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Clinical science
Intraocular pressure and coronary artery calcification in asymptomatic men and women
  1. Sungmin Ye1,
  2. Yoosoo Chang1,2,
  3. Chan-Won Kim1,
  4. Min-Jung Kwon1,3,
  5. Yuni Choi1,
  6. Jiin Ahn1,
  7. Joon Mo Kim4,
  8. Hyun Soo Kim1,5,
  9. Hocheol Shin1,6,
  10. Seungho Ryu1,2
  1. 1Center for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, Korea
  2. 2Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, Korea
  3. 3Department of Laboratory Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, Korea
  4. 4Department of Ophthalmology, Kangbuk Samsung Hospital , Sungkyunkwan University School of Medicine, Seoul, Korea
  5. 5Department of Anesthesiology and Pain Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, Korea
  6. 6Department of Family Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Seoul, Korea
  1. Correspondence to Dr Seungho Ryu, Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Samsung Main Building B2, 250, Taepyung-ro 2ga, Jung-gu, Seoul 100-742, Korea; sh703.yoo@gmail.com Dr Yoosoo Chang, Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, Samsung Main Building B2, 250, Taepyung-ro 2ga, Jung-gu, Seoul 100-742, Korea; yoosoo.chang@gmail.com

Abstract

Objective We evaluated the relationship between intraocular pressure (IOP) and the risk of coronary artery calcification as a predictable marker of cardiovascular disease (CVD) in a large study of asymptomatic men and women.

Methods A cross-sectional study was performed in 10 732 asymptomatic men and women without diagnosed CVD or glaucoma. Coronary artery calcium (CAC) was measured by cardiac CT. The IOPs of all participants were measured by experienced nurses with a non-contact tonometer and automatic air puff control. Logistic regression was used to estimate the OR (95% CI) for the presence of CAC (score >0) with IOP quartiles.

Results The prevalence of detectable CAC was 13.7% in men and 4.3% in women. Increasing levels of right IOP were significantly associated with an increased prevalence of CAC. After adjusting for age, sex, smoking, alcohol intake, physical activity, body mass index, educational level, centre, family history of CVD, use of dyslipidaemia medication, diabetes, hypertension, total cholesterol, high density lipoprotein cholesterol and triglycerides, the ORs for CAC score >0, comparing 2–4 quartiles of the right IOP to the lowest quartiles, were 1.32 (95% CI 1.09 to 1.59), 1.20 (95% CI 0.98 to 1.46), and 1.28 (95% CI 1.05 to 1.56), respectively. These associations did not differ by clinically relevant subgroups.

Conclusions A higher IOP is significantly associated with the presence of CAC regardless of conventional cardiovascular risk factors. The present study provides more insight into understanding the process of subclinical atherosclerosis in CVD and the relationship with a higher IOP as a common pathophysiology.

  • Epidemiology
  • Intraocular pressure

https://doi.org/10.1136/bjophthalmol-2014-305925

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    Introduction

    Increased intraocular pressure (IOP) is a major risk factor for primary open-angle glaucoma, one of the major leading causes of blindness in the world.1 IOP is associated with ocular features such as central corneal thickness, corneal curvature, cup to disc ratio, family history of glaucoma or myopia.2 ,3 In addition, studies have reported associations between IOP and systemic conditions. Several cohort studies and population-based cross sectional studies consistently suggest that blood pressure (BP), a history of diabetes or elevated serum glucose are positively correlated with IOP.4 ,5 High BP and diabetes are well known established risk factors associated with cardiovascular disease (CVD). Furthermore, several studies have demonstrated the positive association between IOP and cardiometabolic risk factors or metabolic syndrome.6 ,7 Therefore, the relationship between IOP and cardiovascular risk factors raises the possibility that increased IOP may be associated with CVD.

    To our knowledge, however, there is no study to evaluate the relationship between IOP and the risk of CVD. Coronary artery calcium (CAC) detected by cardiac CT is a subclinical marker of coronary atherosclerosis that predicts future coronary heart disease.8 We therefore examined whether the distribution of IOP is related to the presence of CAC in a large sample of asymptomatic individuals attending an annual or biannual health screening examination.

    Methods

    Study population

    The Kangbuk Samsung Health Study is a cohort study of Korean men and women who underwent a comprehensive annual or biennial examination at the Kangbuk Samsung Hospital Total Healthcare Center in Seoul and Suwon, South Korea.9 The study population consisted of examinees who underwent a cardiac CT estimation of CAC scores as part of a comprehensive health examination from January 2012 to April 2013 (N=18 916), where all measurements were performed using identical equipment and standardised protocols.9 Cardiac CT scanning has become a common component of these screening exams.

