Abstract
Purpose
This study aimed to investigate the association between folate levels and the prevalence of glaucoma.
Methods
This nationwide population-based cross-sectional study included 1790 participants aged ≥40 years. We analyzed data regarding the participants obtained in the 2016–2018 Korean National Health and Nutrition Examination Survey. The diagnosis of glaucoma was defined according to the International Society of Geographical and Epidemiological Ophthalmology criteria. Logistic regression analyses were used to investigate the relationship between blood folate levels and glaucoma.
Results
There was a significantly lower prevalence of glaucoma in the highest quartile of blood folate levels than in the lowest quartile, after adjusting for confounding factors such as age, sex, systemic hypertension, diabetes, hypercholesterolemia, and smoking (odds ratio [OR] = 0.470; 95% confidence interval [CI], 0.291–0.759; P for trend = 0.017). There was a significantly lower risk of glaucoma in the highest quartile of blood folate levels than in the lowest quartile among women (OR = 0.188; 95% CI, 0.099–0.357; P for trend <0.001) and younger participants (OR =0.443; 95% CI, 0.229-0.856; P for trend = 0.045).
Conclusions
Our findings indicate a strong inverse correlation between blood folate levels and glaucoma.
Keywords: folate, glaucoma, sex differences, korea
Glaucoma refers to a group of progressive optic neuropathies characterized by damage of retinal ganglion cells (RGCs) and their axons, leading to irreversible vision loss.1 Glaucoma is expected to cause bilateral blindness in approximately 11.1 million people, suggesting that glaucoma will be responsible for 12% of blindness cases worldwide.2,3 The major risk factors for glaucoma include intraocular pressure (IOP) elevation, older age, high myopia, and family history of glaucoma.4,5 Other potential risk factors for glaucoma include systemic hypertension, cardiovascular illness, migraine, and peripheral vasospasm.1 Patients with glaucoma present progressive visual impairment despite appropriate IOP lowering treatment, including surgical therapy.6 Recently, vitamin B intake has been reported to be related with a low prevalence of glaucoma.7 Moreover, nicotinamide (vitamin B3) has been shown to reduce oxidative stress, improve mitochondrial motility, exert strong neuroprotective effects, and improve visual function in patients with glaucoma.8,9
Folate, which is also known as vitamin B9, is crucially involved in thymidine and methionine synthesis; trans-sulfuration; and methylation of different molecules such as nucleic acid, neurotransmitters, phospholipid, and homocysteine.10 Folate has been suggested to reduce cardiovascular events, cancer, and neural tube defects; furthermore, folate deficiency is associated with hyperhomocysteinemia and coronary artery disease.10–13 Folate supplementation reduces the risk of age-related macular degeneration14; moreover, low plasma folate levels are associated with the development of central retinal vein occlusion.15 This may be related to the crucial role of folate in DNA methylation, synthesis, and repair10; however, the underlying biologic mechanisms remain unclear. Previous studies have reported an association of folate with hyperhomocysteinemia and glaucoma.16–18 However, there have been no epidemiologic studies on the association between folate levels and glaucoma. Therefore we aimed to investigate the association between blood folate levels and glaucoma in a large representative population of Korean adults.
Methods
This study used data obtained through the Korean National Health and Nutrition Examination Survey (KNHANES). The KNHANES is a complex, stratified, multistage, probability cluster sampling survey based on a rolling sampling design that proportionally allocates the National Census Registry of the non-institutional civilian population of Korea. Further, the KNHANES represents a series of cross-sectional national, population-based studies conducted by the Korean Ministry of Health and Welfare and the Division of Chronic Disease Surveillance, Korean Center for Disease Control and Prevention. The set of the study design and methods have been previously described.19,20
We used data from the 2016–2018 KNHANES to analyze the relationship between blood folate levels and glaucoma. Among 20,180 participants, we excluded 8453 participants aged <40 years and 7880 participants who did not undergo examinations for glaucoma. Among the remaining 3847 participants who underwent glaucoma examination, we excluded 2057 participants who did not undergo tests for blood folate levels. Finally, we included 1790 participants aged ≥40 years (Figure). This study was approved by the Institutional Review Board of the Catholic University of Korea and adhered to the tenets of the Declaration of Helsinki. All participants signed and provided written informed consent.
Figure.
