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Table 1.  Person-time Characteristics by Total Nitrate Intake During the Follow-up Period in the Nurses’ Health Study (1984-2012) and the Health Professionals Follow-up Study (1986-2012)
Person-time Characteristics by Total Nitrate Intake During the Follow-up Period in the Nurses’ Health Study (1984-2012) and the Health Professionals Follow-up Study (1986-2012)
Table 2.  Primary Open-Angle Glaucoma by Quintiles of Nitrate Intake in the Nurses’ Health Study (1984-2012) and the Health Professionals Follow-up Study (1986-2012)a
Primary Open-Angle Glaucoma by Quintiles of Nitrate Intake in the Nurses’ Health Study (1984-2012) and the Health Professionals Follow-up Study (1986-2012)a
Table 3.  Subtypes of Primary Open-Angle Glaucoma by Quintiles of Nitrate Intake in the Nurses’ Health Study (1984-2012) and the Health Professionals Follow-up Study (1986-2012)a
Subtypes of Primary Open-Angle Glaucoma by Quintiles of Nitrate Intake in the Nurses’ Health Study (1984-2012) and the Health Professionals Follow-up Study (1986-2012)a
Table 4.  Quintiles of Daily Servings of Foods High in Nitrate in Relation to All POAG and Para-POAG in the Nurses’ Health Study (1984-2012) and the Health Professionals Follow-up Study (1986-2012)a
Quintiles of Daily Servings of Foods High in Nitrate in Relation to All POAG and Para-POAG in the Nurses’ Health Study (1984-2012) and the Health Professionals Follow-up Study (1986-2012)a
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Original Investigation
Journal Club
March 2016

Association of Dietary Nitrate Intake With Primary Open-Angle Glaucoma: A Prospective Analysis From the Nurses’ Health Study and Health Professionals Follow-up Study

Journal Club PowerPoint Slide Download
Author Affiliations
  • 1Channing Division of Network Medicine, Department of Medicine, Brigham & Women’s Hospital and Harvard Medical School, Boston, Massachusetts
  • 2Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts
  • 3Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts
  • 4Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts
  • 5Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital Research Institute, Boston
  • 6Glaucoma Service, Massachusetts Eye and Ear Infirmary, Boston
JAMA Ophthalmol. 2016;134(3):294-303. doi:10.1001/jamaophthalmol.2015.5601
Abstract

Importance  Nitric oxide signaling alterations in outflow facility and retinal blood flow autoregulation are implicated in primary open-angle glaucoma (POAG). Nitric oxide donation has emerged as a POAG therapeutic target. An exogenous source of nitric oxide is dietary nitrates.

Objective  To evaluate the association between dietary nitrate intake, derived mainly from green leafy vegetables, and POAG.

Design, Setting, and Participants  We followed up participants biennially in the prospective cohorts of the Nurses’ Health Study (63 893 women; 1984-2012) and the Health Professionals Follow-up Study (41 094 men; 1986-2012) at each 2-year risk period. Eligible participants were 40 years or older, were free of POAG, and reported eye examinations.

Exposures  The primary exposure was dietary nitrate intake. Information on diet and potential confounders was updated with validated questionnaires.

Main Outcomes and Measures  The main outcome was the incidence of POAG and POAG subtypes; 1483 cases were confirmed with medical records and classified into subtypes defined by intraocular pressure (IOP) (≥22 or <22 mm Hg) or by visual field (VF) loss pattern at diagnosis (peripheral loss only or early paracentral loss). Cohort-specific and pooled multivariable rate ratios (MVRRs) and 95% CIs were estimated.

