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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Ann Epidemiol. Author manuscript; available in PMC Jun 1, 2012.
Published in final edited form as:
PMCID: PMC3091261
NIHMSID: NIHMS285611

A prospective study of diabetes, lifestyle factors, and glaucoma in African-American women

Lauren A. Wise, Sc.D.,1 Lynn Rosenberg, Sc.D.,1 Rose G. Radin, M.P.H.,1 Cynthia Mattox, M.D.,2 Erynn B. Yang, M.D.,2 Julie R. Palmer, Sc.D.,1 and Johanna M. Seddon, M.D.3

Abstract

PURPOSE

To evaluate the association of self-reported type 2 diabetes, anthropometric factors, alcohol consumption, and cigarette smoking with risk of primary open-angle glaucoma (POAG) in a prospective cohort study of African-American women.

METHODS

From 1995 through 2007, 32,570 Black Women’s Health Study participants aged 21–69 at baseline were followed for incident POAG. Questionnaires were mailed biennially to update exposures and identify incident cases of POAG. Incidence rate ratios (IRRs) and 95% confidence intervals (CIs) were derived from Cox regression models.

RESULTS

During 416,171 person-years of follow-up, 366 incident POAG cases were confirmed by physician report. After adjustment for potential confounders, the IRR comparing women with and without type 2 diabetes was 1.58 (95%CI=1.17–2.13), and the IRR comparing current with never alcohol consumers was 1.35 (95% CI=1.05–1.73). Among women age <50 years, associations with diabetes and alcohol consumption were stronger, and POAG was significantly associated with BMI, waist circumference, waist-to-hip ratio, and both long-duration and high-intensity current smoking.

CONCLUSIONS

These results suggest that type 2 diabetes and current alcohol consumption are independent risk factors for POAG in African-American women, and that in addition to those factors, overall and central adiposity and smoking may be associated with increased risk of early-onset POAG

MeSH Key words: african-americans, female, diabetes, anthropometry, smoking, alcohol, primary open-angle glaucoma

BACKGROUND

Glaucoma is the second leading cause of blindness worldwide (1) and affects more than 2 million individuals in the United States (2). The most common form, primary open-angle glaucoma (POAG), is at least 3 times more common among African-Americans than Caucasians (24). Reasons for the ethnic disparity in POAG rates remain poorly understood. Risk factors for POAG include older age (5), family history of POAG (6), and ocular hypertension (710). Some studies have found an increased risk among men relative to women (5, 6), but others have found a decreased risk (11) or no difference in risk (2, 4).

Type 2 diabetes is a growing problem among African-American women (12). Some studies have found significant (1315) and non-significant (16) positive associations between type 2 diabetes and POAG risk, while other studies have found no association (1725), including several studies of participants with African ancestry (17, 1921, 23, 25). Whether anthropometric factors such as overall adiposity (as measured by body mass index (BMI)) or central adiposity (as measured by waist circumference or waist-to-hip ratio (WHR)) are determinants of POAG risk is unclear. Studies have found both positive (21) and inverse associations (6, 13, 26) between BMI and POAG, and we know of no studies that have evaluated central adiposity. Studies of smoking and POAG risk have yielded both positive (2123, 27, 28) and null results (2932), while most studies of alcohol consumption and POAG risk have been null (2123, 2931, 33, 34).

The present report evaluates the association of type 2 diabetes, anthropometric factors, alcohol consumption, and cigarette smoking with risk of incident POAG in the Black Women’s Health Study (BWHS), a large prospective cohort study of African-American women.

METHODS

Study population

The Black Women’s Health Study (BWHS) is an ongoing U.S. prospective cohort study, established in 1995 when 59,000 African-American women aged 21–69 were enrolled through mailed questionnaires (35). The baseline questionnaire elicited information on demographic, lifestyle, and behavioral characteristics, health care utilization, and medical history. The cohort is followed every 2 years by postal questionnaire and cohort retention has exceeded 80% through 2007. The institutional review board of Boston University Medical Center approved the study protocol.

Assessment of POAG

On the 1995, 1997, and 1999 questionnaires, women reported “glaucoma” under an open-ended question about “other serious illness” along with the year of first diagnosis. On subsequent follow-up questionnaires, women reported whether they had been diagnosed with “glaucoma” by a physician and the year of first diagnosis. Incident cases were those who reported to have been first diagnosed after March 1995.

