Association of metabolic syndrome with glaucoma and ocular hypertension in a Midwest United States population

Abstract

Purpose:

To determine whether glaucomatous optic neuropathy, also known as glaucoma, and ocular hypertension are more likely to occur in patients with metabolic syndrome.

Patients and methods:

Patients in Olmsted County, MN, USA were identified as having metabolic syndrome based on diagnosis codes, laboratory values, and/or medication use to meet three or more of the five standard criteria for diagnosing metabolic syndrome: systemic hypertension, hyperglycemia, hypertriglyceridemia, reduced high density lipoprotein cholesterol, and central adiposity defined by increased body mass index. Patients with glaucoma, including primary open angle, low tension, pigment dispersion, and pseudoexfoliation, were identified using diagnostic codes. The charts of patients with glaucoma were individually reviewed to collect visual acuity, intraocular pressure, cup to disc ratio, central corneal thickness, visual field mean deviation, retinal nerve fiber layer thickness, and treatment of intraocular pressure. Patients with ocular hypertension were separately identified and similarly evaluated.

Results:

In patients with glaucoma, those with metabolic syndrome had higher intraocular pressure and central corneal thickness compared to those without metabolic syndrome. After adjustment for central corneal thickness, there was no longer a significant difference in intraocular pressure between groups. Metabolic syndrome was also associated with the diagnosis of ocular hypertension, and although central corneal thickness trended higher in patients with metabolic syndrome, it did not attain statistical significance.

Conclusion:

In Olmsted County, though metabolic syndrome was associated with ocular hypertension and higher intraocular pressure in patients with glaucoma, the results were likely related to a thicker central corneal thickness in this patient population.

Précis

For patients with glaucomatous optic neuropathy, metabolic syndrome was associated with higher intraocular pressure and higher central corneal thickness. Patients with metabolic syndrome were also more likely to have ocular hypertension.

Introduction

Glaucomatous optic neuropathy (GON) is a chronic, progressive optic neuropathy that results in characteristic cupping of the optic nerve and visual field loss. GON is a leading cause of blindness, accounting for 8.5% of blindness worldwide, second only to cataract and uncorrected refractive error, which can both be definitively treated.¹ The most significant risk factor for the development of GON is intraocular pressure (IOP). Ocular hypertension (OHTN), though a risk factor for development of GON, is the presence of elevated IOP without evidence of GON. The only reliable treatment to date for GON is lowering IOP with medications, laser, or surgery. These treatments, even when successful, may only delay progression, and furthermore, side effects and repeated dosing lead to compliance issues and high economic burden.^{2, 3} Therefore, the prevention of glaucoma or reduction of progression risk through lifestyle modification is an attractive low-risk, high-reward intervention.

Prior evidence suggests that lifestyle factors may impact the development of glaucoma. In a large study of nurses, certain dietary patterns, including high consumption of leafy green vegetables, are associated with lower risk of primary open angle glaucoma (POAG).⁴ Additionally, a longitudinal study of patients with GON and OHTN demonstrated that greater physical activity is associated with slower visual field loss.⁵ Defining a person’s overall state of health related to lifestyle is a challenge because there are many variables, including underlying genetic predisposition, diet, and exercise. Metabolic syndrome (MetS) is one such definable endpoint.⁶ MetS is a cluster of findings including increased waist circumference (WC), elevated triglycerides, reduced high density lipoprotein cholesterol (HDL-C), elevated systemic blood pressure (BP), and elevated fasting glucose.⁷ The development of MetS is multifaceted with genetic, environmental, and metabolic factors.⁸ At a cellular level, MetS accelerates aging related to inflammation and oxidative stress in similar pathways seen in GON.⁶

The association of MetS with GON ^9–13 and OHTN ^14–28 was recently reviewed.²⁹ However, knowledge gaps exist. Many of the prior studies excluded patients with a prior diagnosis of GON ^{9, 10, 12} or OHTN, ^{15–19, 21, 22, 24–26, 28, 30} which may have contributed to an underestimation of the true association of MetS with GON and OHTN. Additionally, the vast majority of studies investigating the association of MetS with GON and OHTN evaluated populations of East Asian descent.^{9–11, 13, 15–18, 21–28} Since a risk factor of MetS is consumption of a Western diet, which is more common in Europe and North America,³¹ it is unclear whether associations of MetS with OHTN or GON in certain populations can be applied broadly at this time. In addition, other important metrics such as central corneal thickness (CCT), which is inconsistently linked to MetS, ^{12, 32, 33} have not been thoroughly investigated. Prior literature has shown that thin CCT is a risk for advanced GON, potentially due to underestimation of IOP,³⁴ and various formulas have been developed to adjust IOP by CCT.^35–39 No previous studies have assessed CCT adjusted IOP in the setting of MetS, and thus, the role of CCT in the relationship between IOP and MetS is yet to be determined.

