June 2015
Volume 56, Issue 6
Free
Clinical and Epidemiologic Research  |   June 2015
Prevalence of Optic Disc Hemorrhage in Korea: The Korea National Health and Nutrition Examination Survey
Author Affiliations & Notes
  • Dai Woo Kim
    Department of Ophthalmology, Seoul National University College of Medicine, Seoul, Korea
    Department of Ophthalmology, Seoul National University Hospital, Seoul, Korea
  • Young Kook Kim
    Department of Ophthalmology, Jeju National University College of Medicine, Jeju, Korea
    Department of Ophthalmology, Jeju National University Hospital, Seoul, Korea
  • Jin Wook Jeoung
    Department of Ophthalmology, Seoul National University College of Medicine, Seoul, Korea
    Department of Ophthalmology, Seoul National University Hospital, Seoul, Korea
  • Dong Myung Kim
    Department of Ophthalmology, Seoul National University College of Medicine, Seoul, Korea
    Department of Ophthalmology, Seoul National University Hospital, Seoul, Korea
  • Ki Ho Park
    Department of Ophthalmology, Seoul National University College of Medicine, Seoul, Korea
    Department of Ophthalmology, Seoul National University Hospital, Seoul, Korea
  • Correspondence: Ki Ho Park, Department of Ophthalmology, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 110-744, Korea; kihopark@snu.ac.kr
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 3666-3672. doi:10.1167/iovs.14-16319
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      Dai Woo Kim, Young Kook Kim, Jin Wook Jeoung, Dong Myung Kim, Ki Ho Park, ; Prevalence of Optic Disc Hemorrhage in Korea: The Korea National Health and Nutrition Examination Survey. Invest. Ophthalmol. Vis. Sci. 2015;56(6):3666-3672. doi: 10.1167/iovs.14-16319.

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

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Abstract

Purpose.: We determined the prevalence of disc hemorrhage (DH) and the associated factors of DH in a large Korean population based on the data from the nationwide cross-sectional survey, the Korea National Health and Nutrition Examination Survey (KNHANES).

Methods.: We performed a retrospective review of the KNHANES dataset covering January 2012 to December 2012. A total of 5612 subjects aged 19 years and older had completed health interviews, physical examinations, and ophthalmologic assessment, including comprehensive glaucoma evaluation. Two masked graders evaluated the fundus photography to detect DH. The prevalence of DH in each subject was defined as the presence of DH in at least one eye.

Results.: The estimated prevalence of DH in the Korean population aged 19 years and older was 0.42% (95% confidence interval [CI], 0.26–0.67), which increased with age, 1.04-fold in 1 year and 1.54-fold in 10 years, according to Poisson regression analysis. The estimated prevalences of DH were 0.54% in subjects aged 30 years and older, 0.67% in those aged 40 years and older, and 0.71% in those aged 50 years and older. Glaucoma was diagnosed in 4.18% (95% CI, 3.58–4.88) of cases, and the prevalence of DH in glaucomatous subjects was 2.82% (95% CI, 1.53–5.14). In a multivariate analysis, the occurrence of DH was significantly associated with age (P < 0.001) and the presence of glaucoma (P < 0.001).

Conclusions.: The prevalences of DH among Koreans are similar to the figures reported by previous population-based studies for the same age ranges. Associated factors were age and glaucoma. The presence of DH suggested the presence of glaucoma with a positive predictive value of 41.4%.