A validation study to confirm self-reported incident glaucoma was initiated in 2005 and is ongoing. Participants are asked for permission to review their medical records regarding the diagnosis of glaucoma. The participant’s treating ophthalmologist or optometrist is asked to complete a questionnaire about the diagnosis and/or send copies of ocular records for review by the study ophthalmologists (J.M.S., C.M., E.B.Y.). The questionnaire asks about the diagnosis (primary open angle glaucoma, secondary glaucoma, narrow angle glaucoma, suspect glaucoma, and ocular hypertension), year of first diagnosis, signs of glaucoma, treatment history (date of initiation of medication(s), type and name of medication(s), laser or other surgery for POAG), family history of POAG, and whether there was gonioscopic evidence of open angles. In primary analyses, confirmed cases of POAG were defined as women whose physicians reported they had “primary open angle glaucoma” (current version of questionnaire) or “glaucoma” (2005 version of questionnaire), and at least two of three of the following glaucomatous signs: 1) “visual field defect,” 2) “increased intraocular pressure,” or 3) “optic nerve findings.”

To date, 812 women among the 1,426 who reported incident glaucoma have responded to our request for medical information. Of these, 640 (79%) gave permission to review their medical records, 93 (11%) denied the diagnosis, and 79 (10%) refused. We obtained medical record data for 630 of the 640 women who gave us permission (98%) and confirmed the self-report in 403 (64%). Of the 403 confirmed cases, 369 (92%) had POAG, 14 had secondary glaucoma (3%), 18 had narrow-angle glaucoma (4%), and 2 had low-tension glaucoma (<1%). Medical record data indicated that 97% of cases were using eye drops to treat POAG and 27% had surgery or laser treatments. The median age of cases was 56 years (interquartile range: 49–63 years). Of the 227 disconfirmed cases, most were classified by their physician as “suspect glaucoma” or “ocular hypertension” (90%), 7% had other ocular conditions such as diabetic retinopathy or cataracts, and 3% had no ocular condition. Of the 369 women with confirmed POAG, 3 had missing data on diabetes or BMI, leaving a total of 366 cases for the present analysis. Disconfirmed cases were treated as non-cases for the remainder of follow-up and cases pending validation were censored at their reported year of diagnosis.

Prevalence estimates for overweight and obesity at baseline were lower among women whose eye exam records were reviewed compared with those whose records were not reviewed (BMI ≥30: 33% versus 42%; BMI ≥25: 69% versus 76%), but estimates were similar with respect to diabetes (10% versus 14%), current smoking (16% vs. 20%), current drinking (29% vs. 27%), age (mean: 49.3 vs. 48.8 years), WHR (0.80 in both groups), and waist circumference (33.2 vs. 33.5 inches).

Assessment of exposures and covariates

On the 1995 questionnaire, participants reported whether they had ever been diagnosed with “diabetes (not during pregnancy),” their age at first diagnosis: <30, 30–39, 40–49, and ≥50 years, whether they were currently taking insulin or pills for diabetes, and the duration of medication use (<1, 1, 2, 3–4, ≥5 years). On each follow-up questionnaire, women were asked if they had been diagnosed with “diabetes not during pregnancy” in the prior two-year interval, the year of first diagnosis, and the use of injections or pills for diabetes. Women who reported diabetes with an age at first diagnosis before 30 years were excluded from analyses of type 2 diabetes because of the possibility that they had type 1 diabetes (3638). The accuracy of self-reported diabetes was assessed in a random sample of 656 women who reported a diagnosis after 1995. These women were asked to sign a release for their physician to be contacted, after which we mailed a questionnaire to the treating physician about criteria used for diagnosis (abnormal fasting blood glucose: >126 mg/dl or >140 mg/dl, casual plasma glucose level >200 mg/dl, oral glucose tolerance test >200 mg/dl, or other), the year of first diagnosis, and medications prescribed. Of the 293 women providing permission to contact their physicians, 229 physicians returned a completed questionnaire and 200 (96%) of these cases were confirmed: 217 had type 2 diabetes, 2 had type 1 diabetes, and 1 had steroid-induced diabetes. Of the 9 disconfirmed cases, 4 had metabolic syndrome, 2 had gestational diabetes, and 3 did not have diabetes.