Flow diagram presenting the selection of study participants.
Data Collection
Glaucoma was diagnosed based on the International Society of Geographical and Epidemiological Ophthalmology criteria using non-mydriatic fundus photographs and visual field examination.21,22 All participants underwent automated visual field examination using the Frequency Doubling Technology, N30-5 screening, and Humphrey Matrix (Carl Zeiss Meditec, Dublin, CA, USA) following standard procedures. Furthermore, only reliable results of visual function tests (≤1 fixation losses and false-positive responses) in the analysis. As previously described, the specific diagnostic criteria for glaucoma were as follows23: presence of glaucomatous structural damage (thinning of the neuroretinal rim, notching, asymmetry of the cup-to-disc ratio ≥ 0.3, vertical cup-to-disc ratio ≥ 0.7, or retinal nerve fiber layer [RNFL] defect), a glaucomatous visual field defect corresponding to the optic nerve head or abnormality of the RNFL, and normal anterior chamber angle. In case there were no reliable results of visual field examination and fundus imaging because of advanced glaucoma or media opacity, the diagnosis of glaucoma was established based on visual acuity (VA), IOP, and a history of glaucoma (glaucoma surgery, anti-glaucoma drug therapy, and diagnosis). Specifically, the diagnostic criteria were as follows23: corrected VA ≤10/200, IOP > 97.5th percentile, and a history of glaucoma. Cirrus HD-OCT (Carl Zeiss Meditec) was used as the reference to help confirm the diagnosis of glaucoma.
The diagnosis of diabetes was established using the following criteria: a history of self-reported physician-based diagnosis; having received medication for diabetes, including insulin or oral hypoglycemic agents; or a fasting plasma glucose level >126 mg/dL.24 Prediabetes was indicated by a fasting plasma glucose level of 100 to 125 mg/dL.24
Body mass index was calculated as body weight (kg) divided by squared height (m)2. Regarding smoking, participants were classified as current, former, and never smokers. The age of the participants was stratified by 10 years. Hypercholesterolemia was indicated by a total cholesterol level ≥240 md/dL or taking cholesterol-lowering medication.25 Hypertriglycemia was indicated by triglyceride levels >150 mg/dL.26
Blood pressure (BP) was measured three times at five-minute intervals with the participant in a sitting position. The mean of the second and third BP values was included in the analysis. Hypertension was indicated by a systolic blood pressure (SBP) ≥ 140 mmHg, a diastolic blood pressure ≥ 90 mm Hg, or taking antihypertensive medications. Prehypertension was indicated by a SBP of 120 to 139 mm Hg or a diastolic blood pressure of 80 to 89 mm Hg.25 Demographic information was administered by health interviews.
Statistical Analysis
The characteristics of the participants were compared according to the presence or absence of glaucoma. Continuous variables are presented as means and standard errors while categorical variables are presented as percentages and standard errors. Categorical variables were analyzed using the χ2 test.
Blood folate levels were classified into quartiles to analyze the relationship between blood folate levels and the incidence of glaucoma.11 Simple and multiple logistic regression analyses were used to analyze the relationship between blood folate levels and the incidence of glaucoma. In logistic regression model, we first adjusted for sex and age (Model 1). Subsequently, we adjusted for age, sex, diabetes, hypertension, hypercholesterolemia, and smoking, which have been reported as risk factors for glaucoma (Model 2).5,27 For trend analysis, the folate level quartile was applied as a continuous variable to analyze the change in the odds ratio (ORs) across the quartile categories of folate levels. Multicollinearity was investigated for all variables in the logistic regression analysis; subsequently, only variables with a variance inflation factor <10 were used. All statistical analyses were performed using SPSS statistical software (ver. 18.0; SPSS, Inc., Chicago, IL, USA) and Strata. Statistical significance was set at P < 0.05.
Results
Glaucoma was diagnosed in 67 (3.74%) out of the 1790 eligible participants who underwent tests for blood folate levels. The demographic characteristics of participants with and without glaucoma are summarized in Table 1. Compared with patients without glaucoma, patients with glaucoma showed older age (P < 0.001), higher hemoglobin A1c levels (P < 0.001), lower total cholesterol levels (P < 0.001), and higher SBP (P < 0.001). Additionally, there were significant between-group differences in the incidence of systemic diseases, including diabetes, systemic hypertension, and hypercholesterolemia (P < 0.001, P < 0.001, and P = 0.023, respectively). The baseline characteristics of the quartiles are listed in Table 2. Table 3 presents the mean folate levels for each quartile according to the presence of glaucoma.
