.21–19.5)
 60–69 7.0 (2.1–23.8) 8.4 (1.1–66.6)
 70–79 8.3 (2.3–29.9) 12.2 (1.5–103)
 80+ 10.0 (2.2–46.0) 8.6 (0.63–116)
Family history 2.1 (1.03–4.2) 1.1 (0.29–4.0)
α-Blocker use 1.7 (0.45–6.1) 4.8 (1.2–18.8)
Pseudoexfoliation present 9.4 (2.6–34.4) 11.2 (2.0–63.3)
AMD present 2.2 (1.2–3.9) 1.7 (0.67–4.2)
IOP (mm Hg) 1.1 (1.03–1.2) 1.1 (1.04–1.2)
CDR more than 0.7 7.9 (4.4–14.1) 11.0 (4.6–26.8)
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×