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American Journal of Public Health logoLink to American Journal of Public Health
. 2016 Sep;106(9):1684–1689. doi: 10.2105/AJPH.2016.303317

Contribution of the Nurses’ Health Study to the Epidemiology of Cataract, Age-Related Macular Degeneration, and Glaucoma

Jae H Kang 1,✉, Juan Wu 1, Eunyoung Cho 1, Soshiro Ogata 1, Paul Jacques 1, Allen Taylor 1, Chung-Jung Chiu 1, Janey L Wiggs 1, Johanna M Seddon 1, Susan E Hankinson 1, Debra A Schaumberg 1, Louis R Pasquale 1
PMCID: PMC4981799  PMID: 27459452

Abstract

Objectives. To review the contribution of the Nurses’ Health Study (NHS) to understanding the genetic and lifestyle factors that influence the risk of cataract, age-related macular degeneration, and glaucoma.

Methods. We performed a narrative review of the publications of the NHS between 1976 and 2016.

Results. The NHS has helped to elucidate the roles of genetics, lifestyle factors (e.g., cigarette smoking associated with cataract extraction and age-related macular degeneration), medical conditions (e.g., diabetes associated with cataract extraction and glaucoma), and dietary factors (e.g., greater carotenoid intake and lower glycemic diet associated with lower risk of age-related macular degeneration) in the etiology of degree and progression of lens opacities, cataract extraction, age-related macular degeneration, primary open-angle glaucoma, and exfoliation glaucoma.

Conclusions. The findings from the NHS, combined with those of other studies, have provided compelling evidence to support public health recommendations for helping to prevent age-related eye diseases: abstinence from cigarette smoking, maintenance of healthy weight and diabetes prevention, and a healthy diet rich in fruits and vegetables.

Loss of vision is a major cause of disability in the United States that substantially compromises quality of life and is feared by many.1 The number of Americans aged 65 years or older will double by 2050,2 and consistent with this, the major causes of blindness and visual impairment, such as cataract, age-related macular degeneration, and glaucoma, are also projected to increase dramatically, because these are strongly age-related conditions.3 By 2020, a projected 5.5 million adults in the United States will be visually impaired.3 The economic costs of major vision disorders is tremendous (> $138 billion annually, including direct costs and lost productivity4) and will grow considerably. Major advances have been made in treatments, and there has been a parallel research effort resulting in major advances in the understanding of these diseases for primary prevention.

The Nurses’ Health Study (NHS) has provided compelling results that inform important topics in the epidemiology of cataract, age-related macular degeneration, and glaucoma. We have summarized some of the major contributions, and the Appendix (available as a supplement to the online version of this article at http://www.ajph.org) provides a list of the relevant NHS publications reviewed here.

EYE DISEASES AND THE NURSES’ HEALTH STUDY

With its prospective design, large sample size, long follow-up, and rich, updated data on numerous exposures, the NHS offers extraordinary opportunities for the epidemiological investigation of eye diseases. In one approach, a subset of several hundred NHS participants completed detailed standardized eye examinations in Boston, Massachusetts, which allowed studies of graded lens opacities and age-related maculopathy. However, because repeated eye examinations were unattainable on tens of thousands of geographically dispersed NHS participants overall, one challenge for using the data from the whole cohort was to develop approaches that would allow valid evaluations of risk factor–disease relationships.

First, we relied on participants’ self-report of physician-diagnosed eye diseases as the initial step in case identification. Because of their medical training and background, NHS participants presumably have better health care access and knowledge of eye diseases than does a general population sample; thus, when asked about diagnosed eye diseases, the majority would be able to self-report true occurrences of eye disease relatively accurately.

Second, for each eye disease, we developed case definitions that maximized specificity (minimizing false positives). In prospective observational studies, this specificity, when combined with the reasonable assumption that disease underascertainment would be similar in those exposed versus unexposed to a factor of interest, helped to ensure that measures of association (e.g., rate ratios) would be unbiased.5 For example, cataract extraction confirmed by medical records from eye care providers served as one definition for clinically significant cataract. Not only was this definition highly specific, but it also represented the outcome of greatest public health importance.