    Of 18 916 participants, 8184 were excluded for any of the following reasons: 4713 participants with missing data on IOP and important covariates including smoking status, physical activity and alcohol consumption; 269 participants with a history of CVD; 557 participants with a history of glaucoma, cataract and retinal macular degeneration; 4210 participants whose IOP differed by >2 mm Hg between the two measurements; and two participants with extreme IOP readings <5 mm Hg or >30 mm Hg because of the potential for measurement error. Because some individuals met more than one criterion for exclusion, the total number of eligible subjects for the study was 10 732. This study was approved by the Institutional Review Board of Kangbuk Samsung Hospital, which exempted the requirement for informed consent as we only accessed de-identified data routinely collected as part of health screening exams.

    Measurements

    Data on medical history, medication use, family history, physical activity, alcohol intake, smoking habits, and education level were collected through a self-administered questionnaire, while anthropometry, BP, and serum biochemical parameters were measured by trained staff during the health examinations.9 Smoking status was categorised into never, former, and current smokers. Alcohol consumption was categorised into none, moderate (≤20 g/day), and high (>20 g/day). Physical activity levels were assessed using the Korea-validated version of the International Physical Activity Questionnaire (IPAQ) short form and were classified into three categories: inactive, minimally active, and health-enhancing physically active (HEPA).10 Education level was categorised into less than college graduate, and college graduate or more. Family history of CVD was defined as CVD in one or more first degree relatives at any age.

    All participants underwent physical measurements and biochemical tests during the health examinations. Blood samples were taken after at least 10 h of fasting. The blood parameters included total calcium, inorganic phosphorus, glucose, glycated haemoglobin (HbA1C), insulin, total cholesterol, low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), triglycerides, and high sensitivity C reactive protein (hsCRP) concentration. All blood measures were analysed in the same laboratory with the same machines by the same trained staff using the same methodology. The Laboratory Medicine Department at Kangbuk Samsung Hospital in Seoul, Korea has been biannually accredited by the Korean Society of Laboratory Medicine (KSLM), and annually participates in the survey of the Korean Association of Quality Assurance for Clinical Laboratories (KAQACL) and the CAP (Collage of American Pathologists) Proficiency Testing.9

    Hypertension was defined as a systolic BP (SBP) ≥140 mm Hg, diastolic BP (DBP) ≥90 mm Hg, or current use of antihypertensive medication. Diabetes was defined as fasting serum glucose ≥126 mg/dL, HbA1C ≥6.5%, or the use of blood glucose lowering agents.

    Assessment of IOP

    The IOPs of all participants were measured by experienced nurses with a non-contact tonometer and automatic air puff control (CT-80, Topcon Yamagata Co Ltd, Tokyo, Japan). IOP was measured twice in both eyes while the patient was sitting and the mean of the two results was used for analysis. Subjects whose IOP differed by >2 mm Hg between the two measurements were excluded.

    Measurement of CAC by multidetector CT

    CT scans were performed with a Lightspeed VCT XTe-64 slice multidetector CT scanner (GE Healthcare, Tokyo, Japan) in both the Seoul and Suwon centres using the same standard scanning protocol, which was 2.5 mm thickness, 400 ms rotation time, 120 kV tube voltage, and 124 mAs (310 mA*0.4 s) tube current under ECG-gated dose modulation. The quantitative CAC scores were calculated as previously described by Agatston et al.11 The inter-observer and intra-observer reliabilities for CAC scores were both excellent (intraclass correlation coefficients of 0.99).9

    Statistical analysis

    Baseline characteristics of the study population were calculated both overall and according to the quartiles of the right IOP. Participants were divided into the following quartiles so there would be an adequate number within each group: 7.0–13.0, 13.1–15.0, 15.1–17.0, and 17.1–27.0 mm Hg. To test for linear trends, we included the median value of each of the IOP quartiles as a continuous variable in the regression models. The distribution of continuous variables was evaluated and appropriate transformations were performed during analysis as needed. ORs were used to measure the association of the presence of coronary calcium with the IOP quartiles. Logistic regression models were used to estimate ORs and 95% CIs after adjusting for potential confounders.

    The models were initially adjusted for age and sex, and then for centre (Suwon or Seoul), smoking status (never, former, current, or unknown), alcohol intake (0, <20, ≥20 g/day, or unknown), physical activity (inactive, minimally active, health-enhancing physical activity, or unknown), body mass index (BMI), educational level (high school graduate or less, college graduate or higher, or unknown), family history of CVD, medication for dyslipidaemia, diabetes, hypertension, total cholesterol, HDL-C, and triglycerides. Subgroup analyses were conducted according to age group (<40 vs ≥40 years), sex (women vs men), BMI (<25 vs ≥25 kg/m2), smoking (current smoker vs non-current smoker), alcohol intake (<20 vs ≥20 g/day), HEPA (yes vs no), hsCRP (<1.0 vs ≥1.0 mg/L), diabetes (yes vs no), hypertension (yes vs no), and Framingham risk score (<10% vs ≥10%). Interactions by subgroups were tested using likelihood ratio tests comparing models with and without multiplicative interaction terms. Statistical analysis was performed using Stata v.13.0 (StataCorp LP, College Station, Texas, USA). All reported p values are two tailed with p<0.05 considered statistically significant.