In 1995, we collected data on self-reported height (in feet and inches), current weight (in pounds), weight at age 18 (in pounds), waist circumference at the level of the umbilicus (in inches), and hip circumference at its widest location (in inches). Current weight was updated every two years by follow-up questionnaire. BMI was calculated as weight (kg) divided by height squared (m2). Data on cigarette smoking, alcohol consumption, hypertension (and use of diuretics or antihypertensive medications), and physical activity were obtained at baseline and updated on all follow-up questionnaires. Education and energy intake as measured by Food Frequency Questionnaire (39) were ascertained at baseline. In 2001, we conducted a validation study of anthropometric measures among 115 BWHS participants in which Spearman correlations for self-reported versus technician-measured weight, height, waist circumference, and hip circumference were 0.97, 0.93, 0.75, and 0.74, respectively (40).

Exclusion criteria

Of the 59,028 women who completed the 1995 (baseline) questionnaire, we excluded women who did not complete at least one of the 2001, 2003, 2005, and 2007 questionnaires on which we asked specifically about glaucoma (N=5,454); those reporting “glaucoma” without a date of first diagnosis (N=168) or with a date before baseline (N=377); and those with incomplete information on important covariates (N=398). To reduce potential for detection bias, we further excluded non-cases who did not report having an eye exam within the past 2 years on the 2007 questionnaire (N=20,061). After these exclusions, 32,570 women remained in the present analyses. There were no appreciable differences between women who were and were not included in the analysis with respect to the prevalence of diabetes at baseline (3.9% vs. 4.3%), age at baseline (39.5 vs. 38.5 years), and anthropometric measures (BMI ≥25: 62% in both groups, BMI ≥30: 30% vs. 31%, mean waist circumference: 32 inches in both groups, mean WHR: 0.79 vs. 0.80). However, those included were less likely than those excluded to report current smoking (14% vs. 19%) and more likely to report alcohol consumption (29% vs. 25%) at baseline.

Data Analysis

Each participant contributed person-time from March 1995 until the diagnosis of POAG, death, loss to follow-up, or end of follow-up (March 2007), whichever came first. Analyses were carried out using SAS statistical software (version 9.1) (41). We used age- and time-stratified Cox regression (42, 43) to estimate incidence rate ratios (IRRs) and 95 percent confidence intervals (CI) for selected exposure variables in relation to risk of incident POAG. BMI was categorized according to WHO standards (44) and the other lifestyle variables were categorized based on their frequency distributions among non-cases. In multivariable Cox models, we mutually adjusted for each exposure variable. For example, in the assessment of BMI, terms were included for alcohol consumption (<1, 1–6, ≥7 drinks/week), cigarette smoking (current, past, never), and diabetes (no, yes without medications, yes with pills, yes with injections). We adjusted for adult BMI in analyses of each anthropometric variable except for weight change since age 18.

Potential POAG risk factors that were associated with the exposures of interest at baseline (Table 1) were added to the multivariable model, including education (≤12, 13–16, ≥17 years), hypertension (no, yes without medications, yes with medications), vigorous physical activity (none, <5, ≥5 hours/week), and energy intake (<1000, 1,000–1,499, ≥1,500 kilocalories/day). To test for trend, we modeled a single ordinal term coded as the score of each exposure category (including the unexposed) (45). Departures from the proportional hazards assumption were tested by the likelihood ratio test comparing models with and without cross-product terms for each exposure with age (<50 versus ≥50) and time period.

Table 1
Baseline characteristics of 32,570 women according to type 2 diabetes, body mass index, waist to hip ratio, and drinking and smoking status in the Black Women’s Health Study, 1995*

RESULTS

Among the 32,570 participants in the present analysis, 3% reported having type 2 diabetes, 32% were overweight (BMI 25–29 kg/m2), and 30% were obese (BMI ≥30 kg/m2) in 1995 (Table 1). Type 2 diabetes was positively associated with age, BMI, waist circumference, WHR, adult weight gain, energy intake, hypertension, and smoking, and inversely associated with education, alcohol consumption, and vigorous exercise. Obesity (BMI ≥30 kg/m2) was positively associated with age, adult weight gain, energy intake, diabetes, and hypertension, and inversely associated with height, education, and vigorous exercise. WHR was positively associated with BMI, adult weight gain, energy intake, hypertension, and diabetes. Current drinking was positively associated with age, smoking, and energy intake. Smoking was positively associated with age, current drinking, energy intake, and hypertension, and inversely associated with education and adult weight gain.

There were 366 incident cases of POAG confirmed by physician report during 416,171 person-years of follow-up. Type 2 diabetes was positively associated with POAG risk (Table 2). The multivariable incidence rate ratio (IRR) comparing women with and without type 2 diabetes was 1.58 (95% CI: 1.17–2.13). Type 2 diabetes treated with pills or injections was associated with increased POAG risk, but untreated diabetes was not. There was no evidence that POAG risk increased with increasing years since diabetes diagnosis (P-trend=0.64).