Third, in the main analyses or in sensitivity analyses, we included only those reporting eye examinations to minimize detection bias. For example, this restriction was applied in all main analyses of primary open-angle glaucoma (POAG), because approximately 50% of new patients are unaware of their condition.6 Furthermore, for some investigations, the NHS results were pooled with results from the Health Professionals Follow-up Study (HPFS), a cohort of male health professionals with a similar design and case definitions, to maximize power. A major limitation was that because of the lower sensitivity of case ascertainment and lack of standardized eye examinations, neither generating accurate estimates of disease incidence rates nor conducting large studies of detailed standardized clinical features was possible. However, using innovative methodological approaches, NHS investigators could conduct extensive epidemiological studies of complex eye diseases in a large geographically dispersed population.

CATARACT

Untreated cataract is the leading cause of blindness worldwide,7 and the direct annual costs in the United States for cataract are several billions of dollars.4 Cataract is an opacification of the crystalline lens, and the only treatment is surgical removal. The precise mechanisms underlying cataract formation are not clear. Normally, the lens is a highly organized syncytium of cells that are precisely arranged to maximize transparency. Over time, lens proteins aggregate and precipitate, and the extracellular spaces between lens fiber cells become perturbed, leading to lens opacities that impair vision. There are 3 major cataract phenotypes. These reflect the predominant location of lens opacity—nuclear, cortical, and posterior subcapsular—with each likely having a different, although possibly overlapping, etiology.8

Two approaches for cataract research were used in the NHS. First, cataract extraction—defined as a participant’s self-report confirmed with information from an eye care provider (also used for cataract subtyping)—was used as an outcome; all participants aged 45 years or older were eligible. Second, standardized lens opacity grading was used as an outcome among several hundred NHS participants aged 50 years or older who completed standardized eye examinations in Boston.

Smoking

Age, cumulative ultraviolet light exposure, and smoking are now considered established risk factors for cataract.8 Smoking induces oxidative stress and is associated with lower levels of plasma antioxidants.9 Early studies showed associations between smoking and cataract; however, they were mainly cross-sectional and did not address smoking cessation. In the NHS, we observed that smoking 65 or more pack-years was associated with a 1.5- to 1.8 times greater risk of cataract extraction, particularly for nuclear and posterior subcapsular cataract, and that there was a dose response, with more cigarettes smoked in current smokers.

Furthermore, we observed inverse associations with quitting smoking: former smokers who had quit smoking for 25 years or longer had a 20% lower risk of cataract extraction than did current smokers, although the risk among former smokers, especially those who had smoked 2 or more packs per day, was not at the level of never smokers. These findings underscore the importance of never smoking or quitting early. On the basis of these and other confirmatory studies,9 the US surgeon general’s report on the health effects of smoking added cataracts as the first ocular condition related to smoking.10 Because approximately 20% of US cataract cases may be attributable to smoking,9 cigarette smoking is an important modifiable factor for cataract prevention.

Antioxidant Intake

Antioxidants, such as vitamins C and E, are natural defenses against oxidative stress. Early small retrospective studies of cataract found associations with dietary antioxidants.8 Vitamin C is present in the lens at more than 50 times the concentration found in plasma,8 and in the NHS, vitamin C supplement use for 10 years or longer, especially among never smokers and women younger than 60 years, was associated with a 20% to 30% lower risk of cataract extraction. We found that those with the highest vitamin C intake or vitamin C supplement use for 10 years or longer, especially if younger than 60 years, were least likely to show lens opacities, particularly nuclear and cortical cataract. Similar results were observed with vitamin E; plasma levels of vitamins C and E were inversely associated with nuclear opacities.

In a related finding, lower odds of nuclear opacities were observed with greater fruit intake. Another contribution of the NHS was the evaluation of carotenoids and cataract. High intake of total vitamin A, lutein or zeaxanthin, and foods rich in lutein or zeaxanthin (e.g., spinach and kale) were associated with a 20% to 30% lower risk of cataract extraction. Similarly, in relation to posterior subcapsular opacities, we observed that higher total lutein or zeaxanthin was associated with lower risk, as were higher plasma carotenoids and carotenoid intakes among never smokers only. These findings from the NHS, bolstered by numerous other studies,9 have provided the motivation for multiple randomized trials in cataract prevention. Although the 10 or more randomized trials of specific vitamin supplements have not shown convincing protective effects,8,11 the National Eye Institute includes eating “green leafy vegetables, fruit, and other foods with antioxidants” as a factor that may protect against age-related cataract.12

Diabetes, Obesity, Carbohydrate Intake, and Other Dietary Factors

Several other aspects of nutrition have been evaluated in the NHS. A major focus has been on exposures related to obesity and type 2 diabetes mellitus. With type 2 diabetes, high levels of sorbitol (a sugar derived from glucose) accumulate in the lens, causing osmotic stress and cataract formation, particularly the posterior subcapsular subtype.13 In the NHS, a 4.0 times and 2.5 times increased odds of posterior subcapsular opacity were observed with type 2 diabetes or high fasting glucose and obesity, respectively. For cataract extraction, a 36% increased risk was observed with obesity that was driven mainly by posterior subcapsular cataracts.