    Results

    The mean±SD age of study participants was 40.7±7.5 years and 83.3% of participants were males. The prevalence of current smokers, diabetes, and hypertension were 26.8%, 4.8%, and 14.1%, respectively. The mean±SD IOP of the left and right eye were both 14.9±3.0 mm Hg. The correlation between left and right IOP was 0.88 (p<0.001).

    Subjects with higher levels of right IOP were more likely to be older, men, smokers, drinkers, and to have hypertension, diabetes, and a high education level. The right IOP was significantly associated with a variety of metabolic parameters, including BMI, waist circumference, SBP and DBP, glucose, total cholesterol, LDL-C, triglycerides, hsCRP, and the homeostasis model assessment of insulin resistance (HOMA-IR). HDL-C values were inversely associated with the right IOP (table 1).

    View this table:
    Table 1

    Baseline characteristics of study participants by right IOP

    Of the 10 732 participants, 13.7% of men and 4.3% of women had a CAC score >0. Table 2 presents the associations between the right IOP quartiles and the prevalence of detectable CAC. Increasing levels of right IOP were progressively associated with increased prevalence of CAC. In age and sex adjusted models, the OR for CAC score >0 comparing 2–4 quartiles of right IOP to the lowest quartiles was 1.39 (95% CI 1.16 to 1.67), 1.33 (95% CI 1.11 to 1.60), and 1.62 (95% CI 1.35 to 1.95), respectively (p for trend <0.001). After adjusting further for smoking, alcohol intake, physical activity, BMI, educational level, centre, and family history of CVD, the OR for CAC score >0 comparing the highest quartiles of right IOP to the lowest quartiles was 1.45 (95% CI 1.20 to 1.76). The association also persisted after adjusting further for medication to treat dyslipidaemia, diabetes, hypertension, total cholesterol, HDL-C, and triglycerides (OR for CAC score >0 comparing the highest quartiles of right IOP to the lowest quartiles 1.28, 95% CI 1.05 to 1.56).

    View this table:
    Table 2

    ORs* (95% CI) of coronary artery calcification by right IOP quartiles

    The association between both right quartiles and the prevalence of detectable CAC were similar across subgroups of study participants, and there were no significant interactions according to age group (<40 vs ≥40 years), sex (women vs men), BMI (<25 vs ≥25 kg/m2), smoking (current smoker vs non-current smoker), alcohol intake (<20 vs ≥20 g/day), HEPA (yes vs no), hsCRP (<1.0 vs ≥1.0 mg/L), diabetes (yes vs no), hypertension (yes vs no), and Framingham risk score (<10% vs ≥10%) (see online supplementary appendix table 1).

    Discussion

    In this large sample of an asymptomatic population, we found an association between IOP and subclinical atherosclerosis measured by CAC CT. This association remained significant even after adjustment of possible confounders including conventional cardiovascular risk factors.

    It is presumed that the increased risk of CAC status and distribution of higher IOP have a coexisting pathophysiology. There is a possibility that high BP would play an important role in both increased IOP and CAC. Elevated BP, an established risk factor for CVD, has been reported to be associated with elevated IOP levels.4–6 In our study, SBP, DBP, and hypertension status were positively correlated with higher quartile distribution of IOP. It has been inferred that high BP contributes to the elevation of ciliary artery pressure in the eye, increasing the ultrafiltration and production of aqueous humour.12 This mechanism has been postulated as the cause of elevated IOP. In this study, however, increasing levels of IOP were progressively associated with the increasing risk of CAC independently of hypertension.

    Obesity and other metabolic conditions could be considered for the possible shared pathophysiology between CAC and higher IOP. The result of present study showed increased LDL-C, decreased HDL-C, increased triglycerides, and obesity features based on BMI and waist circumference were associated with higher quartile IOP. Some of these parameters are the main components of metabolic syndrome with elevated BP and fasting glucose value. Metabolic syndrome and obesity are known risk factors of CVD and type 2 diabetes.13 Several previous studies have also indicated metabolic syndrome as a risk factor for increased IOP or ocular hypertension.14 However, in this study, the association of IOP with the prevalence of detectable CAC persisted after adjusting further for BMI and metabolic profiles.

