Purpose
Diabetic retinopathy is a major cause of irreversible vision loss. Recent studies have suggested that myopia may be negatively correlated with the prevalence of diabetic retinopathy. We sought to further investigate the association between refractive error and the likelihood of having diabetic retinopathy in a cross-sectional, population-based study of the South Korean population.
Design
Cross-sectional study.
Methods
Data were included from right eyes of 13 424 participants who were 40 years and older with gradable fundus photographs of the Fourth and the Fifth Korea National Health and Nutrition Examination Survey. Diabetic retinopathy was graded using standard fundus photographs. Autorefraction data were collected to calculate spherical equivalent of refraction in diopters (D) and further classified into 4 groups: hyperopia (≥1.0 D), emmetropia (−0.99 D to 0.99 D), mild myopia (−1.0 D to −2.99 D), and moderate to high myopia (≤−3.0 D). Demographic, comorbidity, and health-related behavior information was obtained via interview. A multivariate model was used to evaluate the association between the diagnosis of any diabetic retinopathy and the refractive status.
Results
Mild myopia and moderate to high myopia groups were negatively associated with development of any diabetic retinopathy (odds ratio [OR] 0.42; 95% confidence interval [CI] 0.18–0.97 and OR 0.14; 95% CI 0.02–0.88, respectively). In addition, for every 1 D increase in spherical equivalent, there was a 30% increase of having diabetic retinopathy (OR 1.30; 95% CI, 1.08–1.58).
Conclusions
Our results from a population-based study suggest that myopic status is associated with lower odds of having diabetic retinopathy in the South Korean population.
Diabetic retinopathy is a sight-threatening microvascular complication of diabetes mellitus (DM), and is the leading cause of blindness in the working age population worldwide. Numerous epidemiologic studies have identified risk factors such as hypertension, renal impairment, duration of diabetes, glycemic control, and use of insulin as risk factors for development of diabetic retinopathy. Interestingly, both cross-sectional clinic-based studies and large population surveys have suggested a negative association between myopia and diabetic retinopathy, suggesting that myopia may have a protective effect on developing diabetic retinopathy. This was first suggested in cross-sectional clinic-based studies in diabetic patients with similar HLA phenotypes, showing that nonmyopic subjects were more likely to have nonproliferative diabetic retinopathy or proliferative diabetic retinopathy. An inverse association between myopia and proliferative diabetic retinopathy was also found in the Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR) study, where those with myopia <−2 diopters (D) spherical equivalent (SE) were 60% less likely to progress to proliferative diabetic retinopathy (PDR) in younger-onset diabetes. A multivariate analysis of the Singapore Malay Eye Study (SiMES) also demonstrated that eyes with more severe myopia were less likely to have any diabetic retinopathy. In contrast, the Beijing Eye Study did not demonstrate an association between myopia and diabetic retinopathy in a univariate analysis. Thus, though some studies suggest a negative association between myopia and diabetic retinopathy, there are still conflicting data among large population-based epidemiologic studies.
In this study we use the Korean National Health and Nutrition Examination Survey (KNHANES), a large prospective population-based cross-sectional health study that included screening for diabetic retinopathy, to assess the association between myopia and diabetic retinopathy in this population. The findings may be particularly relevant in this population, which has a high rate of myopia and a growing population of diabetics.
Methods
This study is an analysis of a large prospective population-based cross-sectional health study of South Koreans. The survey has been conducted annually since 2007 under the auspices of the Korea Centers for Disease Control and Prevention, with approval by its institutional review board.
Study Population
All analyses were based on data from the fourth and fifth KNHANES performed from July 2008 to December 2011. The KNHANES is a cross-sectional survey that examines the health and nutritional status of the noninstitutionalized civilian South Korean population. The KNHANES consists of the health interview, health behavior and nutrition surveys, and a health examination. The survey adhered to the principles outlined in the Declaration of Helsinki for research that involves humans, and all participants provided written informed consent. This nationwide representative study for noninstitutionalized civilians uses a stratified, multistage probability sampling design with a rolling survey sampling model.
Data on demographic characteristics, diet, and health-related variables were collected through personal interview and a self-administered questionnaire. Physical examination and blood and urine sampling were performed at a mobile examination center. Ophthalmologic interview questions and examinations were added in the second half of 2008 and were thus available for KNHANES IV and V.