These and other studies14 support the importance of maintaining a healthy weight and of a healthy diet that helps prevent type 2 diabetes. Consistent with this, we observed lower odds of lens opacities with adherence to an overall healthy diet or components that may help lower diabetes risk. Considering that by 2030 more than 50% of US adults might be obese15 and are at risk for type 2 diabetes, it is imperative to promote a healthy diet and lifestyle and an awareness that obesity and type 2 diabetes carry risks of vision problems.

AGE-RELATED MACULAR DEGENERATION

Age-related macular degeneration (AMD) is a chronic retinal disease and a leading cause of vision impairment in developed countries.3 The US prevalence of AMD is approximately 6.5% among those aged 40 years or older and more than 15% among those aged 85 years or older,16 and it is projected to grow rapidly and globally.

Among classification systems for AMD, the one proposed by the Age-Related Eye Disease (AREDS) trial17 has been increasingly used clinically and epidemiologically. Briefly, early and intermediate stages of AMD are characterized by the accumulation of drusen (yellow deposits under the retina) and abnormalities of the retinal pigment epithelium and the possible development of noncentral geographic atrophy. The advanced stages of AMD are characterized by subretinal neovascularization or central geographic atrophy and are associated with a greater risk of nonreversible vision loss. In the NHS, a physician diagnosis of AMD is self-reported by participants and confirmed by medical record.

A similar classification scheme to that of AREDS was used, but another required criterion was added to reduce the possibility of detection bias among early asymptomatic cases: visual acuity loss of 20/30 or worse attributable to AMD (except for those with advanced AMD and documentation of treatment with anti–vascular endothelial growth factor therapy). The NHS case definition has been validated by comparison with retinal images and medical records. Also, in several hundred NHS participants aged 50 years or older who completed eye examinations in Boston, we determined the presence and degree of age-related maculopathy using the AREDS classification scheme.

Smoking

Age, family history, and smoking are the most consistent risk factors for AMD.16 In the NHS, we observed that smoking was significantly related to AMD risk (current smokers of 20 or more cigarettes per day had a 2 times increased risk) with a dose–response relationship for the number of pack-years smoked. Even 15 years after smoking cessation, past smokers who previously smoked 25 or more cigarettes per day had double the risk of AMD, indicating that any reduction of risk from smoking cessation may take several decades.

This finding was corroborated by other large studies.18 On the basis of these consistent findings, AMD was added to the 2014 surgeon general’s report on the consequences of smoking.19

Antioxidants (Carotenoids)

Lutein and zeaxanthin are carotenoids found in high concentration in the macula. In the first National Health and Nutrition Examination Survey,20 higher intakes of fruits and vegetables were inversely correlated with AMD prevalence, and the Eye Disease Case–Control Dietary Ancillary Study21 found that high intake of carotenoids, specifically lutein or zeaxanthin (6 mg/day), was associated with a 43% lower risk of advanced neovascular AMD. Our data from the NHS strengthened the body of evidence for the role of antioxidants: the highest intakes of fruits and lutein or zeaxanthin were associated with an approximately 25% to 35% lower risk of neovascular AMD.

With extended follow-up, we observed that the association with lutein or zeaxanthin persisted with an even stronger inverse association with advanced AMD. Indeed, in AREDS, a randomized clinical trial, supplementation with antioxidant vitamins (C, E, and beta-carotene) and minerals (zinc and copper) led to an approximately 25% reduction in the risk of progression from intermediate to advanced AMD over 5 years.22 A secondary analysis of AREDS2 showed an additional 10% risk reduction when beta-carotene in the original AREDS formula was replaced with lutein or zeaxanthin.23 With the NHS data, we have also advanced the understanding of the role of other nutrients, including other antioxidants, omega-3 fats, alcohol, and zinc, on AMD; in particular, we observed that consuming foods with a higher glycemic index was strongly associated with AMD.