Results  During 1 678 713 person-years of follow-up, 1483 incident cases of POAG were identified. The mean (SD) age for the 1483 cases was 66.8 (8.3). Compared with the lowest quintile of dietary nitrate intake (quintile 1: approximately 80 mg/d), the pooled MVRR for the highest quintile (quintile 5: approximately 240 mg/d) was 0.79 (95% CI, 0.66-0.93; P for trend = .02). The dose response was stronger (P for heterogeneity = .01) for POAG with early paracentral VF loss (433 cases; quintile 5 vs quintile 1 MVRR = 0.56; 95% CI, 0.40-0.79; P for trend < .001) than for POAG with peripheral VF loss only (835 cases; quintile 5 vs quintile 1 MVRR = 0.85; 95% CI, 0.68-1.06; P for trend = .50). The association did not differ (P for heterogeneity = .75) by POAG subtypes defined by IOP (997 case patients with IOP ≥22 mm Hg: quintile 5 vs quintile 1 MVRR = 0.82; 95% CI, 0.67-1.01; P for trend = .11; 486 case patients with IOP <22 mm Hg: quintile 5 vs quintile 1 MVRR = 0.71; 95% CI, 0.53-0.96; P for trend = .12). Green leafy vegetables accounted for 56.7% of nitrate intake variation. Compared with consuming 0.31 servings per day, the MVRR for consuming 1.45 or more servings per day was 0.82 for all POAG (95% CI, 0.69-0.97; P for trend = .02) and 0.52 for POAG with paracentral VF loss (95% CI, 0.29-0.96; P for trend < .001).

Conclusions and Relevance  Higher dietary nitrate and green leafy vegetable intake was associated with a lower POAG risk, particularly POAG with early paracentral VF loss at diagnosis.

Introduction

Elevated intraocular pressure (IOP) and impaired autoregulation of optic nerve blood flow are implicated in primary open-angle glaucoma (POAG).1-10 Endothelial dysfunction, a key contributor to vascular regulatory impairment, is involved in both processes.11 The vascular endothelium regulates the microcirculation via vasoactive factors; one potent factor is nitric oxide (NO). In the l-arginine–NO pathway, NO is formed from l-arginine and oxygen by NO synthases (NOSs), such as endothelial NOS (NOS3).12

Abundant evidence supports NO’s role in POAG pathogenesis.13 With administration of a systemic NOS inhibitor, differences in ocular blood flow response were observed between cases with POAG and controls.14 In addition, polymorphisms in NOS3 (OMIM 163729), the gene for NOS3, were associated with lower blood NO levels15-19 and POAG.16,20-22

As an alternative to the l-arginine–NO pathway, when under hypoxia23,24 or when NOS may be dysfunctional,14,16,20,21 which may occur in POAG, exogenous nitrate can be reduced to nitrite25-27 by commensal bacteria28-30 and subsequently converted enzymatically or nonenzymatically to NO in tissues26,31-33 in the nitrate-nitrite-NO pathway.34-38 Evidence suggests that nitrate or nitrite, precursors for NO, is beneficial for blood circulation.34,39-42 Dietary nitrate is predominately derived from green leafy vegetables,43 which contribute approximately 80% of nitrate intake.29 Although plasma nitrite levels16,44 or intake of specific vegetables45,46 have been associated with POAG, to our knowledge, dietary nitrate intake as a specific nutrient has not been evaluated. Therefore, we evaluated dietary nitrate and incident POAG in a longer-than-25-year prospective study of 63 893 women in the Nurses’ Health Study (NHS) and 41 094 men in the Health Professionals Follow-up Study (HPFS).

Box Section Ref ID

At a Glance

  • Question: What is the association between dietary nitrate intake, derived mainly from green leafy vegetables, and primary open-angle glaucoma (POAG)?

  • Findings: Compared with the lowest quintile of dietary nitrate intake (approximately 80 mg/d), the highest quintile (approximately 240 mg/d) was associated with a 21% lower risk of all POAG and 44% lower risk of POAG with early paracentral visual field loss, a subtype of POAG linked to dysfunction in blood flow autoregulation.

  • Meaning: These findings could have important implications for POAG if the association of higher dietary nitrate and green leafy vegetable intake with a lower POAG risk is confirmed in observational or intervention studies.