In KNHANES, both the 1-year data surveys and the integrated data of the 2008 through 2011 surveys represent the entire population of Korea. Response rates were 77.8%, 82.8%, 81.9%, and 80.4% in 2008, 2009, 2010, and 2011, respectively (9744 of 12 528 in 2008, 10 533 of 12 722 in 2009, 8958 of 10 938 in 2010, and 8518 of 10 589 in 2011). There were 14 932 subjects 40 years of age and older who participated during the 4-year study period with gradable fundus photographs. We further excluded participants who had a history of refractive surgery and anyone who was aphakic or pseudophakic (n = 1087), or those in which no refraction data were available (n = 421). This left 13 424 subjects who were then included in the study.
Survey Components
The methods related to the ophthalmologic examination in the KNHANES have been described in prior publications. After an ophthalmology-focused interview, participants underwent visual acuity measurements, automated refraction, slit-lamp examination, intraocular pressure (IOP) measurement, fundus photography, and, when deemed appropriate, visual field (VF) examination.
Evaluation of Diabetes Mellitus
Those who were diagnosed by a self-reported history of a physician diagnosis or those who were receiving drug treatment for DM, including insulin or oral hypoglycemic agents, and those who had a fasting plasma glucose level >126 mg/dL without a previous diagnosis of DM were classified as subjects with DM.
Evaluation of Diabetic Retinopathy
Evaluation of diabetic retinopathy in the KNHANES study was described previously. In participants with a history of DM, random blood glucose level >200 mg/dL, or a suspicious diabetic DR finding in nonmydriatic digital fundus photographs (TRC-NW6S; Topcon, Tokyo, Japan), which was performed in all participants >40 years old, 7 standard photographs from the Early Treatment Diabetic Retinopathy Study (ETDRS) were obtained from both eyes after pharmacologic pupil dilation. Retinopathy was identified if any characteristic lesion as defined by the ETDRS severity scale was present: microaneurysms (MAs), hemorrhages, cotton-wool spots (CWSs), intraretinal microvascular abnormalities (IRMAs), hard exudates (HEs), venous beading, and new vessels. A retinopathy severity score was assigned to each eye according to the modification of the Airlie House Classification system as previously described. Eyes were graded according to the following criteria: no DR (levels 10–13) or any DR (levels 14–80). The DR was divided further into nonproliferative DR (NPDR, levels 14–60) and proliferative DR (level >60).
Refractive Status
The primary predictor variable was refractive error, which was evaluated by autorefraction (KR-8800; Topcon) without cycloplegia. Refraction was converted to spherical equivalent, calculated as the spherical value plus half of the astigmatic value. We categorized refractive status into 4 groups: emmetropia (−0.99 to 0.99 D), mild myopia (−1.00 to −2.99 D), moderate to high myopia (≤−3.00 D), and hyperopia (≥1.00 D). We then evaluated the odds of having any diabetic retinopathy, nonproliferative diabetic retinopathy, and proliferative diabetic retinopathy of each refractive group compared with the emmetropia group.
Slit-Lamp Examination
We also investigated the relationship between diabetic retinopathy and anterior chamber depth (ACD) and cataract status. A slit-lamp examination (Haag-Streit model BQ-900; Haag-Streit AG, Koeniz, Switzerland) was performed by study ophthalmologists for determination of diseases in the anterior segment of the eye (eg, pterygium, cataract, aphakia, and pseudophakia) and measurement of the IOP and the ACD using the Van Herick method. Cataract status was defined as a nuclear, cortical, anterior subcapsular, posterior subcapsular, and mixed-type cataract. Pseudophakic and aphakic eyes were excluded from our analyses.
Potential confounding variables that were considered included age; sex; income status; educational level; health-related behavior, such as smoking, alcohol use, exercise, and body mass index; and medical comorbidities, such as anemia, renal failure, hypertension, hyperlipidemia, angina, and stroke. In addition to assessment of demographic information and medical history, participants underwent examination of blood pressure and testing of blood and urine.
Statistical Analysis
Complex sample analysis was used for the KNHANES IV and V data for weighting all values following statistical guidance from the Korea Centers for Disease Control and Prevention. The regression model was constructed after identification of potential confounding variables. All risk factors that were identified as being associated with any DR, NPDR, and PDR diagnosis by univariate analysis with P < .1 as the cutoff point were then included in the multivariable analysis to assess the possible independent association between diabetic retinopathy and the refractive status. After ascertainment of such a possible association, 95% confidence intervals [CIs] of odds ratios (ORs) were identified for each possible association. Two-sided statistical tests were performed with SPSS statistical software, version 21.0 (IBM, Armonk, New York, USA).