Genetics

There has been strong evidence for a genetic predisposition in AMD. The NHS has contributed to large genome-wide association studies through participation in the International AMD Genomics Consortium.24 The largest genome-wide association studies (including the NHS) with more than 17 000 AMD cases revealed 19 susceptibility genes that collectively explained more than 50% of the risk of AMD.24 Other genetic variants, such as those in or near CX3CR1, ROBO1, and RORA, and genes involved in vitamin D metabolism have been examined in relation to AMD.

A person’s AMD risk is most likely determined by interactions between genetic and environmental factors. Results from studies that included the NHS and results from other studies suggested that lifestyle factors such as smoking and obesity may multiply the risks associated with the 2 major genetic variants in CFH and ARMS2.

Biomarkers

Genetic studies shed light on underlying biological pathways implicated in AMD pathogenesis, including regulation of complement activity, lipid metabolism, extracellular matrix remodeling, and angiogenesis.24 Research has yielded promising findings regarding biomarkers involved in those pathways and AMD risk.25 Among those factors, C-reactive protein, a biomarker of systemic inflammation, was positively associated with AMD risk in a pooled analysis including the NHS. The utility of those biomarkers in predicting AMD are still controversial, and more studies are needed; yet the unique availability of prediagnostic blood collected in more than 30 000 NHS participants will allow the future evaluation of promising AMD biomarkers.

Research from the NHS, combined with other studies, over the past several decades has enabled remarkable progress in the understanding of this multifactorial disease and has helped develop some measures of prevention and treatment of AMD.

PRIMARY OPEN-ANGLE GLAUCOMA

Glaucoma is the leading cause of irreversible blindness worldwide.26 POAG is the most common type; it is painless and causes progressive vision loss, usually from the peripheral visual field and the central visual field in advanced stages. The established risk factors are age, family history, African heritage, and elevated intraocular pressure (IOP); of these, IOP is the only modifiable factor.26

In the NHS, POAG was defined as self-report of glaucoma confirmed with information from eye care providers showing open angles with no identifiable secondary cause of elevated IOP and reproducible glaucomatous visual field loss on standardized tests. Only those aged 40 years or older and reporting eye examinations were eligible (to minimize detection bias).

Type 2 Diabetes Mellitus

Type 2 diabetes may elevate IOP.27 However, the type 2 diabetes–POAG relation had been controversial and mainly determined by cross-sectional studies. In the NHS, we observed that type 2 diabetes was associated with an 82% higher POAG risk.

This association has been replicated in other studies,28 and 1 study found that type 2 diabetes–related genetic variants were associated with POAG.29 This further underscores the importance of type 2 diabetes primary prevention and more frequent eye examinations in patients with diabetes.

Body Mass Index

Higher body mass index is related to higher IOP,27 yet the relation with POAG was unclear. In the NHS and the HPFS, we observed that higher body mass index was associated with a lower risk of normal-tension POAG (IOP < 22 mmHg), especially in women, and this has been confirmed in other studies.30

These findings support a novel hypothesis that higher intracranial pressure, which is linked to higher body mass index, may protect against optic nerve damage.31

Diet

Although oxidative stress has been hypothesized to increase IOP,32 little was known about antioxidant intake in relation to POAG. In the NHS and the HPFS, we observed no relations with cigarette smoking, a major oxidative exposure, or with consumption of antioxidants or fats.

However, we observed that a high consumption of dietary nitrate, an exogenous source of nitric oxide (a potent vasodilator)33 or green leafy vegetables rich in nitrate was associated with an approximately 20% lower risk of POAG, particularly POAG with early paracentral visual field loss. This was consistent with findings from other cross-sectional studies of various vegetables and POAG.34

Sex Hormones in Women

Estrogen may be neuroprotective,35 lower IOP, and enhance ocular blood flow.36 In the NHS, we observed that among postmenopausal women aged 65 years or older, entering menopause at aged 54 years or older versus 50 to 54 years was associated with a 47% lower POAG risk, and current estrogen plus progesterone use (vs no hormone use) was associated with a 42% lower risk of high-tension POAG (IOP > 21 mmHg).

We also observed that genes involved in estrogen metabolism were collectively associated with POAG, and we observed a gene–environment interaction involving the use of postmenopausal hormone therapy and NOS3 (the gene coding for nitric oxide synthase 3) for POAG.

Genetics

The NHS has contributed to various large POAG consortia to help confirm and discover novel genetic variants of POAG37 and various related quantitative traits (e.g., IOP, central cornea thickness that determines IOP, and optic disc parameters). The genome-wide association studies findings supported the associations with genetic variants in or near the genes of CDKN2BAS, CAV1/CAV2, TMCO1, a regulatory region on 8q22, GAS7, and ATOH7 and contributed to the identification of novel loci: those in or near SIX1/SIX6, ABCA1, GMDS, AFAP1, TXNRD2, ATXN2, and FOXC1.