Table 1.
Demographic and Clinical Characteristics, According to glaucoma, as Reported in the Korean National Health and Nutrition Examination Survey 2016-2018
| Characteristics | No Glaucoma (n = 1723) | Glaucoma (n = 67) | P | Participants (n = 1790) |
|---|---|---|---|---|
| Male (%) | 43.88 (0.5) | 47.76 (0.3) | 0.530 | 44.02 |
| Age (yrs) | 57.02 (0.19) | 63.08 (0.45) | <0.001* | 60.05 (0.23) |
| Systolic blood pressure (mm Hg) | 120.17 (0.19) | 126.09 (0.74) | <0.001* | 120.13 (0.38) |
| Diastolic blood pressure (mm Hg) | 76.38 (0.13) | 76.23 (0.48) | 0.763* | 76.30 (0.26) |
| Fasting glucose (mg/dL) | 103.43 (0.23) | 106.30 (1.14) | 0.016* | 104.87 (0.58) |
| HbA1c (%) | 5.79 (0.01) | 5.94 (0.03) | <0.001* | 5.86 (0.16) |
| Total cholesterol (mg/dL) | 194.36 (0.46) | 187.56 (1.75) | <0.001* | 190.96 (0.92) |
| Triglyceride (mg/dL) | 145.30 (1.27) | 146.52 (4.10) | 0.780 | 145.91 (2.12) |
| Folate (ng/mL) | 7.94 (0.06) | 7.71 (0.26) | 0.364 | 7.82 (0.14) |
| Folate quartiles | <0.001* | |||
| Folate level < 5.10 (%) | 24.3 (0.7) | 27.9 (2.7) | 24.4 (0.7) | |
| Folate level 5.10–7.10 (%) | 25.7 (0.7) | 26.6 (4.1) | 25.7 (0.7) | |
| Folate level 7.10–10.00 (%) | 24.1 (0.8) | 27.9 (3.9) | 24.2 (0.8) | |
| Folate level > 10.00 (%) | 25.9 (0.8) | 17.5 (2.6) | 25.6 (0.8) | |
| Hypertension | <0.001* | |||
| Normal (%) | 37.4 (0.6) | 25.7 (1.7) | 36.9 (0.6) | |
| Pre hypertension (%) | 26.0 (0.4) | 25.5 (1.8) | 25.9 (0.4) | |
| Hypertension (%) | 36.6 (0.5) | 48.8 (1.9) | 37.1 (0.5) | |
| Diabetes | <0.001* | |||
| Normal (%) | 56.2 (0.5) | 42.7 (1.9) | 55.6 (0.5) | |
| Pre Diabetes (%) | 29.4 (0.5) | 37.6 (2.1) | 29.7 (0.5) | |
| Diabetes (%) | 14.5 (0.4) | 19.7 (1.4) | 14.7 (0.4) | |
| Smoking status | <0.001* | |||
| Never (%) | 56.1 (0.5) | 50.9 (1.8) | 55.9 (0.5) | |
| Former (%) | 25.4 (0.4) | 32.6 (1.9) | 25.7 (0.4) | |
| Current (%) | 18.5 (0.5) | 16.6 (1.5) | 18.4 (0.5) | |
| Body mass index (kg/m2) | 0.528 | |||
| Underweight <18.5 (%) | 2.5 (0.2) | 3.2 (0.9) | 2.5 (0.2) | |
| Normal weight 18.5–22.9 (%) | 36.6 (0.5) | 33.0 (1.6) | 36.4 (0.5) | |
| Pre-Obese 23.0–24.9 (%) | 25.2 (0.4) | 26.0 (2.0) | 25.2 (0.4) | |
| Obese I 25.0–29.9 (%) | 31.3 (0.4) | 33.6 (1.9) | 31.4 (0.4) | |
| Obese II 30.0–34.9 (%) | 4.1 (0.2) | 3.9 (0.8) | 4.1 (0.2) | |
| Obese III ≥35.0 (%) | 0.3 (0.1) | 0.2 (0.2) | 0.3 (0.1) | |
| Hypercholesterolemia (%) | 27.1 (0.5) | 30.8 (1.6) | 0.023* | 27.2 (0.4) |
| Hypertriglyceridemia (%) | 16.4 (0.4) | 17.0 (1.8) | 0.755 | 16.5 (0.4) |
Data are expressed as weighted means or weighted frequency (%) with standard errors.