Bjerrum1 first reported optic disc hemorrhage in a glaucoma patient, using the term “glaucoma haemorrhagicum,” in 1889. Nowadays, it is widely accepted that one of the most important risk factors for development and progression of glaucoma is disc hemorrhage (DH).24 
Numerous hospital-based analyses and several population-based studies have examined the prevalence and locations of DH in various ethnic groups and in various groups of glaucoma patients. The prevalence of DH in the normal population is 0% to 1.4%,2,59 whereas in glaucoma or ocular hypertension patients, the range is 2% to 33.4%,which is much wider and higher.2,514 Due to the high potential for selection artifacts resulting from referral bias in hospital-based studies, prevalences determined in general populations may be more meaningful. 
The primary aim of the present study was to investigate the prevalence of DH in the adult Korean population aged 19 years and older. The secondary aim was to identify the associated factors of DH. The data analyzed were obtained from the Korea National Health and Nutrition Examination Survey (KNHANES), a nationally representative sample collected by the Korea Center for Disease Control and Prevention (KCDC). South Korea is an East Asian country of approximately 50 million people constituting what is almost entirely a single ethnic group.15 Its ethnic homogeneity offers rare and valuable insight into the risk factors for any disease. To the best of our knowledge, this is the first report on DH prevalence and associated factors in the general Korean population. 
Methods
Study Population
The KNHANES is a nationwide population-based cross-sectional survey of a representative civilian nonhospitalized South Korean population. It was initiated in 1998 and has been conducted annually since 2007.16 The data analyzed in the present study were acquired from the fifth KNHANES (KNHANES V-III), which was conducted from January to December 2012. To prevent subject omission and overlap, 3840 households across 192 national enumerated districts were selected, using a stratified multistage cluster sampling design, on the basis of the National Census Data. The enumerated districts were geographic areas representing a specific portion of a city or a county, from which 20 households were selected using systematic sampling.16 To avoid selection bias, participants were selected to represent the actual distribution of the Korean population according to a stratified multistage cluster sampling design. All family members of selected households above 1 year of age were included as eligible subjects. All were asked to participate in the Health Interview Survey and the Health Examination Survey, which latter included ophthalmologic examinations. All of the interviews and examinations were performed by trained teams in mobile centers. Ultimately, participants aged 19 years and older who had one or more evaluable fundus photograph were included in the present study. Written informed consent was obtained from all of them, the KCDC Institutional Review Board (IRB)/Ethics Committee approval was obtained, and the tenets of the Declaration of Helsinki were observed. 
Examinations
The Health Interview Survey included standardized questionnaires on demographic variables, as well as current and past medical conditions. The questionnaires queried respondents on health-influencing behaviors, such as smoking, drinking, and exercise, socioeconomic status, and known diagnoses of systemic diseases. Body height and weight, waist circumference, and average blood pressure in a sitting position corrected by arm length were measured. Routine blood tests also were performed. 
Ophthalmologists engaged with the Korean Ophthalmological Society (KOS) who had been periodically trained by the KOS National Epidemiologic Survey Committee performed comprehensive ophthalmologic examinations in a suitably equipped mobile clinic. After an ophthalmology-focused interview, visual acuity based on the LogMAR Scale (Jin's Vision Chart, Seoul, Korea),17 Goldmann applanation tonometry, and automatic refractometry (KR-8800; Topcon, Tokyo, Japan) were measured. Slit-lamp biomicroscopy also was performed, and any abnormality of the anterior segment was noted. Retinal examinations were performed by obtaining a 458-field angle nonmydriatic fundus photograph of each eye from all of the participants aged 19 years and older. The photographs were taken with a digital fundus camera (TRCNW6S; Topcon) using reinstalled software (IMAGEnet; Topcon) in a dark room to allow for physiological dilation of pupils. Automated visual field testing (Humphrey Matrix frequency-doubling perimeter; Carl Zeiss Meditec, Inc., Dublin, CA, USA) with the screening program N-30-1 was performed on participants with elevated IOP (≥22 mm Hg) or a glaucomatous optic disc. Glaucomatous optic disc was determined based on the following criteria: horizontal or vertical cup-to-disc ratio ≥ 0.5, or violation of the ISNT rule (neuroretinal rim thickness order: inferior > superior > nasal > temporal), or presence of optic disc hemorrhage, or presence of retinal nerve fiber layer (RNFL) defect. In the same manner as in the relevant previous studies,18,19 glaucoma was defined according to the criteria of the International Society of Geographical and Epidemiological Ophthalmology (ISGEO) classification scheme,20 which requires category 1, category 2, or category 3 criteria to be met. Category 1 is a visual field defect consistent with glaucoma as well as a vertical cup-to-disc ratio (VCDR) greater than or equal to 0.7 or asymmetry of VCDR greater than or equal to 0.2 (both values ≥ 97, fifth percentile for normal population in KNHANES), or the presence of RNFL defect. Category 2, in the event of unproven visual field defects, is a VCDR greater than or equal to 0.9 or asymmetry of VCDR greater than or equal to 0.3 (both values ≥ 99, fifth percentile for normal population in KNHANES), or the presence of RNFL defect with violation of the ISNT rule (neuroretinal rim thickness order: inferior > superior > nasal > temporal). Category 3, in the event that no information on visual field testing or optic disc is available, is visual acuity less than 3/60 and IOP greater than the 99, fifth percentile. Two masked ophthalmologists (KHP, YKK) evaluated fundus photography for the presence of DH. Both evaluators read all of the photographs individually. The presence of DH was determined when both evaluators agreed. Diagnosis of DH in each subject was defined as the presence of DH in at least one eye. 
Statistical Analysis
All estimates were derived using sample weights statistically adjusted for response rate, extraction rate, and distribution of the Korean population in 2012. Prevalence estimates for all outcomes were performed for the overall sample and then expressed as mean values with the 95% confidence interval (CI). Poisson regression analysis was performed for tendency of prevalence change in the age and sex distributions. The study population was divided into a hemorrhagic group (according to the definitions noted above) and a nonhemorrhagic group (which included all of the remaining subjects). The demographic and systemic parameters included in the analysis were age, sex, systolic and diastolic blood pressure, body mass index (BMI), waist circumference, fasting blood glucose, glycosylated hemoglobin, total cholesterol, triglyceride, hemoglobin, and hematocrit. Of the ocular parameters, IOP, refractive error, vertical cup-to-disc ratio, presence of RNFL defect, and presence of glaucoma were included in the analysis. Associated factors determining the presence of DH were examined using a two-step approach. In the first step, potential risk factors were individually subjected to univariate logistic regression analysis, and those with a P value < 0.05 were selected as candidates for further analysis. In the second step, those factors were subjected to multivariate logistic regression analysis with a stepwise selection method. Categorical and continuous variables were examined as risk factors, which entailed the calculation of odds ratios (OR) with 95% CIs. Statistical analyses were performed using SPSS for Windows software, version 20.0 (SPSS, Inc., Chicago, IL, USA). 
Results
Study Participants
From January to December 2012, 7645 of the 10,069 total eligible subjects (a 75.9% response rate) participated in the Health Interview Survey and the Health Examination Survey (which involved ophthalmologic examinations, Fig. 1). Of these, 5612 (73.4%) who were aged ≥ 19 years and had available fundus photographs for at least one eye were finally included in this study. Their mean age was 51.55 ± 2.37 years. Age groups from 19 to 29 years, 30 to 39 years, 40 to 49 years, 50 to 59 years, 60 to 69 years, 70 to 79 years, and 80+ years included 11.4%, 16.7%, 16.9%, 19.1%, 18.1%, 14.8%, and 3.0% of the study population, respectively. The male sex accounted for 45.63 ± 0.67% of the participants. The mean refractive error was −1.01 ± 0.06 diopters, and the mean IOP was 13.86 ± 0.16 mm Hg. A comparison of the characteristics of the included and excluded participants showed no significant difference between the two groups (Table 1). 
Figure 1
 