Overall, the NHS has allowed unprecedented large prospective analyses on dietary and lifestyle factors and has allowed collaborations to explore genetic risk factors in relation to POAG.

EXFOLIATION GLAUCOMA

Exfoliation syndrome (XFS) is a systemic condition in which grayish white material (exfoliation material) accumulates in various tissues. In the eye, XFS is associated with elevated IOP, and it is the most common cause of secondary glaucoma (exfoliation glaucoma [XFG]).38

To investigate XFS in the NHS, we used a definition of a self-report of glaucoma confirmed by medical records documenting ocular exfoliation material with the presence of any glaucomatous sign (elevated IOP, large cup to disk ratio or visual field loss). Among eligible participants, we excluded those with cataract extractions because exfoliation material is difficult to diagnose when lenses are removed.

Genetics

Age and family history are strongly related to XFS, and XFS is hyperendemic in certain regions (e.g., Scandinavia).39 A major XFS genetic discovery was LOXL1 (coding for lysyl oxidase-like 1 protein, which is involved in elastogenesis).40

One LOXL1 polymorphism was present in more than 98% of cases, with an effect size of greater than 20. However, 88% of controls also had this polymorphism; also, there is no correlation between LOXL1 polymorphism frequencies and XFS prevalence, implicating other genetic and nongenetic factors. The NHS is participating in a large consortium that will explore other genetic risk factors.

Latitude of Residence and Time Spent Outdoors

Prevalence studies of XFS suggested that XFS occurred predominantly in regions farthest from the equator. We used the residential data available from birth to the present among the NHS and HPFS participants and observed that compared with currently living at higher than 40° latitude N, living in the southern United States (< 37° latitude N) was associated with a 49% lower XFG risk. When residences of different ages were evaluated, southern residence at aged 15 years was independently associated with a 60% lower risk. This finding, replicated in other studies, combined with the fact that Scandinavian heritage was not associated with XFG in the NHS and the HPFS, strongly indicates environmental factors as causal influences for XFS and XFG.

XFG is associated with various solar-related ophthalmic conditions, living in states with more sunny days, and being from rural areas.41 We evaluated the relation between self-reported time spent outdoors and XFG in the NHS and the HPFS. Consistent with residence at age 15 years being associated with XFG, a 2 times higher risk was observed with spending 11 or more hours versus 5 or fewer hours outdoors per week from high school to age 24 years; the highest risks were found among those spending the most time outdoors in northern latitudes. Thus, the findings suggest that the public health recommendations42 for sun protection in children that include promoting sunglass use outdoors may also be important for XFG prevention.

Homocysteine-Related Dietary Factors

Homocysteine, which has been consistently elevated in XFS,43 could alter the methylation patterns of key genetic loci44 and contribute to XFS. In the first prospective studies of homocysteine-related exposures, we observed in the NHS and the HPFS that high coffee consumption (related to higher homocysteine) was associated with a 63% increased risk, and we observed that those in the highest quintile had a suggestive 25% reduced risk of XFG, supporting the role of homocysteine-lowering nutritional factors in modulating XFG risk.

Overall, work from the NHS has transformed the view of XFS from a mainly genetics-centered to a multifactorial disease perspective, opening avenues of research into possible primary prevention strategies.

CONCLUSIONS

Although promoting regular eye examinations is at the frontline of preventing vision loss, the World Health Organization cites the reduction of modifiable risk factors for age-related eye diseases as being key in primary prevention efforts to reduce vision loss.45 The findings from more than 50 published studies using NHS data of eye diseases have made major contributions that, combined with those from other studies, provide compelling evidence to support public health recommendations for helping to prevent age-related eye diseases: abstinence from cigarette smoking, maintenance of healthy weight and diabetes prevention, and eating a healthy diet rich in fruits and vegetables (Table 1).