Table 2
Association of diabetes, anthropometric factors, alcohol consumption, and cigarette smoking with risk of primary open-angle glaucoma. The Black Women’s Health Study, 1995–2007.

BMI, weight gain since age 18, height, waist circumference, and WHR were not associated with POAG risk in multivariable models (Table 2). Further control for BMI at age 18 had little effect on the IRR for weight gain since age 18 (data not shown). Current alcohol consumption was positively associated with POAG risk: the multivariable IRR was 1.35 (95% CI: 1.05–1.73) for current drinking relative to never drinking, and 1.60 (95% CI: 1.06–2.43) for current consumption of ≥7 drinks/week relative to non-drinking. Cigarette smoking, whether defined by recency, intensity, or duration of smoking, was not associated with POAG risk. While some associations observed in the overall sample were stronger among younger (age <50) than older women (age ≥50), significant age-interactions were found only for BMI and waist circumference (Table 3).

Table 3
Association of diabetes anthropometric factors, alcohol consumption and cigarette smoking with risk of primary open-angle glaucoma, by age. The Black Women’s Health Study, 1995–2007.

In analyses that excluded cases with “increased intraocular pressure” as a glaucomatous sign, the association between diabetes and POAG was stronger than that found in the original analysis (N=329 cases: IRR=1.69, 95% CI: 1.24–2.30), suggesting that bias due to greater detection among diabetics with increased intraocular pressure did not explain our results. In analyses restricted to cases for whom “visual field defect” was noted as a glaucomatous sign (N=215 cases), the multivariable IRR comparing women with and without type 2 diabetes was 1.47 (95% CI: 0.99–2.18) and the IRR for current relative to never alcohol consumption was 1.32 (95% CI: 0.95–1.83). Suggestive positive associations were also found among non-cases with “suspect glaucoma” or “ocular hypertension” (N=203) in association with type 2 diabetes (IRR=1.42, 95% CI: 0.94–2.13) and current alcohol consumption of ≥7 drinks per week (IRR=1.61, 95% CI: 0.95–2.74). Finally, in analyses that added back the women who did not report a recent eye exam (N=20,061), associations of POAG with BMI and diabetes were similar to those presented in the primary analyses (data not shown).

DISCUSSION

In the present study of over 32,000 African-American women aged 21–69 years, type 2 diabetes was associated with a 58% increased risk of POAG overall, and a more than two-fold increased risk of POAG among women under age 50 years. Current alcohol consumption was also positively associated with POAG. Overall and central adiposity and smoking were associated with increased risk of early-onset POAG, albeit the smoking findings were based on small numbers of heavy smokers.

Our overall results for type 2 diabetes are consistent with two cohort studies among Caucasians that reported relative risks in the range of 1.6 to 1.8 (13, 16), and a meta-analysis of case-control and cross-sectional studies that reported a 1.5-fold increased risk (14). However, our findings conflict with other cross-sectional (1820), case-control (2123), and prospective (17, 24, 25, 28) studies showing no association, including several studies that enrolled large numbers of participants with African ancestry (17, 1921, 25).

Diabetes may influence risk of POAG via hyperglycemia-related vascular constriction leading to elevated intraocular pressure (46, 47) and increased susceptibility to glaucomatous optic nerve damage (48). According to Sato and Roy, high glucose levels in the aqueous humor of patients with diabetes may increase fibronectin synthesis and accumulation in the trabecular meshwork (49). The accelerated depletion of trabecular meshwork cells is a characteristic feature of the outflow system in POAG (49). Pasquale et al. noted the correlation between glycosylated hemoglobin and increased ocular pressure (13, 50, 51) and speculated that glycosylation of extracellular matrix proteins in the trabecular meshwork could further reduce outflow facility in patients with type 2 diabetes (13). Therefore, relative obstruction of the outflow of aqueous humor via the trabecular meshwork may be a primary mechanism by which diabetes affects POAG risk. To our knowledge, there are no studies that have assessed blood glucose levels or level of glycemic control among diabetics in relation to POAG risk, but such studies would permit a direct test of this hypothesis.