Methods

The NHS began in 1976 with 121 700 US registered female nurses (30-55 years old) who completed a mailed questionnaire.47 The HPFS began in 1986 with 51 529 US male health professionals (dentists, veterinarians, pharmacists, optometrists, osteopaths, and podiatrists) aged 40 to 75 years.48 Participants have been followed up biennially with mailed questionnaires of health, diet, and diseases, such as glaucoma. Follow-up rates were high (>85%). The human research committees of Brigham & Women’s Hospital, Massachusetts Eye and Ear Infirmary, and the Harvard School of Public Health approved this study. Participants’ return of a completed questionnaire was accepted as implied informed consent by the human research committees.

The first detailed assessment of diet with a semiquantitative food frequency questionnaire (SFFQ) was conducted in 1984 for the NHS and 1986 for the HPFS; thus, these dates are the baseline years. Participants contributed person-years in approximately 2-year units from the return date of 1 questionnaire to that of another until the earliest occurrence of a glaucoma report, cancer, death, loss to follow-up, or the end of study in 2012. Eligible participants were 40 years or older (when glaucoma risk increases) and reported undergoing an eye examination in the 2-year risk period (to minimize possible detection bias).

We excluded at baseline the following NHS and HPFS participants, respectively: 47 512 and 1596 who did not respond to baseline SFFQs or had outlying total caloric intakes; 4011 and 1927 with prevalent cancers, excluding nonmelanoma skin cancer, because cancer diagnoses could alter diet; 902 and 1035 with prevalent glaucoma; 450 and 1874 lost to follow-up from 1976 to 1984 (NHS) or less than 2 years of baseline (NHS and HPFS); and 2391 and 3251 who never reported an eye examination during follow-up. After these exclusions, 66 435 and 41 846 NHS and HPFS participants, respectively, were eligible; however, at the beginning of each 2-year risk period, we applied additional provisional exclusions for age and eye examination status. For example, for the 1984-1986 (NHS) and 1986-1988 (HPFS) risk periods, respectively, only 45 955 and 29 039 contributed person-years after we provisionally excluded participants (20 480 and 12 807) who were younger than 40 years and reported no eye examinations. In later periods, those provisionally excluded were allowed in analyses if they met eligibility criteria during follow-up. Thus, during the study period, 63 893 and 41 094 NHS and HPFS participants, respectively, ever contributed person-years.

Ascertainment of Cases With POAG and Classification of POAG by IOP and VF Loss Pattern

We included 1483 cases with confirmed incident POAG (1000 women and 483 men). Glaucoma case ascertainment occurred biennially when we asked about eye examinations and physician diagnoses of glaucoma. For those self-reporting glaucoma, we sought permission to contact eye care professionals, who were requested to send all visual fields (VFs) with medical records or a completed glaucoma questionnaire with items on maximal IOP, status of the filtration apparatus, optic nerve structural information, ophthalmic surgery, and VF loss. Records were reviewed by a glaucoma specialist (L.R.P.), masked to participants’ diet, to confirm POAG cases using standardized criteria.

Cases had to be appraised as definite or probable POAG. For definite POAG cases (>70% of all cases), the following criteria were required: (1) gonioscopy in which the filtration angle was not occludable in either eye; (2) slitlamp biomicroscopy with no signs in either eye of pigment dispersion syndrome, uveitis, exfoliation syndrome, trauma, or rubeosis; and (3) reproducible VF defects consistent with POAG on 2 or more reliable tests. For probable POAG cases, the slitlamp examination and VF criteria were also required, but documentation of pupil dilation without subsequent adverse events was accepted in lieu of gonioscopy. For VF defects, the type of perimetry was not restricted; however, full static threshold testing was documented in 95% and kinetic VFs in less than 1%. For static threshold or suprathreshold tests, the following reliability definitions were used: fixation loss of 33% or less, false-positive rate of 20% or less, and false-negative rate of 20% or less. For kinetic VFs, a VF test result was considered reliable unless the examiner noted to the contrary.