In order to address the knowledge gaps, we conducted this study as a retrospective chart review using the Rochester Epidemiology Project (REP), which is a collaboration of health care providers in Olmsted County, MN, USA to share patient medical records, with permission, to researchers.⁴⁰ The REP links medical records to patients within Olmsted County, and verification by manual review and comparison to census data has confirmed the accuracy in correctly identifying residents.⁴¹ This population is relatively stable, with at least 80% of patients over the age of 40 having complete follow-up, and its demographic characteristics are typical for the Midwestern United States.^{42, 43} Thus, the REP provides a comprehensive database of the health status in an American community, with the information necessary to investigate the relationship between MetS, GON, and OHTN.

Methods

The study protocol received institutional review board approval at Mayo Clinic and Olmsted Medical Center. Storage and transfer of patient data complied with the Health Insurance Portability and Accountability Act of 1996 and followed all tenets of the Declaration of Helsinki.

The REP was used to identify all adults 40 years of age or older who resided in Olmsted County, MN at any time between January 1, 2005 and December 31, 2018. Patients were then included if they resided in Olmsted County through December 31, 2018 or passed away prior and had at least one documented eye exam during the study period.

All patients were defined as having MetS or not having MetS. We initially identified only 2,355 (6.15% of those included) patients with MetS as defined by diagnosis code (ICD-10 E88.81). Since the prevalence of MetS would be expected to be much higher in this population,⁴⁴ we employed a more vigorous inclusion criteria based on a previously established definition of MetS (Table 1).⁷ Thus, patients were considered to have MetS if they carried the MetS diagnosis code (ICD-10 E88.81) or had at least three of the five criteria in Table 1 during the study period. These criteria were identified using corresponding diagnostic codes, laboratory values, and prescribed medications. If body mass index (BMI) was not documented in the patient chart, it was calculated from median height and weight for the patient. In order to eliminate measurement outliers, median BP was used to assess for systemic hypertension, and at least two abnormal laboratory values were required to qualify for hypertriglyceridemia, dyslipidemia, and hyperglycemia. Medical treatment for a given condition was considered equivalent to having that condition, and the classes of medications used to treat individual components were noted. The date at which the patient qualified as having MetS was based on the date at which the patient met the third criteria, and once patients qualified for MetS, they were not subsequently reclassified as not having MetS, even with cessation of medication or improvement of blood work. Eye exams after this date were then used to ensure that MetS was present at the time of any other ocular diagnoses. Patients were classified as not having MetS if they had at least three normal criteria from Table 1, including at least 2 normal laboratory values for each measurement. Patients with insufficient data to qualify as having or not having MetS were excluded.

Table 1: Diagnosis of Metabolic Syndrome.

Criteria used to diagnose metabolic syndrome, with patients needing at least three criteria to qualify⁷

Body mass index (BMI) ≥ 27 kg/m2, substituted for waist circumference75

Triglycerides ≥ 150 mg/dL or treatment for or diagnosis of hypertriglyceridemia

HDL-C < 40 mg/dL in men, HDL-C < 50 mg/dL in women or treatment for or diagnosis of dyslipidemia

Blood pressure (BP) ≥ 130 mmHg systolic or ≥ 85 mmHg diastolic or treatment for or diagnosis of hypertension