P < 0.05.
Table 2.
Baseline Characteristics According to Quartile Categories of Blood Folate Level, as Reported in the Korean National Health and Nutrition Examination Survey 2016-2018
| Quartile Blood Folate Level (ng/mL) | |||||
|---|---|---|---|---|---|
| Quartile 1 | Quartile 2 | Quartile 3 | Quartile 4 | P for Trend | |
| Male | 77.0 (1.4) | 55.9 (1.5) | 43.9 (1.7) | 32.9 (1.1) | <0.001* |
| Age ≥ 60 years | 32.1 (1.9) | 27.9 (1.8) | 30.0 (1.4) | 36.8 (1.5) | <0.001* |
| Hypertension | 0.009* | ||||
| Normal | 31.7 (1.7) | 33.7 (1.5) | 39.1 (1.7) | 38.1 (1.5) | |
| Pre hypertension | 26.3 (2.1) | 29.4 (1.7) | 24.9 (1.2) | 25.3 (1.0) | |
| Hypertension | 42.0 (1.7) | 36.9 (1.5) | 35.9 (1.5) | 36.7 (1.3) | |
| Diabetes | 0.021* | ||||
| Normal | 52.5 (1.6) | 53.9 (1.7) | 54.3 (1.7) | 59.8 (1.4) | |
| Pre diabetes | 30.9 (1.4) | 31.3 (1.6) | 30.0 (1.5) | 26.1 (1.0) | |
| Diabetes | 16.6 (1.4) | 14.8 (1.1) | 15.7 (1.0) | 14.1 (1.0) | |
| Hypercholesterolemia | 23.4 (1.8) | 24.2 (1.1) | 24.9 (1.1) | 30.8 (1.1) | 0.001* |
| Smoking | <0.001* | ||||
| Never | 30.2 (1.9) | 49.4 (1.6) | 61.5 (1.6) | 71.1 (1.2) | |
| Former | 29.7 (1.5) | 27.9 (1.3) | 24.4 (1.3) | 19.8 (1.0) | |
| Current | 40.2 (2.0) | 22.7 (1.6) | 14.1 (1.1) | 9.1 (0.8) | |
Data are expressed as weighted frequency (%) with standard errors.
P < 0.05.
Table 3.
Distribution of Folate Levels by the Presence of Glaucoma
| Folate Levels (ng/mL) | No Glaucoma | Glaucoma | P | Total |
|---|---|---|---|---|
| Folate level < 5.10 (quartile 1) | 3.87 (0.04) | 3.73 (0.08) | 0.01 | 3.79 (0.12) |
| Folate level 5.10–7.10 (quartile 2) | 6.07 (0.02) | 6.28 (0.09) | 0.01 | 6.06 (0.01) |
| Folate level 7.10–10.00 (quartile 3) | 8.42 (0.03) | 8.84 (0.16) | 0.01 | 8.45 (0.02) |
| Folate level > 10.00 (quartile 4) | 13.15 (0.07) | 14.41 (0.36) | 0.01 | 12.86 (0.07) |
Data are expressed as weighted means with standard errors.
Table 4 presents the prevalence of glaucoma according to the quartiles categories of blood folate levels. The prevalence of glaucoma was negatively correlated with blood folate levels (P for trend = 0.045) even after adjusting for potential confounding factors (P for trend = 0.017).
Table 4.