Participation flowchart from the KNHANES 2012.
Figure 1
 
Participation flowchart from the KNHANES 2012.
Table 1
 
Characteristics of Study Participants and Excluded Candidates
Table 1
 
Characteristics of Study Participants and Excluded Candidates
Prevalence of Optic DH
Among the 5612 subjects, DH was detected in 29 cases. The estimated prevalence of DH, as analyzed with sample weights, was 0.42% (95% CI, 0.26–0.67). The prevalences in the 19 to 29, 30 to 39, 40 to 49, 50 to 59, 60 to 69, 70 to 79, and 80+ age groups were 0.06% (95% CI, 0.01–0.46), 0%, 0.52% (95% CI, 0.18–1.54), 0.52% (95% CI, 0.19–1.42), 0.56% (95% CI, 0.27–1.15), 1.27% (95% CI, 0.60–2.66), and 2.09% (95% CI, 0.33–12.05), respectively (Fig. 2; Table 2). The prevalence of DH increased with age: 1.04-fold in 1 year, and 1.54-fold in 10 years, according to Poisson regression analysis (P < 0.001). When different cut-off ages were applied, the prevalences of DH were 0.54% (95% CI, 0.34–0.75) in subjects aged 30 years and older, 0.67% (95% CI, 0.4–0.92) in those 40 years and older, 0.71% (95% CI, 0.42–1.01) in those 50 years and older, and 0.89% (95% CI, 0.48–1.31) in those 60 years and older (Table 2). Glaucoma was diagnosed in 292 of the 5612 subjects, for an overall prevalence of 4.18% (95% CI, 3.58–4.88). Disc hemorrhage was found in 12 of those 292 glaucomatous subjects (2.82%; 95% CI, 1.53–5.14) and in 17 of the 5320 nonglaucomatous subjects (0.32%; 95% CI, 0.21–0.63). The prevalences of DH among glaucomatous subjects in the different age groups were 0%, 0%, 2.29% (95% CI, 0.32–14.54), 0%, 3.94% (95% CI, 1.47–10.18), 7.12% (95% CI, 3.05–15.73), and 0%, in the 19 to 29, 30 to 39, 40 to 49, 50 to 59, 60 to 69, 70 to 79, and 80+ age groups, respectively (Table 2). Over again, the prevalences of DH were 2.88% (95% CI, 1.54–5.33) in glaucomatous subjects aged 30 years and older, 3.25% (95% CI, 1.74–5.99) in those 40 years and older, 3.50% (95% CI, 1.83–6.59) in those 50 years and older, and 3.67% (95% CI, 1.95–7.02) in those 60 years and older. However, a Poisson regression analysis indicated that the prevalence DH in glaucomatous subjects did not increase with age (P = 0.269). 
Figure 2
 
Age-stratified prevalence of DH in Korean population.
Figure 2
 
Age-stratified prevalence of DH in Korean population.
Table 2
 
Age-Stratified Prevalence of DH in Population-Based Studies
Table 2
 
Age-Stratified Prevalence of DH in Population-Based Studies
The characteristics of the hemorrhagic and nonhemorrhagic subjects are compared in Table 3. In the hemorrhagic group, the subjects were significantly older, the proportion of rural residents was higher, and glaucoma was more prevalent. The subjects from urban areas numbered 4568 (81.4%), and those from rural areas, 1044 (18.6%), which represents the actual distribution of the Korean population. The prevalences of DH in the urban and rural areas were 0.28% (95% CI, 0.19–0.62) and 0.82% (95% CI, 0.37–1.71), respectively (P = 0.032). Glaucoma was diagnosed in 3.82% (95% CI, 3.11–4.60) and 5.93% (95% CI, 4.48–7.72) of the urban and rural populations, respectively (P = 0.008). In comparison with the urban population, the rural population was older (51.35 ± 0.99 vs. 44.32 ± 0.38, P < 0.001), and showed significantly higher systolic BP (120.19 ± 0.91 vs. 117.13 ± 0.39, P = 0.002), BMI (24.20 ± 0.17 vs. 23.68 ± 0.08, P = 0.006), waist circumference (82.87 ± 0.51 vs. 80.57 ± 0.26, P < 0.001), and hemoglobin A1C (HbA1C; 5.82 ± 0.05 vs. 5.71 ± 0.02, P = 0.004). 
Table 3
 
Characteristics of Subjects With DH (Hemorrhagic Group) and Without DH (Nonhemorrhagic Group)
Table 3
 
Characteristics of Subjects With DH (Hemorrhagic Group) and Without DH (Nonhemorrhagic Group)
Associated Factors of Optic DH
The univariate logistic regression analysis found the presence of DH to be significantly associated with older age (P < 0.001), higher HbA1C (P = 0.043), rural residential area (P = 0.037), and the presence of glaucoma (P < 0.001, Table 4). No significant association with sex (P = 0.723), refractive error (P = 0.511), or IOP (P = 0.105) was evident. All of the parameters showing a significant association with DH in the univariate analysis were put into the multivariate logistic regression analysis and significantly associated was age (P < 0.001; OR, 1.05; 95% CI, 1.02–1.08) and the presence of glaucoma (P < 0.001; OR, 5.97; 95% CI, 2.42–14.68, Table 4). 
Table 4
 