With regard to anthropometric factors, one case-control study among African Blacks found a weak positive association between BMI and POAG after control for diabetes (21), while three other studies in Black (6) and White (13, 26) populations found an inverse association. None of these studies stratified by age. Most studies of alcohol consumption and POAG risk have been case-control studies. They have largely reported null associations (21, 22, 30, 31, 52) except for a small study that reported a strong inverse association (27). One case-control study of ocular hypertension also suggested an inverse association (8). The only prospective study is the pooled analysis of the Nurses’ Health Study and the Health Professionals Follow-up Study, in which results were null for current drinkers having the same level of exposure as our study (53).

Previous results on cigarette smoking come largely from case-control studies, yielding positive (2123, 27, 28) and null (2931, 33) associations. A pooled analysis of two prospective cohort studies, the Nurses Health Study and the Health Professionals Follow-up Study, found no overall association between current smoking and POAG (32). Similar to the present investigation, those studies were prospective, confined to participants with recent eye exams and to cases confirmed by medical record, and controlled for several risk factors for POAG. However, these studies did not stratify by age.

To our knowledge, only one study has examined whether risk factors for early-onset POAG differ from late onset POAG (54). The Baltimore Eye study found a positive association between systemic hypertension and POAG overall, but the association was stronger in older than younger participants (54). It is plausible, as observed in the present study, that some risk factors are stronger for early-onset illness than for later-onset disease. For example, heavy cigarette smoking is associated with a doubling or less in risk of myocardial infarction among elderly men and women, but the relative increase in risk of myocardial infarction for heavy smokers less than 45 years of age is at least tenfold (5558).

A study limitation is that participants were not systematically screened for POAG. To minimize the potential for underdetection of POAG, we confined the analytic sample to women who reported a recent eye examination. However, if women with diabetes were more likely to receive a comprehensive eye examination for POAG relative to those without diabetes, a spurious positive association between diabetes and POAG would have resulted. We believe that such diagnostic bias is unlikely in the present study for two reasons: 1) the findings for time since diagnosis of diabetes did not reveal a peak in POAG risk shortly after diagnosis with diabetes, but rather a similar increased magnitude in POAG risk over time, and 2) there was no increased risk of POAG among other groups for which a more comprehensive eye exam was also likely (e.g., hypertensives). Nonetheless, we cannot rule out the possibility that a more comprehensive eye exam among diabetics contributed to the positive associations observed in this study.

All cases were confirmed by physician diagnosis to maximize specificity. Because we relied on the judgment of the diagnosing eye care provider that glaucomatous optic neuropathy was present, and because different ophthalmologists will not have used exactly the same criteria, some cases may have been misclassified. However, the findings from secondary analyses implementing more stringent case definitions were highly consistent with the overall findings.

Our study had several strengths. The BWHS is the largest study to date of POAG in African-American women, a group at increased risk of POAG (2, 3, 11). Accuracy of self-reported type 2 diabetes, weight, height, waist circumference and hip circumference has been shown in validation studies. The prospective assessment of risk factors for POAG served both to clarify the temporal relationship of the associations examined and to minimize reporting bias. We controlled for several POAG risk factors in multivariable models, thereby reducing the potential for confounding. Although the BWHS is a convenience sample of African-American women with higher levels of education than the general population, associations identified in our study did not vary appreciably by factors other than age. Moreover, rates of POAG were similar to those found in other studies of black women (59), suggesting our results may extend to a wider population of black women. Finally, high cohort retention (>80%) reduced the likelihood of selection bias.

At present, few modifiable risk factors for POAG have been identified. Observations from the present study regarding the association of type 2 diabetes with POAG are consistent with several studies conducted to date. In addition, many of these findings are new for African-American women. Confirmation of these associations in a population systematically screened for POAG would be desirable. Since the prevalence of type 2 diabetes is 2- to 3-fold higher in African-American women than Caucasian women (12), efforts to reduce the occurrence of type 2 diabetes could have a large impact on POAG incidence in this population. In addition, if confirmed, the positive associations of POAG with alcohol consumption, as well as with obesity and cigarette smoking in younger women, provide an opportunity for primary prevention efforts.

Acknowledgments

This work was supported by the National Cancer Institute at the National Institutes of Health [CA058420]. The content is solely the responsibility of the authors and does not necessarily represent the official view of the National Cancer Institute or the National Institutes of Health. We acknowledge the ongoing contributions of Black Women’s Health Study participants and staff.