    Sympathetic neural tone has been proposed as a mechanism for the relationship between heart rate and increased IOP.15 It was reported, in a rabbit experiment, that the stimulation of the ocular sympathetic nerve could also increase IOP by decreasing aqueous humour outflow.16 Sympathetic hyperstimulation or dysregulation is well observed in clinical research and suggested as a common physiologic condition of metabolic syndrome, obesity and dyslipidaemia.17 Therefore, there is a possibility that sympathetic nerve activity could be a link to both CAC and IOP. In regards to obesity and IOP, a hypothesis has been suggested that excessive orbital fatty tissue or lipid deposits are responsible for high episcleral venous pressure and decreased aqueous humour outflow, which results in the elevation of IOP.12

    Diabetes and glucose tolerance are well known representative risk factors for CVD.18 Earlier studies documented that diabetes and hyperglycaemia were related to IOP elevation. In our study, interestingly, the association between IOP quartiles and the prevalence of detectable CAC was stronger in diabetic subjects, even though the interaction of IOP quartiles and diabetes for CAC was not statistically significant. The mechanisms by which a higher IOP is more strongly associated with the presence of CAC in diabetic subjects compared to non-diabetic subjects are not fully understood. However, diabetes-related autonomic dysfunction may contribute to increased IOP.19 Autonomic dysfunction often coexists with other diabetes-related complications including micro- and macrovascular complications. Thus, higher IOP as a manifestation of autonomic dysfunction could coexist with CAC as one of the subclinical macrovascular complications.

    Glycation-induced corneal collagen cross-links in diabetes can cause corneal stiffening,20 which has been shown to increase the level of measured IOP over the true IOP. Studies have found that diabetics have greater central corneal thickness compared to those without the disease,21 which may artefactually increase IOP readings depending on the IOP measurements. Among diabetic patients, central corneal thickness was significantly correlated with diabetic duration.22 Thus, artefactually high IOP readings in diabetic patients can reflect longer duration of diabetes, which may relate to the observed association between higher IOP and CAC. Therefore, establishing that higher IOP is associated with increased CAC in diabetic patients will require additional measures to assess further the autonomic dysfunction and relevant ocular factors. Other possibilities may include endothelial dysregulation caused by a hyperglycaemic condition or diabetes. Endothelial dysfunction is a well-explained pathophysiologic model of atherosclerosis in CVD, and many clinical studies have demonstrated the association with diabetes.23 At the same time, diabetes is one of the main causes that change the microvascular structures and blood flow of the retina, optic nerve head and choroid in the eyes, which lead to diabetic retinopathy and various other eye diseases. One of the MESA (Multi-Ethnic Study of Atherosclerosis) studies found retinopathy is associated with CAC.24 Many previous studies have also proposed endothelial dysfunction as a contributing mechanism for the progression of glaucoma.25

    The present research has some limitations. First, the design of this study is a cross-sectional analysis and does not provide a temporal or clear causal relationship between CAC and IOP. Second, the measurement of IOP is based on non-contact air-puff tonometry, and several ocular features, including central corneal thickness and corneal rigidity, were not considered in this study. However, only obtaining the IOP is acceptable and widely used in health screening centres to reduce the time for estimation. Generally, large scale cohort or population based studies usually use a non-contact tonometer to measure IOP. Several previous studies such as the Beijing Eye Study in China, the Shihpai Eye Study in Taiwan, and the Gutenberg Health Study in Germany used non-contact air puff devices.6 ,26 ,27 Although this method does not evaluate the ocular characteristics associated with IOP, we measured the IOP in both eyes of all the participants twice and measurements within 2 mm Hg of one another were used for more accurate and proper analysis. Finally, our study population consisted of young to middle-aged Korean men and women, and the findings may not be generalisable to other populations.

    In conclusion, this is the first study to evaluate the association between the risk of subclinical coronary atherosclerosis and IOP, demonstrating that the presence of CAC is associated with higher IOP. The present study provides more insight into understanding the process of subclinical atherosclerosis in CVD and the relationship with higher IOP as a common pathophysiology.

    Acknowledgments

    We thank Tae Sung Choi (Kangbuk Samsung Hospital, Information System, Seoul, Korea) for his help with technical support.

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    Supplementary materials

    • Supplementary Data

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    Footnotes

    • Contributors SY, SR and YC planned and designed the study and developed the study protocol. SR analysed the data. SY, SR, YC, C-WK, M-JK, YC, JA, JMK, HSK and HS interpreted the results. SY and SR drafted the manuscript. All authors contributed to critical revision of the manuscript.

    • Competing interests None.

    • Ethics approval Institutional Review Board of Kangbuk Samsung Hospital.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data sharing statement Data will be available on request by the corresponding author.

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