Potential Factors Associated With DH in KNHANES 2012
Table 4
 
Potential Factors Associated With DH in KNHANES 2012
Discussion
To our knowledge, this is the first nationwide population-based Korean study on DH prevalence for which sample weights were reflected. The estimated prevalence rates of DH and glaucoma in Korea were 0.42% and 4.18%, respectively, among a population aged 19 years and older. Correspondingly, approximately 0.2 million Koreans might have DH. The associated factors found in this study were age and the presence of glaucoma. 
In previous population-based studies, the prevalences of DH were 1.40% (Blue Mountains Eye Study),5 1.24% (Beijing Eye Study),21 0.93% (Beaver Dam Study),7 0.60% (Japanese Tajimi Study),9 and 0.35% (Central India Eye and Medical Study).22 The discrepancies among these results might reflect the different characteristics of study population, especially age distribution (Table 2). When the same age ranges were applied, the DH prevalences in this study were comparable to the figures from the relevant previous population-based studies. The results were as follows: 0.54% in subjects aged 30 years and older, 0.67% in those aged 40 years and older, and 0.71% in those aged 50 years and older. Moreover, the prevalence of DH in each age group was quite similar between studies (Table 2). Particularly, the Blue Mountains Eye Study disclosed similar DH prevalences for the 60 to 69, 70 to 79, and 80+ age groups, though the overall rate was much higher (1.40%),5 which might indicate that prevalence is considerably dependent on the age distribution of study population. The prevalence of DH was shown to be higher in older age groups and this increasing tendency of DH with age was also demonstrated by Poisson regression analysis in the current study. In the present multivariate regression analysis, age was significantly associated with DH occurrence (OR, 1.05 per year). Likewise, in the Blue Mountains Eye Study,5 DH prevalence increased with age (OR, 2.2 per decade). 
In addition to age, glaucoma was another associated factor for DH occurrence in this study. In all of the relevant previous studies, glaucoma was the main such factor.5,7,9,10,14,21,2326 In the current study, the prevalence of DH in glaucoma cases was 2.8% and glaucoma was a significant associated factor with DH (OR, 5.97). As in the previous studies, however, IOP was not significantly associated with DH. Comparing this study with earlier population-based investigations, the DH prevalence in glaucoma cases was lower; the figure was 5.4% in the Beaver Dam Study,7 5.7% in the Central India Eye and Medical Study,22 8.2% in the Tajimi Study,9 8.8%, 10.6%, 13.2% according to the glaucoma definition in the Beijing Eye Study,21 and 13.8% in the Blue Mountains Eye Study.5 From a clinical point of view, the data suggest that the positive glaucoma-predictive value of DH is 41.4% (12/29), meaning that 41.4% of DH cases would be glaucomatous. The positive predictive value was higher in the Central India Eye and Medical Study (64.7%; 11/17) and the Tajimi Study (73.9%; 65/88), and lower in the Beijing Eye Study (10%∼20% depending on the definition of glaucoma), and the Blue Mountains Eye Study (27.5%; 15/51), respectively. In the present study, 0.32% of nonglaucomatous subjects showed DH, which figure is higher than those from other studies, such as the Tajimi Study (0.2%) and the Central India Eye and Medical Study (0.07%). In hospital-based studies, DH has been found only rarely in normal eyes,13,14 which suggests the high specificity of DH for glaucoma. Population-based studies, on the other hand, including this one, have demonstrated lower DH specificity for glaucoma. The occurrence of DH is relatively more frequent in nonglaucoma cases in such studies. In contrast with the prevalence of DH in the general population, which increases with age, the prevalence of DH among glaucomatous subjects tends not to do so. Also, consistently, as shown in Table 2, two previous studies on age-stratified DH prevalence in glaucomatous subjects found no increasing tendency in older age groups.5,9 
Regarding the association between DH and sex, conflicting results have been reported. Several studies demonstrated female predilection in DH,5,9,23,27 with the OR of 1.9 in the Blue Mountains Eye Study.5 However, others failed to show such association.21,22 In the present study, sex was not significantly associated with the occurrence of DH. 
Although the prevalence of DH in rural areas (0.82%) was higher than in urban areas (0.28%), multivariate analysis revealed no association between DH and residential area (P = 0.396). The older age and higher systolic BP, BMI, waist circumference, and HbA1C of the rural population, all of which are known risk factors for vascular disease, might explain the higher rural prevalence of DH in our study population. Notably in this regard, in the Beijing Eye Study,21 DH occurrence was associated with urban regions, where the mean age was, in fact, older. Moreover, the Central India Eye and Medical Study,22 conducted in rural villages, reported a low DH prevalence of 0.35%, which might be explained by the shorter life expectancy of patients with diabetes mellitus. 