List of abbreviations and acronyms

BMI
body mass index
WHR
waist-to-hip ratio
POAG
primary open angle glaucoma
IRR
incidence rate ratio
CI
confidence interval

Footnotes

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References

1. Quigley HA. Number of people with glaucoma worldwide. Br J Ophthalmol. 1996;80:389–93. [PMC free article] [PubMed]
2. Friedman DS, Wolfs RC, O’Colmain BJ, Klein BE, Taylor HR, West S, et al. Prevalence of open-angle glaucoma among adults in the United States. Arch Ophthalmol. 2004;122:532–8. [PMC free article] [PubMed]
3. Leske MC, Connell AM, Wu SY, Nemesure B, Li X, Schachat A, et al. Incidence of open-angle glaucoma: the Barbados Eye Studies. The Barbados Eye Studies Group. Arch Ophthalmol. 2001;119:89–95. [PubMed]
4. Tielsch JM, Sommer A, Katz J, Royall RM, Quigley HA, Javitt J. Racial variations in the prevalence of primary open-angle glaucoma. The Baltimore Eye Survey. JAMA. 1991;266:369–74. [PubMed]
5. Leske MC, Connell AM, Schachat AP, Hyman L. The Barbados Eye Study. Prevalence of open angle glaucoma. Arch Ophthalmol. 1994;112:821–9. [PubMed]
6. Leske MC, Connell AM, Wu SY, Hyman LG, Schachat AP. Risk factors for open-angle glaucoma. The Barbados Eye Study. Arch Ophthalmol. 1995;113:918–24. [PubMed]
7. Leske MC. The epidemiology of open-angle glaucoma: a review. Am J Epidemiol. 1983;118:166–91. [PubMed]
8. Seddon J, Schwartz B, Flowerdew G. A case-control study of ocular hypertension. Arch Ophthalmol. 1983;101:891–4. [PubMed]
9. Heijl A, Leske MC, Bengtsson B, Hyman L, Bengtsson B, Hussein M, et al. Reduction of Intraocular Pressure and Glaucoma Progression: Results From the Early Manifest Glaucoma Trial. Arch Ophthalmol. 2002;120:1268–79. [PubMed]
10. Kass MA, Heuer DK, Higginbotham EJ, Johnson CA, Keltner JL, Miller JP, et al. The Ocular Hypertension Treatment Study: A Randomized Trial Determines That Topical Ocular Hypotensive Medication Delays or Prevents the Onset of Primary Open-Angle Glaucoma. Arch Ophthalmol. 2002;120:701–13. [PubMed]
11. Quigley HA, Broman AT. The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol. 2006;90:262–7. [PMC free article] [PubMed]
12. Brancati FL, Kao WHL, Folsom AR, Watson RL, Szklo M. Incident Type 2 Diabetes Mellitus in African American and White Adults: The Atherosclerosis Risk in Communities Study. JAMA. 2000;283:2253–9. [PubMed]
13. Pasquale LR, Kang JH, Manson JE, Willett WC, Rosner BA, Hankinson SE. Prospective study of type 2 diabetes mellitus and risk of primary open-angle glaucoma in women. Ophthalmology. 2006;113:1081–6. [PubMed]
14. Bonovas S, Peponis V, Filioussi K. Diabetes mellitus as a risk factor for primary open-angle glaucoma: a meta-analysis. Diabet Med. 2004;21:609–14. [PubMed]
15. Chopra V, Varma R, Francis BA, Wu J, Torres M, Azen SP. Type 2 diabetes mellitus and the risk of open-angle glaucoma: the Los Angeles Latino Eye Study. Ophthalmology. 2008;115:227–32. [PubMed]
16. Ellis JD, Evans JM, Ruta DA, Baines PS, Leese G, MacDonald TM, et al. Glaucoma incidence in an unselected cohort of diabetic patients: is diabetes mellitus a risk factor for glaucoma? DARTS/MEMO collaboration. Diabetes Audit and Research in Tayside Study. Medicines Monitoring Unit. Br J Ophthalmol. 2000;84:1218–24. [PMC free article] [PubMed]
17. Gordon MO, Beiser JA, Kass MA. for the Ocular Hypertension Treatment Study G. Is a History of Diabetes Mellitus Protective Against Developing Primary Open-angle Glaucoma? Arch Ophthalmol. 2008;126:280–1. [PubMed]
18. Quigley HA, West SK, Rodriguez J, Munoz B, Klein R, Snyder R. The prevalence of glaucoma in a population-based study of Hispanic subjects: Proyecto VER. Arch Ophthalmol. 2001;119:1819–26. [PubMed]