New glaucoma diagnoses were self-reported by 8611 and 3791 NHS and HPFS participants, respectively, and these diagnoses were confirmed as various types of glaucoma or suspicion of glaucoma in 5487 (63.7%) and 2058 (54.3%): potential POAG with VF loss (2290 [26.6%] and 985 [26.0%]), elevated IOP or optic disc cupping only (1559 [18.1%] and 612 [16.1%]), and other types of glaucoma or suspicion of glaucoma (1639 [19.0%] and 461 [12.2%]). The remaining diagnoses (3124 [36.3%] and 1733 [45.7%]) were unconfirmed because participants (689 [8.0%] and 563 [14.9%]) or eye care professionals (435 [5.1%] and 204 [5.4%]) were unreachable, participants denied permission for record review (984 [11.4%] and 362 [9.7%]), participants indicated the report was erroneous (835 [9.7%] and 547 [14.4%]), or eye care professionals refuted the glaucoma diagnosis (181 [2.1%] and 57 [1.5%]). Among those diagnoses classified as potential POAG with VF loss, we included only the definite or probable POAG cases (NHS, 1000 and HPFS, 483); other confirmed and unconfirmed self-reports were censored as of the diagnosis date.

For secondary analyses, we classified cases into subtypes by IOP and by VF loss pattern at diagnosis. We defined subtypes of high-tension (n = 997; 651 and 346 of NHS and HPFS participants, respectively) and normal-tension POAG (n = 486; 349 and 137 of NHS and HPFS participants, respectively) as those with a maximum untreated IOP of 22 mm Hg or higher or less than 22 mm Hg, respectively. We defined subtypes by VF loss pattern: those with peripheral VF loss only (n = 835; 576 and 259 of NHS and HPFS participants, respectively) or early paracentral VF loss (n = 433; 288 and 145 of NHS and HPFS participants, respectively) or undetermined VF loss (n = 215; 136 and 79 of NHS and HPFS participants, respectively) with a previously described method.49 For a case with peripheral VF loss only, nasal step, temporal wedge, or Bjerrum scotoma was present with no paracentral loss. For a case with early paracentral loss, there was paracentral loss only or paracentral loss with VF loss in the Bjerrum area and/or nasal step area in the same hemifield but without any temporal wedge loss. We included the latter paracentral group because those with only paracentral loss were uncommon (approximately 21%), whereas those with clear paracentral loss frequently also had peripheral loss. Cases (n = 215) with undetermined VF loss (ie, VF loss in the paracentral and any temporal wedge regions in the same eye or paracentral loss in 1 hemifield with peripheral loss only in the other hemifield) were censored. The proportion of those with normal-tension POAG was 38.3% in those with early paracentral VF loss and 28.8% in those with peripheral VF loss only.

Measurement of Intake of Nitrate and Vegetable Sources of Nitrate

Validated SFFQs were administered every 2 to 4 years. The 1984 NHS SFFQ included 116 items, and similar versions were used from 1986 in the NHS (126 items) and HPFS (131 items). The SFFQ inquires about the average intake of a serving of a food or beverage in the preceding year, with intake choices from never or less than 1 per month to 6 or more per day. To convert responses into average daily intakes of nitrate, nutrient content information of each food obtained from updated US Department of Agriculture food composition50 was used and combined with frequency information.

For primary analyses, we examined daily intake of nitrate and vegetables. Vegetables included celery and others in 4 groups: green leafy vegetables (iceberg lettuce; romaine lettuce; kale, mustard, or chard; cooked spinach; and raw spinach), cruciferous vegetables (kale, mustard, or chard; broccoli; cabbage or coleslaw; cauliflower; and Brussels sprouts), root vegetables (beets, potatoes, onions, carrots, yams or sweet potatoes), and tomato-based foods (tomatoes, tomato sauce, tomato juice).