Prevalence and Adjusted Odds Ratio of Glaucoma, Stratified According to Quartile Categories of Blood Folate Level Among Representative Korean Adults Aged 40 Years or Older
| Folate Level (ng/mL) | |||||
|---|---|---|---|---|---|
| <5.10 (n = 420) | 5.10–7.10 (n = 441) | 7.10–10.00 (n = 430) | >10.00 (n = 499) | P for Trend | |
| Glaucoma | |||||
| Prevalence* | 4.2 (0.5, 3.3–5.3) | 3.8 (0.6, 2.7–5.3) | 4.2 (0.8, 2.9–6.1) | 2.5 (0.4, 1.9–3.3) | 0.105 |
| Unweighted number | 20 | 16 | 16 | 15 | |
| OR | |||||
| 1.0 (reference) | 0.903 (0.588–1.386) | 1.009 (0.718–1.417) | 0.589 (0.407–0.851) | 0.045† | |
| Model 1 | 1.0 (reference) | 0.986 (0.626–1.551) | 1.008 (0.715–1.655) | 0.606 (0.391–0.938) | 0.053 |
| Model 2 | 1.0 (reference) | 0.811 (0.522–1.257) | 0.764 (0.477–1.223) | 0.470 (0.291–0.759) | 0.017† |
Model 1: adjusted for sex and age. Model 2: adjusted for sex, age, diabetes, systemic hypertension, hypercholesterolemia, and smoking.
Prevalence was expressed as weighted estimates [%] (standard errors [%], 95% confidence intervals).
P < 0.05.
Table 5 presents the prevalence of glaucoma in women and men according to the quartile categories of blood folate levels. The prevalence of glaucoma was negatively correlated with blood folate levels in women (P for trend < 0.001) but not men (P for trend = 0.491).
Table 5.
Gender Difference of Prevalence and Adjusted Odds Ratio of Glaucoma, Stratified According to Quartile Categories of Blood Folate Level Among Representative Korean Adults Aged 40 Years or Older
| Quartile Blood Folate Level (ng/mL) | |||||
|---|---|---|---|---|---|
| Quartile 1 | Quartile 2 | Quartile 3 | Quartile 4 | P for Trend | |
| Men | |||||
| Glaucoma Prevalence | 3.1 (0.1, 2.9–3.4) | 4.7 (1.0, 3.1–7.2) | 4.7 (1.8, 2.1–10.0) | 3.7 (0.9, 2.2–6.0) | 0.365 |
| Unweighted number | 11 | 10 | 5 | 6 | |
| OR | 1.0 (reference) | 1.310 (0.912–1.881) | 0.850 (0.402–1.797) | 1.004 (0.605–1.666) | 0.491 |
| Women | |||||
| Glaucoma prevalence | 7.1 (1.8, 4.2–11.7) | 2.5 (0.7, 1.5–4.2) | 3.9 (0.3, 3.4–4.6) | 1.9 (0.3, 1.5–2.5) | 0.167 |
| Unweighted number | 9 | 6 | 11 | 9 | |
| OR | 1.0 (reference) | 0.319 (0.144–0.707) | 0.503 (0.285–0.887) | 0.188 (0.099–0.357) | <0.001* |
Prevalence was expressed as weighted estimates [%] (standard errors [%], 95% confidence intervals).
P < 0.05
Table 6 presents the prevalence and ORs for glaucoma according to quartile categories of blood folate level, stratified by (age ≥ 60 years and < 60 years. There was a significant relationship of glaucoma with blood folate levels in participants aged < 60 years (OR = 0.443; 95% CI, 0.229–0.856).
Table 6.
Difference of Prevalence and Adjusted Odds Ratio of Glaucoma, Stratified According to Quartile Categories of Blood Folate Level Among Representative Korean Adults Aged Under 60 Years or Older
| Quartile Blood Folate Level (ng/mL) | |||||
|---|---|---|---|---|---|
| Quartile 1 | Quartile 2 | Quartile 3 | Quartile 4 | P for Trend | |
| Age < 60 years | |||||
| Glaucoma prevalence* | 3.2 (0.5, 2.4–4.3) | 2.9 (0.8, 1.7–4.9) | 2.7 (1.0, 1.3–5.5) | 1.5 (0.4, 0.9–2.4) | 0.691 |
| Unweighted number | 8 | 6 | 6 | 5 | |
| OR | 1.0 (reference) | 0.707 (0.385–1.297) | 0.471 (0.242–0.920) | 0.443 (0.229–0.856) | 0.045† |
| Age ≥ 60 years | |||||
| Glaucoma prevalence* | 6.4 (1.3, 4.3–9.4) | 6.5 (1.2, 4.5–9.2) | 8.0 (1.4, 5.7–11.2) | 4.6 (0.8, 3.3–6.5) | 0.012† |
| Unweighted number | 12 | 10 | 10 | 10 | |
| OR | 1.0 (reference) | 0.975 (0.470–2.023) | 1.112 (0.519–2.383) | 0.538 (0.245–1.185) | 0.052 |
Prevalence was expressed as weighted estimates [%] (standard errors [%], 95% confidence intervals).