19. Tielsch JM, Katz J, Quigley HA, Javitt JC, Sommer A. Diabetes, intraocular pressure, and primary open-angle glaucoma in the Baltimore Eye Survey. Ophthalmology. 1995;102:48–53. [PubMed]
20. Wormald RP, Basauri E, Wright LA, Evans JR. The African Caribbean Eye Survey: risk factors for glaucoma in a sample of African Caribbean people living in London. Eye. 1994;8 (Pt 3):315–20. [PubMed]
21. Kaimbo DK, Buntinx F, Missotten L. Risk factors for open-angle glaucoma: a case-control study. J Clin Epidemiol. 2001;54:166–71. [PubMed]
22. Charliat G, Jolly D, Blanchard F. Genetic risk factor in primary open-angle glaucoma: a case-control study. Ophthalmic Epidemiol. 1994;1:131–8. [PubMed]
23. Wilson MR, Hertzmark E, Walker AM, Childs-Shaw K, Epstein DL. A case-control study of risk factors in open angle glaucoma. Arch Ophthalmol. 1987;105:1066–71. [PubMed]
24. de Voogd S, Ikram MK, Wolfs RCW, Jansonius NM, Witteman JCM, Hofman A, et al. Is Diabetes Mellitus a Risk Factor for Open-Angle Glaucoma?: The Rotterdam Study. Ophthalmology. 2006;113:1827–31. [PubMed]
25. Leske MC, Suh-Yuh W, Anselm H, Robert H, Barbara N. Risk Factors for Incident Open-angle Glaucoma: The Barbados Eye Studies. Ophthalmology. 2008;115:85–93. [PubMed]
26. Gasser P, Stumpfig D, Schotzau A, Ackermann-Liebrich U, Flammer J. Body mass index in glaucoma. J Glaucoma. 1999;8:8–11. [PubMed]
27. Fan BJ, Leung YF, Wang N, Lam SC, Liu Y, Tam OS, et al. Genetic and environmental risk factors for primary open-angle glaucoma. Chin Med J (Engl) 2004;117:706–10. [PubMed]
28. Le A, Mukesh BN, McCarty CA, Taylor HR. Risk Factors Associated with the Incidence of Open-Angle Glaucoma: The Visual Impairment Project. Invest Ophthalmol Vis Sci. 2003;44:3783–9. [PubMed]
29. Reynolds DC. Relative risk factors in chronic open-angle glaucoma: an epidemiological study. Am J Optom Physiol Opt. 1977;54:116–20. [PubMed]
30. Katz J, Sommer A. Risk factors for primary open angle glaucoma. Am J Prev Med. 1988;4:110–4. [PubMed]
31. Ponte F, Giuffre G, Giammanco R, Dardanoni G. Risk factors of ocular hypertension and glaucoma. The Casteldaccia Eye Study. Doc Ophthalmol. 1994;85:203–10. [PubMed]
32. Kang JH, Pasquale LR, Rosner BA, Willett WC, Egan KM, Faberowski N, et al. Prospective study of cigarette smoking and the risk of primary open-angle glaucoma. Arch Ophthalmol. 2003;121:1762–8. [PubMed]
33. Morgan RW, Drance SM. Chronic open-angle glaucoma and ocular hypertension: an epidemiological study. Br J Ophthalmol. 1975;59:211–5. [PMC free article] [PubMed]
34. Kang JH, Willett WC, Rosner BA, Hankinson SE, Pasquale LR. Prospective study of alcohol consumption and the risk of primary open-angle glaucoma. Ophthalmic Epidemiology. 2007;14:141–7. [PubMed]
35. Rosenberg L, Adams-Campbell LL, Palmer JR. The Black Women’s Health Study: a follow-up study for causes and preventions of illness. JAMWA. 1995;50:56–8. [PubMed]
36. Krishnan S, Rosenberg L, Djousse L, Cupples LA, Palmer JR. Overall and central obesity and risk of type 2 diabetes in U.S. black women. Obesity (Silver Spring) 2007;15:1860–6. [PubMed]
37. Krishnan S, Rosenberg L, Singer M, Hu FB, Djousse L, Cupples LA, et al. Glycemic index, glycemic load, and cereal fiber intake and risk of type 2 diabetes in US black women. Arch Intern Med. 2007;167:2304–9. [PubMed]
38. Palmer JR, Boggs DA, Krishnan S, Hu FB, Singer M, Rosenberg L. Sugar-sweetened beverages and incidence of type 2 diabetes mellitus in African American women. Arch Intern Med. 2008;168:1487–92. [PMC free article] [PubMed]