We evaluated updated cumulatively averaged intakes, which better represent long-term exposure and have less random measurement error.51 With cumulative averaging, the average of all available information was used (eg, in the NHS in 1984, the 1984 nitrate value was used; in 1986, the average of the 1984 and 1986 values was used). Intakes of other dietary factors (eg, other antioxidants, caffeine, alcohol, folate, or flavonoids) were similarly derived.

Validity of SFFQ Assessment of Nitrate and Vegetable Sources

The reproducibility and validity of the SFFQ have been reported previously.52,53 In a biomarker study54 among 630 participants, being in the highest tertile of dietary nitrate intake based on the SFFQ was associated with a 3.18-mmol/L increase in plasma nitrate (P = .1). In 127 participants who completed both the SFFQ and multiple weighed dietary records,55 the SFFQ performed reasonably well, with a mean correlation with dietary record values of 0.46 across vegetables: from 0.25 for kale, mustard, or chard greens to 0.73 for lettuce.

Statistical Analysis

For analyses of nitrate intake, intake values were total energy adjusted using the residual method.56 For food analyses, we adjusted for cumulatively updated total calories.

We calculated incidence rates of POAG by dividing the incident cases by person-years accrued for each intake category (quintiles). For multivariable analyses, we conducted Cox proportional hazards regression analysis stratified by age in months and the specific 2-year period at risk57 while controlling for potential glaucoma risk factors. We derived incidence rate ratios and 95% CIs. We conducted tests for trend by evaluating the significance of a variable representing quintile median values.

Potential covariates were updated biennially from baseline: glaucoma family history, African heritage, body mass index (calculated as weight in kilograms divided by height in meters squared), pack-years of smoking, hypertension, diabetes mellitus, physical activity (metabolic equivalent hours per week), number of eye examinations reported during follow-up, multivitamin use, and, among women, age at menopause and postmenopausal hormone use. In addition, main multivariable models (model 1) included other dietary components: cumulatively updated intake categories of total calories, alcohol, and caffeine. In additional multivariable models (model 2), we further adjusted for intake of folate, vitamin A, and antioxidants (alpha carotene, beta carotene, beta cryptoxanthin, lycopene, lutein or zeaxanthin, other carotenoids, flavonoids, and vitamins C and E).

We analyzed cohort-specific data separately and performed tests for heterogeneity to check for appropriateness of pooling the results. We then pooled the results using meta-analytic methods that incorporated random effects.58

Secondary Analyses

We performed several secondary analyses. First, we evaluated nitrate intake only as of baseline or as of the most recent questionnaire. Second, we separately analyzed the risks of high- vs normal-tension POAG and POAG with peripheral VF loss only vs early paracentral loss. When testing whether the associations between nitrate and 1 POAG subtype are different from those with another subtype, we combined the data sets into 1, then conducted Cox proportional hazards regression analyses that further stratified on the 2 cohorts (to allow for differing hazard functions) and used the Lunn-McNeil approach59 to derive the P for heterogeneity.

Results

Quiz Ref IDDuring 1 678 713 person-years of follow-up, we identified 1483 incident cases. The mean (SD) age for the 1483 cases was 66.8 (8.3). Highest consumers of dietary nitrate consumed more antioxidants (carotenoids, vitamin C, vitamin E), flavonoids, folate, and vitamin A; exercised more; and were more frequently African American (Table 1). They were also leaner and smoked less. These differences were adjusted for in multivariable analyses.

In nitrate analyses, cohort-specific results were not heterogeneous and thus were pooled. Age-adjusted and multivariable analyses revealed similar associations (Table 2). Compared with the lowest quintile (quintile 1) of approximately 80 mg/d of nitrate, the pooled multivariable relative risk (MVRR) of POAG in the main model (model 1) was 0.81 (95% CI, 0.69-0.96) for quintile 2, 0.88 (95% CI, 0.75-1.04) for quintile 3, 0.90 (95% CI, 0.66-1.23) for quintile 4, and 0.79 (95% CI, 0.66-0.93) for quintile 5 (P for trend = .02) (Table 2). When other dietary factors (model 2) were also adjusted for, similar inverse associations were observed (pooled MVRR for quintile 5 vs quintile 1, 0.67; 95% CI, 0.52-0.85; P for trend = .01).