TABLE 1—

Summary of Major Modifiable Factors for Age-Related Eye Diseases Supported by the Nurses’ Health Studies: United States, 1976–2016

Protective Factor Cataract and Lens Opacities Age-Related Macular Degeneration Primary Open-Angle Glaucoma Exfoliation Glaucoma
Abstinence or cessation of cigarette smoking X X
Maintaining healthy weight and healthy diet and lifestyle to prevent diabetes X X X
Healthy diet high in fruits and vegetables, carotenoids, and folate X X X X
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A critical factor in the success of the study of eye diseases in the NHS was the exceptional long-term dedication of a large number of nurse participants who provided accurate updated responses to questionnaires and even biospecimens. Future work in the NHS will incorporate data from the NHS II (a similar cohort of younger nurses) and studies of biomarkers and metabolomics.

ACKNOWLEDGMENTS

This work was supported by the National Institutes of Health and the Arthur Ashley Foundation (grants UM1 CA186107; UM1 CA167552; EY09611; EY015473 to L. R. P.; and R21 EY022766, R01 EY020928, and R01 EY022305 to J. L. W); a Harvard Medical Distinguished Ophthalmology Scholar award (to L. R. P.); and JSPS KAKENHI (grant 15J03698 to S. O.). L. R. P. and J. L. W. were also supported by the Harvard Glaucoma Center of Excellence.

HUMAN PARTICIPANT PROTECTION

No protocol approval was necessary because no human participants were involved in this study.