39. Kumanyika SK, Mauger D, Mitchell DC, Phillips B, Smiciklas-Wright H, Palmer JR. Relative validity of food frequency questionnaire nutrient estimates in the Black Women’s Health Study. Ann Epidemiol. 2003;13:111–8. [PubMed]
40. Wise LA, Palmer JR, Spiegelman D, Harlow BL, Stewart EA, Adams-Campbell LL, et al. Influence of body size and body fat distribution on risk of uterine leiomyomata in U.S. black women. Epidemiol. 2005;16:346–54. [PMC free article] [PubMed]
41. SAS Institute Inc. SAS/STAT User’s Guide, Version 9.1. Cary, NC: SAS Institute; 2004.
42. Cox DR, Oakes D. Analysis of survival data. London, UK: Chapman Hall; 1984.
43. Hertzmark E, Spiegelman D. The SAS MPHREG Macro. Boston, MA: Channing Laboratory; 2001.
44. World Health Organisation. Physical Status: The Use and Interpretation of Anthropometry. Geneva: World Health Organisation; 1995. [PubMed]
45. Breslow NE, Day NE. The Design and Analysis of Cohort Studies. II. Lyon, France: IARC; 1987. Statistical Methods in Cancer Research. [PubMed]
46. Johnson MA, Lutty GA, McLeod DS, Otsuji T, Flower RW, Sandagar G, et al. Ocular structure and function in an aged monkey with spontaneous diabetes mellitus. Experimental Eye Research. 2005;80:37–42. [PubMed]
47. Wilson MR, Martone J. Epidemiology of chronic open angle glaucoma. In: Ritch R, Shields MB, Krupin T, editors. The Glaucomas. St. Louis: Mosby; 1996. pp. 753–68.
48. Kanamori A, Nakamura M, Mukuno H, Maeda H, Negi A. Diabetes has an additive effect on neural apoptosis in rat retina with chronically elevated intraocular pressure. Current Eye Research. 2004;28:47–54. [PubMed]
49. Sato T, Roy S. Effect of high glucose on fibronectin expression and cell proliferation in trabecular meshwork cells. Investigative Ophthalmology & Visual Science. 2002;43:170–5. [PubMed]
50. Klein BEK, Klein R, Linton KLP. Intraocular pressure in an American community: The Beaver Dam Eye Study. Investigative Ophthalmology and Visual Science. 1992;33:2224–8. [PubMed]
51. Hennis A, Wu S-Y, Nemesure B, Leske MC. Hypertension, diabetes, and longitudinal changes in intraocular pressure. Ophthalmology. 2003;110:908–14. [PubMed]
52. Leske MC, Warheit-Roberts L, Wu SY. Open-angle glaucoma and ocular hypertension: the Long Island Glaucoma Case-control Study. Ophthalmic Epidemiol. 1996;3:85–96. [PubMed]
53. Kang JH. Prospective Study of Alcohol Consumption and the Risk of Primary Open-Angle Glaucoma. Ophthalmic Epidemiology. 2007;14:141–7. [PubMed]
54. Tielsch JM, Katz J, Sommer A, Quigley HA, Javitt JC. Hypertension, perfusion pressure, and primary open-angle glaucoma. A population-based assessment. Arch Ophthalmol. 1995;113:216–21. [PubMed]
55. Slone D, Shapiro S, Rosenberg L, Kaufman DW, Hartz S, Rossi AC, et al. Relation of cigarette smoking to myocardial infarction in young women. New England Journal of Medicine. 1978;298:1273–6. [PubMed]
56. Hoit BD, Gilpin EA, Henning H, Maisel AA, Dittrich H, Carlisle J, et al. Myocardial infarction in young patients: an analysis by age subsets. Circulation. 1986;74:712–21. [PubMed]
57. Gordon T, Kannel WB, McGee D, Dawber TR. Death and coronary attacks in men after giving up cigarette smoking. A report from the Framingham study. Lancet. 1974;2:1345. [PubMed]
58. Wilson PWF, D’Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of Coronary Heart Disease Using Risk Factor Categories. Circulation. 1998;97:1837–47. [PubMed]
59. Leske MC, Wu SY, Honkanen R, Nemesure B, Schachat A, Hyman L, et al. Nine-Year Incidence of Open-Angle Glaucoma in the Barbados Eye Studies. Ophthalmology. 2007;114:1058–64. [PubMed]
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