When we explored the timing of intake, no association was found between nitrate intake only at baseline and intake at the most recent SFFQ (pooled MVRR for model 1, 0.88; 95% CI, 0.74-1.04; P for trend = .21 for baseline intake and 0.91; 95% CI, 0.76-1.09; P for trend = .13 for most recent intake for quintile 5 compared with quintile 1).

When nitrate intake with POAG subtypes characterized by IOP at diagnosis was evaluated (Table 3), we observed similar associations, and the P for heterogeneity was .75. However, we observed differences (P for heterogeneity = .01) in associations by VF subtypes (pooled MVRR for POAG with peripheral VF loss only, 0.85; 95% CI, 0.68-1.06; P for trend = .50; pooled MVRR for POAG with early paracentral VF loss, 0.56; 95% CI, 0.40-0.79; P for trend < .001 for quintile 5 compared with quintile 1).

For specific foods and food groups (Table 4), when compared with those consuming a median of 0.31 servings per day of green leafy vegetables (quintile 1), the pooled MVRR for 1.45 servings per day (quintile 5) was 0.82 (95% CI, 0.69-0.97; P for trend = .02) for overall POAG and 0.52 (95% CI, 0.29-0.96; P for trend < .001) for POAG with early paracentral VF loss. Among green leafy vegetables, the pooled MVRR for quintile 5 vs quintile 1 ranged from 0.72 to 0.89 for overall POAG; for POAG with early paracentral VF loss, the pooled MVRRs were 0.69 (95% CI, 0.49-0.97; P for trend = .001) for iceberg lettuce, 0.71 (95% CI, 0.29-1.75; P for trend = .19) for romaine lettuce, and 0.33 (95% CI, 0.16-0.69; P for trend = .01) for kale, mustard, or chard greens. Associations were not observed with other nitrate-contributing food or food groups except root vegetables. Inverse associations were observed for root vegetables in men only (P for heterogeneity = .01): in men, the pooled MVRR for consuming 1.76 servings per day (quintile 5) compared with 0.50 servings per day (quintile 1) was 0.68 (95% CI, 0.48-0.96; P for trend = .04) for overall POAG and 0.51 (95% CI, 0.27-0.96; P for trend = .04) for POAG with early paracentral VF loss.

Discussion

Quiz Ref IDGreater intake of dietary nitrate and green leafy vegetables was associated with a 20% to 30% lower POAG risk; the association was particularly strong (40%-50% lower risk) for POAG with early paracentral VF loss at diagnosis, for which ocular vascular dysregulation has been implicated.60

Quiz Ref IDEvidence suggests a key role of the NO system in POAG pathogenesis; alterations of this system may dysregulate ocular blood flow14,61 and IOP.62-68 Elevated IOP was observed in a murine POAG model after the gene for soluble guanylate cyclase, the NO intracellular receptor, was knocked out.69 Nitric oxide may regulate IOP by mediating aqueous humor outflow. In an in vitro study,70 glaucomatous Schlemm canal cells produced negligible NO after shear stress compared with nonglaucomatous cells. Thus, exogenous NO donators are emerging as new glaucoma therapeutics.13

The nitrate-nitrite-NO pathway may be an important alternative source of NO in POAG. One lettuce serving can yield more NO than that generated daily via the l-arginine–NO pathway.71 Tissue NO bioavailability and cerebral blood flow can increase with nitrate salts72,73 and nitrate-rich beet juice supplementation.74-79 Therefore, dietary nitrate supplementation represents a practical method to increase NO levels. Indeed, across the 2 cross-sectional studies in all (95 cases among 1155 total)45 or only African American (77 cases among 587 total)46 women in the Study of Osteoporotic Fractures, the only vegetable that was consistently inversely associated with POAG was kale or collard greens: 1 serving or more per month of kale or collard greens was significantly associated with 55% to 70% reduced odds of POAG.