P < 0.05
Discussion
To the best of our knowledge, this is the first epidemiologic study to investigate the association between blood folate levels and the incidence of glaucoma using logistic regression. Our findings indicated that there was a significantly lower prevalence of glaucoma in the highest quartile of blood folate levels than in the lowest quartile. Among women, after adjusting for age, diabetes, hypertension, hypercholesterolemia, and smoking, participants in the highest quartile of blood folate levels had an 81.2% lower risk of glaucoma than those in the lowest quartile.
Previous studies have reported no significant differences in blood folate levels between patients with primary open-angle glaucoma and healthy individuals.16,28 However, these previous studies did not perform regression analyses. To our knowledge, this is the first study to investigate the relationship between glaucoma and folate levels using logistic regression analyses.
Pseudoexfoliation glaucoma is associated with low blood folate levels.17 However, a few studies have reported increased plasma and aqueous homocysteine levels in patients with primary open-angle glaucoma, normal tension glaucoma, and pseudoexfoliation glaucoma.17,29,30 This could be attributed to the negative correlation of serum and aqueous homocysteine levels with folate levels.29,31 In addition, folate deficiency alters calcium dynamics, which is related to cell cycle control and stimulates apoptosis.32,33 Therefore folate deficiency might be associated with cardiovascular diseases, neurologic disorders such as Alzheimer's disease, and retinal vascular occlusion.11,15,32 Taken together, the aforementioned mechanisms related to folate could contribute to the negative correlation of the incidence of glaucoma with blood folate levels.
Homocysteine is a neurotoxin that can induce glaucomatous optic neuropathy and apoptosis of RGCs, extracellular matrix alteration, proinflammatory cytokines, and vascular dysregulation.34–37 In patients with diabetes retinopathy, there is a negative correlation between serum homocysteine levels and the RNFL thickness.38 In addition, increased serum homocysteine levels induce oxidative stress in trabecular meshwork cell and are associated with the presence of glaucomatous RNFL defects.38,39 Moreover, homocysteine induces synaptic dysfunction, DNA damage, and activation of apoptosis, which might contribute to the risk of cardiovascular disease, stroke, and neurodegenerative diseases.40 Folate can modulate DNA methylase activities that protect against oxidative stress,10,32 promote remethylation of homocysteine to regenerate methionine, and prevent homocysteine effects.40,41 Although the pathologic role of homocysteine in the development of glaucoma remains unclear, our findings suggest that the inhibitory effect of folate may be related to the negative relationship between folate levels and glaucoma, and thus homocysteine levels, which are negatively associated with folate, may affect the risk of glaucoma.
Women in the highest quartile of blood folate levels had an 81.2% lower risk of glaucoma than those in the lowest quartile. However, this association was not observed in men (Table 4). The mechanism underlying this sex difference remains unclear. Previous studies have reported that migraine, microvascular dysfunction, and vasospasm occur more frequently in women than in men.42,43 Accordingly, these underlying vascular factors in women may influence the relationship between folate and glaucoma.
This study has several limitations. First, we could not include serum homocysteine levels in the analysis since they was no relevant information from the KNHANES; therefore, further research is warranted. Second, it was difficult to establish a causal relationship given the inherent limitation of cross-sectional design. Third, since sex appeared to be an effect modifier, multiple comparisons were performed. Therefore the stratified results were presented separately according to sex. Finally, we did not consider the dietary intake of folate.
In summary, this study suggests a negative correlation between blood folate levels and the prevalence glaucoma in a Korean nationally representative population even after adjusting confounding factors. This inverse correlation was more pronounced in women and younger participants. Folate may have an inhibitory effect on glaucoma development through its antioxidative effect and suppression of homocysteine elevation.
Acknowledgments
The authors thank the Epidemiologic Survey Committee of the Korean Ophthalmologic Society for conducting the examinations in KNHANES and supplying data for this study.
Supported by a grant of Patient-Centered Clinical Research Coordinating Center (PACEN) funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HC23C0130).
Disclosure: J.Y. Lee, None; J.A. Choi, None; S.P. Park, None; D. Jee, None
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