REFERENCES

  • 1.Saaddine JB, Narayan KM, Vinicor F. Vision loss: a public health problem. Ophthalmology. 2003;110(2):253–254. doi: 10.1016/s0161-6420(02)01839-0. [DOI] [PubMed] [Google Scholar]
  • 2.Vincent GK, Velkoff VA. The Next Four Decades. The Older Population in the United States: 2010 to 2050—Population Estimates and Projections. Washington, DC: US Census Bureau; 2010. [Google Scholar]
  • 3.Congdon N, O’Colmain B, Klaver CC et al. Causes and prevalence of visual impairment among adults in the United States. Arch Ophthalmol. 2004;122(4):477–485. doi: 10.1001/archopht.122.4.477. [DOI] [PubMed] [Google Scholar]
  • 4.Rein DB. Vision problems are a leading source of modifiable health expenditures. Invest Ophthalmol Vis Sci. 2013;54(14):ORSF18–22. doi: 10.1167/iovs.13-12818. [DOI] [PubMed] [Google Scholar]
  • 5.Rothman KJ, Greenland S. Modern Epidemiology. 2nd ed. Philadelphia, PA: Lippincott-Raven; 1998. [Google Scholar]
  • 6.Tielsch JM, Sommer A, Katz J, Royall RM, Quigley HA, Javitt J. Racial variations in the prevalence of primary open-angle glaucoma. JAMA. 1991;266(3):369–374. [PubMed] [Google Scholar]
  • 7.Pascolini D, Mariotti SP. Global estimates of visual impairment: 2010. Br J Ophthalmol. 2012;96(5):614–618. doi: 10.1136/bjophthalmol-2011-300539. [DOI] [PubMed] [Google Scholar]
  • 8.Weikel KA, Garber C, Baburins A, Taylor A. Nutritional modulation of cataract. Nutr Rev. 2014;72(1):30–47. doi: 10.1111/nure.12077. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.West S. Epidemiology of cataract: accomplishments over 25 years and future directions. Ophthalmic Epidemiol. 2007;14(4):173–178. doi: 10.1080/09286580701423151. [DOI] [PubMed] [Google Scholar]
  • 10.US Department of Health and Human Services. 2004 Surgeon General’s Report: The Health Consequences of Smoking. Washington, DC: US Government Printing Office; 2004. [Google Scholar]
  • 11.Mathew MC, Ervin AM, Tao J, Davis RM. Antioxidant vitamin supplementation for preventing and slowing the progression of age-related cataract. Cochrane Database Syst Rev. 2012;6:CD004567. doi: 10.1002/14651858.CD004567.pub2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.National Eye Institute. Facts about cataract. 2015. Available at: https://nei.nih.gov/health/cataract/cataract_facts. Accessed February 1, 2016.
  • 13.Biswas S, Harris F, Singh J, Phoenix D. Role of calpains in diabetes mellitus–induced cataractogenesis: a mini review. Mol Cell Biochem. 2004;261(1–2):151–159. doi: 10.1023/b:mcbi.0000028750.78760.6f. [DOI] [PubMed] [Google Scholar]
  • 14.Ye J, Lou LX, He JJ, Xu YF. Body mass index and risk of age-related cataract: a meta-analysis of prospective cohort studies. PLoS One. 2014;9(2):e89923. doi: 10.1371/journal.pone.0089923. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Levi J, Segal LM, St Laurent R . F as in Fat: How Obesity Threatens America’s Future. Washington, DC: Trust for America’s Health; 2012. [Google Scholar]
  • 16.Klein R, Peto T, Bird A, Vannewkirk MR. The epidemiology of age-related macular degeneration. Am J Ophthalmol. 2004;137(3):486–495. doi: 10.1016/j.ajo.2003.11.069. [DOI] [PubMed] [Google Scholar]
  • 17.Age-Related Eye Disease Study Research Group. Risk factors associated with age-related macular degeneration. A case–control study in the Age-Related Eye Disease Study: Age-Related Eye Disease Study report number 3. Ophthalmology. 2000;107(12):2224–2232. doi: 10.1016/s0161-6420(00)00409-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Christen WG, Glynn RJ, Manson JE, Ajani UA, Buring JE. A prospective study of cigarette smoking and risk of age-related macular degeneration in men. JAMA. 1996;276(14):1147–1151. [PubMed] [Google Scholar]
  • 19.US Department of Health and Human Services. Let’s Make the Next Generation Tobacco-Free. Your Guide to the 50th Anniversary Surgeon General’s Report on Smoking and Health. Washington, DC: US Government Printing Office; 2014. [Google Scholar]
  • 20.Goldberg J, Flowerdew G, Smith E, Brody JA, Tso MO. Factors associated with age-related macular degeneration. An analysis of data from the first National Health and Nutrition Examination Survey. Am J Epidemiol. 1988;128(4):700–710. doi: 10.1093/oxfordjournals.aje.a115023. [DOI] [PubMed] [Google Scholar]
  • 21.Seddon JM, Ajani UA, Sperduto RD et al. Dietary carotenoids, vitamins A, C, and E, and advanced age-related macular degeneration. Eye Disease Case–Control Study Group. JAMA. 1994;272(18):1413–1420. [PubMed] [Google Scholar]
  • 22.Age-Related Eye Disease Study Research Group. A randomized, placebo-controlled, clinical trial of high-dose supplementation with vitamins C and E, beta carotene, and zinc for age-related macular degeneration and vision loss: AREDS report no. 8. Arch Ophthalmol. 2001;119(10):1417–1436. doi: 10.1001/archopht.119.10.1417. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Chew EY, Clemons TE, Sangiovanni JP et al. Secondary analyses of the effects of lutein or zeaxanthin on age-related macular degeneration progression: AREDS2 report no. 3. JAMA Ophthalmol. 2014;132(2):142–149. doi: 10.1001/jamaophthalmol.2013.7376. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Fritsche LG, Chen W, Schu M et al. Seven new loci associated with age-related macular degeneration. Nat Genet. 2013;45(4):433–439. doi: 10.1038/ng.2578. 439e1–e2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Ross RJ, Verma V, Rosenberg KI, Chan CC, Tuo J. Genetic markers and biomarkers for age-related macular degeneration. Expert Rev Ophthalmol. 2007;2(3):443–457. doi: 10.1586/17469899.2.3.443. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Quigley HA. Glaucoma. Lancet. 2011;377(9774):1367–1377. doi: 10.1016/S0140-6736(10)61423-7. [DOI] [PubMed] [Google Scholar]