Results
There were 14 932 subjects 40 years of age and older who participated during the 4-year study period with gradable fundus photographs. We excluded 1087 subjects with history of refractive surgery or who had aphakia or pseudophakia and 421 subjects with no refraction data OD, leaving 13 424 eligible participants for our analyses ( Table 1 ). The SE was highly correlated between eyes: the mean SE was −0.50 (± 0.02) D in the right eye and −0.47 (± 0.02) D in the left eye (r = 0.867, P < .001), so we therefore used the right eye for all further analyses on refractive error.
| Characteristic | No DR (N = 1517, 90.2%) | DR (N = 168, 9.8%) |
|---|---|---|
| Eye conditions | ||
| Refractive status (SE, diopters) | −0.31 (0.07) | 0.11 (0.13) |
| Hyperopia (SE ≥1.0) | 414 (20.4) | 40 (22.6) |
| Emmetropia (−0.99 ≤ SE ≤ 0.99) | 818 (57.1) | 103 (65.6) |
| Mild myopia (−2.99 < SE ≤ −1.0) | 202 (15.7) | 19 (9.0) |
| Moderate to high myopia (SE ≤−3.0) | 83 (6.8) | 6 (2.8) |
| ACD a | ||
| ≤1/4 | 29 (1.8) | 2 (1.4) |
| 1/4 < ACD <1/2 | 395 (25.9) | 42 (28.4) |
| ≥1/2 | 1071 (72.3) | 122 (70.1) |
| Cataract | ||
| Cortical | 206 (11.6) | 21 (9.5) |
| Nuclear | 513 (30.0) | 64 (34.7) |
| Anterior subcapsular | 23 (1.0) | 1 (1.0) |
| Posterior subcapsular | 8 (0.5) | 3 (3.6%) |
| Mixed | 159 (7.7) | 25 (14.9) |
| No cataract | 608 (49.3) | 54 (36.4) |
| Demographics | ||
| Age, mean (SE), y | 58.37 (0.37) | 59.33 (0.97) |
| Women, n (%) | 719 (42.2) | 85 (45) |
| Education | ||
| Elementary and under | 694 (38.9) | 84 (47.4) |
| Middle school | 239 (16.3) | 32 (21.7) |
| High school | 361 (29.3) | 32 (17.6) |
| College and graduate | 201 (15.6) | 16 (13.2) |
| Annual income, quartile | ||
| 1 st | 482 (26.8) | 61 (38.9) |
| 2 nd | 377 (27.5) | 38 (21.5) |
| 3 rd | 322 (22.5) | 37 (22.8) |
| 4 th | 307 (23.1) | 28 (16.8) |
| Health-related behavior | ||
| Duration of diabetes, mean in years (standard error) | 6.85 (0.25) | 10.75 (0.83) |
| Smoking status | ||
| Never | 792 (47.8) | 94 (54.4) |
| Past smokers | 210 (13.3) | 23 (13.2) |
| Current smokers | 515 (38.9) | 51 (32.4) |
| Alcohol | ||
| No drinking in past year | 256 (18.5) | 34 (30.3) |
| ≤1/month | 220 (17.8) | 21 (12.7) |
| 2–4 times/month | 219 (20.3) | 21 (21.3) |
| 2–3 times/week | 190 (17.8) | 16 (13.5) |
| ≥ 4/week | 164 (15.6) | 20 (13.6) |
| BMI, mean (SE) b | 25.19 (0.11) | 23.82 (0.25) |
| Exercise (days per week) | ||
| 0 | 1103 (68.7) | 140 (85.2) |
| 1 | 86 (6.8) | 3 (3.3) |
| 2 | 83 (6.6) | 4 (1.7) |
| 3 | 91 (7.8) | 8 (4.0) |
| ≥4 | 109 (7.2) | 9 (5.4) |
| Medical comorbidities | ||
| Anemia | 145 (9.6) | 22 (10.8) |
| Renal failure | 10 (0.5) | 0 (0) |
| MI | 35 (1.7) | 4 (2.4) |
| Hypertension | 798 (49.0) | 83 (41.7) |
| Hyperlipidemia | 379 (22.8) | 40 (21.7) |
| Angina | 62 (3.4) | 9 (4.3) |
| Stroke | 72 (3.6) | 10 (7.7) |
| BUN | 15.72 | 16.76 |
| Creatine | 0.87 | 0.88 |
| Triglycerides | 188 | 193 |
| Mean SBP | 126 | 129 |
| Mean SDP | 79 | 77 |
| Blood sugar | 141 | 171 |
| HbA1c | 7.17 | 8.52 |
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