Possible limitations of the current study must be considered. First, as this study was cross-sectional in nature, it did not allow for causality assessment. Nonetheless, DH is widely accepted as one of the most important risk factors for glaucoma progression.24 Second, individuals who did not participate in the survey or who did not have available fundus photographs were excluded from the analyses. However, because the participation rate, 75.9%, was high, and the characteristics of those included in and excluded from the study were not significantly different, the potential selection bias might have been minimal. Third, because the number of eyes with DH was relatively low, a statistically meaningful subgroup analysis was not possible. However, this and the other limitations notwithstanding, the present study did use a national representative dataset that entailed a large study sample, which enabled the extrapolation of the prevalence of DH in the general adult population of Korea. Furthermore, this study, conducted by the KOS and the KCDC, is of a reliable quality and validity, particularly in respect of the use of a standardized protocol and the periodic training of the examiners. 
In conclusion, to our knowledge this is the first detailed report on DH prevalence and associated factors in the general Korean population. The associated factors it identifies are consistent with the literature. Additional prospective studies are required to examine the risk factors for DH incidence and duration, which information would help to elucidate the development and progression of glaucoma. 
Acknowledgments
The authors alone are responsible for the content and writing of the paper. 
Disclosure: D.W. Kim, None; Y.K. Kim, None; J.W. Jeoung, None; D.M. Kim, None; K.H. Park, None 
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Appendix
Epidemiologic Survey Committee of the Korean Ophthalmological Society
Se Woong Kang, MD, PhD (Chair),1 Seung-Hee Baek, MD, PhD,2 Chan Yun Kim, MD, PhD,3 Sang-Duck Kim, MD, PhD,4 Seung-Hyun Kim, MD, PhD,5 Jong Soo Lee, MD, PhD,6 Key Hwan Lim, MD, PhD,7 Ki Ho Park, MD, PhD,8 Young Jeung Park, MD, PhD,9 Jae Pil Shin, MD, PhD,10 Su Jeong Song, MD, PhD,11 Suk-Woo Yang, MD, PhD,12 Kyung-Chul Yoon, MD, PhD,13 and Seung-Young Yu, MD, PhD14 
From the 1Department of Ophthalmology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea; 2Department of Ophthalmology, Kim's Eye Hospital, Konyang; University College of Medicine, Seoul, Korea; 3Institute of Vision Research, Department of Ophthalmology, Yonsei University College of Medicine, Seoul, Korea; 4Department of Ophthalmology, Wonkwang University College of Medicine, Iksan, Korea; 5Department of Ophthalmology, Korea University College of Medicine, Seoul, Korea; 6Department of Ophthalmology, Pusan National University College of Medicine, Busan, Korea; 7Department of Ophthalmology, Ewha Womans University School of Medicine, Seoul, Korea; 8Department of Ophthalmology, Seoul National University College of Medicine, Seoul, Korea; 9Department of Ophthalmology, Cheil Eye Hospital, Daegu, Korea; 10Department of Ophthalmology, Kyungpook National University School of Medicine, Daegu, Korea; 11Department of Ophthalmology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea; 12Department of Ophthalmology, Catholic University of Korea College of Medicine, Seoul, Korea; 13Department of Ophthalmology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Korea; and the 14Department of Ophthalmology, Kyung Hee University School of Medicine, Seoul, Korea. 
Figure 1
 
Participation flowchart from the KNHANES 2012.
Figure 1
 
Participation flowchart from the KNHANES 2012.
Figure 2
 
Age-stratified prevalence of DH in Korean population.
Figure 2
 
Age-stratified prevalence of DH in Korean population.
Table 1
 
Characteristics of Study Participants and Excluded Candidates
Table 1
 
Characteristics of Study Participants and Excluded Candidates
Table 2
 
Age-Stratified Prevalence of DH in Population-Based Studies
Table 2
 
Age-Stratified Prevalence of DH in Population-Based Studies
Table 3
 
Characteristics of Subjects With DH (Hemorrhagic Group) and Without DH (Nonhemorrhagic Group)
Table 3
 
Characteristics of Subjects With DH (Hemorrhagic Group) and Without DH (Nonhemorrhagic Group)
Table 4
 
Potential Factors Associated With DH in KNHANES 2012
Table 4
 
Potential Factors Associated With DH in KNHANES 2012
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