  • 27.Wu S-Y, Leske MC. Associations with intraocular pressure in the Barbados Eye Study. Arch Ophthalmol. 1997;115(12):1572–1576. doi: 10.1001/archopht.1997.01100160742012. [DOI] [PubMed] [Google Scholar]
  • 28.Zhou M, Wang W, Huang W, Zhang X. Diabetes mellitus as a risk factor for open-angle glaucoma: a systematic review and meta-analysis. PLoS One. 2014;9(8):e102972. doi: 10.1371/journal.pone.0102972. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Shen L, Walter S, Melles RB, Glymour MM, Jorgenson E. Diabetes pathology and risk of primary open-angle glaucoma: evaluating causal mechanisms by using genetic information. Am J Epidemiol. 2015;183(2):147–155. doi: 10.1093/aje/kwv204. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Ramdas WD, Wolfs RC, Hofman A, de Jong PT, Vingerling JR, Jansonius NM. Lifestyle and risk of developing open-angle glaucoma: the Rotterdam Study. Arch Ophthalmol. 2011;129(6):767–772. doi: 10.1001/archophthalmol.2010.373. [DOI] [PubMed] [Google Scholar]
  • 31.Berdahl JP, Allingham RR, Johnson DH. Cerebrospinal fluid pressure is decreased in primary open-angle glaucoma. Ophthalmology. 2008;115(5):763–768. doi: 10.1016/j.ophtha.2008.01.013. [DOI] [PubMed] [Google Scholar]
  • 32.Maneesh Kumar DM, Agarwal N. Oxidative stress in glaucoma: a burden of evidence. J Glaucoma. 2007;16(3):334–343. doi: 10.1097/01.ijg.0000243480.67532.1b. [DOI] [PubMed] [Google Scholar]
  • 33.Lundberg JO, Weitzberg E, Gladwin MT. The nitrate-nitrite-nitric oxide pathway in physiology and therapeutics. Nat Rev Drug Discov. 2008;7(2):156–167. doi: 10.1038/nrd2466. [DOI] [PubMed] [Google Scholar]
  • 34.Coleman AL, Stone KL, Kodjebacheva G et al. Glaucoma risk and the consumption of fruits and vegetables among older women in the study of osteoporotic fractures. Am J Ophthalmol. 2008;145(6):1081–1089. doi: 10.1016/j.ajo.2008.01.022. [DOI] [PubMed] [Google Scholar]
  • 35.Nakazawa T, Takahashi H, Shimura M. Estrogen has a neuroprotective effect on axotomized RGCs through ERK signal transduction pathway. Brain Res. 2006;1093(1):141–149. doi: 10.1016/j.brainres.2006.03.084. [DOI] [PubMed] [Google Scholar]
  • 36.Altintaş O, Caglar Y, Yuksel N, Demirci A, Karabas L. The effects of menopause and hormone replacement therapy on quality and quantity of tear, intraocular pressure and ocular blood flow. Ophthalmologica. 2004;218(2):120–129. doi: 10.1159/000076148. [DOI] [PubMed] [Google Scholar]
  • 37.Bailey JN, Loomis SJ, Kang JH et al. Genome-wide association analysis identifies TXNRD2, ATXN2 and FOXC1 as susceptibility loci for primary open-angle glaucoma. Nat Genet. 2016;48(2):189–194. doi: 10.1038/ng.3482. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Naumann GO, Schlotzer-Schrehardt U, Kuchle M. Pseudoexfoliation syndrome for the comprehensive ophthalmologist. Intraocular and systemic manifestations. Ophthalmology. 1998;105(6):951–968. doi: 10.1016/S0161-6420(98)96020-1. [DOI] [PubMed] [Google Scholar]
  • 39.Åström S, Linden C. Incidence and prevalence of pseudoexfoliation and open-angle glaucoma in northern Sweden: I. Baseline report. Acta Ophthalmol Scand. 2007;85(8):828–831. doi: 10.1111/j.1600-0420.2007.00992.x. [DOI] [PubMed] [Google Scholar]
  • 40.Thorleifsson G, Magnusson KP, Sulem P et al. Common sequence variants in the LOXL1 gene confer susceptibility to exfoliation glaucoma. Science. 2007;317(5843):1397–1400. doi: 10.1126/science.1146554. [DOI] [PubMed] [Google Scholar]
  • 41.Taylor HR. The prevalence of corneal disease and cataracts in Australian aborigines in northwestern Australia. Aust J Ophthalmol. 1980;8(4):289–301. doi: 10.1111/j.1442-9071.1980.tb00285.x. [DOI] [PubMed] [Google Scholar]
  • 42.Division of Cancer Prevention; Control of Centers for Disease Control and Prevention. How can I protect my children from the sun. Available at: http://www.cdc.gov/cancer/skin/basic_info/children.htm. Accessed February 1, 2016.
  • 43.Xu F, Zhang L, Li M. Plasma homocysteine, serum folic acid, serum vitamin B12, serum vitamin B6, MTHFR and risk of pseudoexfoliation glaucoma: a meta-analysis. Graefes Arch Clin Exp Ophthalmol. 2012;250(7):1067–1074. doi: 10.1007/s00417-011-1877-4. [DOI] [PubMed] [Google Scholar]
  • 44.Park LK, Friso S, Choi SW. Nutritional influences on epigenetics and age-related disease. Proc Nutr Soc. 2012;71(1):75–83. doi: 10.1017/S0029665111003302. [DOI] [PubMed] [Google Scholar]
  • 45.World Health Organization. Universal eye health: a global action plan 2014–2019. 2013. Available at: http://www.who.int/blindness/AP2014_19_English.pdf?ua=1. Accessed June 22, 2016.

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