The stronger inverse association of POAG with early paracentral VF loss is consistent with evidence that this subtype is more strongly associated with vascular dysregulation.69,80,81 The blood vessels for the inferior paracentral fibers are in the macula vulnerability zone82 and make more acute arcuate turns than others, creating greater shear forces that could compromise local blood flow.61 In addition, among patients with glaucoma and autonomic dysfunction or abnormal peripheral microcirculation, paracentral VF defects were more common80; one hypothesis is that central fibers may have relatively high oxygen demand and thus be more vulnerable to vascular dysregulation.83,84 Furthermore, genetic loci related to the NO pathway (eg, CAV1/CAV285 [OMIM 601047/OMIM 601048] and GUCY1A3/GUCY1B3 [OMIM 139396/OMIM 139397] regions69) are most strongly associated with POAG with paracentral loss. Thus, further studies of exogenous nitrate and POAG with paracentral VF loss are warranted.

This was a large prospective study with 1483 incident cases identified from 63 893 women and 41 094 men followed up for more than 25 years, with high follow-up rates. With repeated questionnaires, we evaluated nitrate intake and POAG in various ways (ie, baseline, recent, and cumulative intake) and controlled for numerous updated POAG risk factors.

Quiz Ref IDOur study had a few limitations. We could not conduct repeated eye examinations; consequently, we relied on questionnaires and medical records for disease confirmation. Our case ascertainment method had low sensitivity; however, methodologically, incidence rate ratios can still be valid if the case definition is highly specific and the ascertainment method is unrelated to exposure.86 Our case definition was highly specific with the requirement of reproducible VF loss, the case ascertainment was unlikely to be related to diet, and we required eye examinations at each follow-up cycle to minimize bias. Another limitation was residual confounding by other dietary factors because nitrate-rich vegetables may have other nutrients. However, we adjusted for intake of other nutrients, and the inverse associations were robust. We may have had some misclassification of nitrate intake from errors in participants recall and because vegetable nitrate content can vary by soil conditions, season, and storage87,88; however, these factors would have biased associations toward the null. In addition, because both cohorts are more than 90% white, our results may not be generalizable; however, in a study of African Americans, kale and collard intake was also associated with a lower POAG risk.46 Finally, these data represent findings from the first population-based observational study; thus, the association between dietary nitrate consumption and POAG should be interpreted cautiously and confirmed.

Conclusions

Greater intake of dietary nitrate, an exogenous NO source, was associated with a lower risk of POAG, particularly POAG with early paracentral VF loss. These results, if confirmed in observational and intervention studies, could have important public health implications.

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Article Information

Submitted for Publication: July 29, 2015; final revision received November 6, 2015; accepted November 23, 2015.

Corresponding Author: Jae H. Kang, ScD, Channing Division of Network Medicine, Department of Medicine, Brigham & Women’s Hospital and Harvard Medical School, 181 Longwood Ave, Boston, MA 02115 (nhjhk@channing.harvard.edu).

Published Online: January 14, 2016. doi:10.1001/jamaophthalmol.2015.5601.

Author Contributions: Dr Kang had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Kang, Willett, Pasquale.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Kang, Pasquale.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Kang, Willett, Rosner, Pasquale.

Obtained funding: Pasquale.

Administrative, technical, or material support: Willett, Wiggs, Pasquale.

Study supervision: Pasquale.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.

Funding/Support: This work was supported by grants UM1 CA186107, UM1 CA167552, EY09611, and EY015473 (Dr Pasquale) and grant R21 EY022766 (Dr Wiggs) from the National Institutes of Health and the Arthur Ashley Foundation, the Harvard Glaucoma Center of Excellence (Drs Pasquale and Wiggs), and a Harvard Medical Distinguished Ophthalmology Scholar Award (Dr Pasquale).

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and the decision to submit the manuscript for publication.

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