Fasting glucose ≥ 100 mg/dL or treatment for or diagnosis of hyperglycemia

In this cohort of patients with and without MetS, we then used ICD-10 and ICD-9 medical billing codes to identify patients with POAG, normal/low tension glaucoma (NTG), pigment dispersion glaucoma, and pseudoexfoliation glaucoma (supplemental figure 1). Any of these conditions that resulted in GON were collectively analyzed and referred to as GON. We also searched for patients with billing codes of OHTN, and patients that carried a diagnosis of OHTN without GON were simply referred to as OHTN. Other forms of glaucoma, including steroid-induced, neovascular, and angle-closure were excluded. A one-time use of these diagnostic codes during the study period was sufficient to qualify for the diagnosis, and if multiple diagnostic codes under GON or OHTN were identified under the same patient, we utilized the most recent code within the study period. We identified other ocular comorbidities, including cataract, age-related macular degeneration (AMD), non-glaucomatous optic neuropathy, retinal vascular occlusion (RVO), and proliferative diabetic retinopathy (PDR) in these patients. The selection of patients is summarized in Figure 1.

Figure 1:

A flowchart that shows the inclusion criteria for the study. Boxes outlined in red show patients that were excluded.

When available in the REP database, we collected baseline demographic data including age, sex, race/ethnicity, and smoking history. In patients with GON or OHTN, we then reviewed their most recent eye exam within the study period and if available for each eye, documented a logMAR conversion for the best corrected or pinhole Snellen visual acuity (VA), IOP, cup to disc ratio (C:D), and CCT. IOP was measured by Goldmann applanation tonometry, iCare tonometer (Vantaa, Finland), or Reichert Tono-Pen (Buffalo, USA), and no distinction was made between these methods of tonometry. CCT was measured using ultrasound pachymetry. For patients in which CCT measurements were available, adjusted IOP based on CCT was also calculated using five separate previously published formulas.^35–39 Eye exams performed as inpatient consults and post-operative visits were not used. If performed within 3 months of the most recent eye exam, the Swedish Interactive Thresholding Algorithm 24–2 (Humphrey Field Analyzer, Jena, Germany) visual field mean deviation (VFMD) and retinal nerve fiber layer thickness (RNFL) on ocular coherence tomography (OCT) (Zeiss Cirrus, Jena, Germany) were collected. The associated slit lamp examination and note were also reviewed for any current and prior medical or surgical management of glaucoma. Trabeculectomy and a glaucoma drainage device were considered incisional glaucoma surgery. Laser trabeculoplasty, cyclophotocoagulation, and minimally invasive glaucoma surgery were referred to as a glaucoma procedure.

For the purposes of analysis of VA and VFMD, patients with any ocular comorbidity as previously identified were excluded. In the analysis of RNFL, patients with non-glaucomatous optic neuropathy, RVO, and PDR were also excluded. For the other documented parameters, patients with these ocular comorbidities were included in the analysis.

Statistical Analysis

The primary outcome measure for this study was the likelihood that a patient has GON or OHTN, comparing patients with and without MetS. The secondary outcome measure was the number of components of MetS and the association with GON or OHTN. VA, IOP, C:D, CCT, VFMD, RNFL, and frequency of medical and surgical treatment for patients with and without MetS were also compared, with subgroup analysis for ocular comorbidities.

Categorical factors were estimated using percentages and compared between groups using Chi-square tests. Continuous factors were summarized with either means and standard deviations or medians and inner quartile ranges, depending on the distribution of the variables. Comparisons were initially completed between groups using Wilcoxon rank-sum test for non-normal factors. Logistic regression models were used to look at potential risk factors for MetS in the population. These models included individual factors, but also further investigated adjusting for other important baseline factors. P-values < 0.05 were considered significant. Analysis was completed using SAS version 9.4 (Cary, NC).

Results

Patient demographics

In the REP database, there were 38,286 patients that met inclusion criteria. 30,204 patients (78.9%) qualified as having MetS (Table 2). Study participants were 57.2% female, and patients without MetS were more likely to be female at 73.0% (P < 0.01). Patients with MetS were more likely to identify as white (90.8%) compared to patients without MetS (89.1%) (P < 0.01). Patients without MetS were also younger than patients with MetS, as 62.2% were 40–59 years-old, compared to 29.9% with MetS (P < 0.01). When comparing patients with and without MetS, patients without MetS were more likely to never have used tobacco (89.4% vs 83.5%, P < 0.01).

Table 2: Patient Characteristics.

The demographics of all patients included in the study including gender, race, age, and tobacco use, broken down by presence of metabolic syndrome.

	Metabolic Syndrome (N = 30204, 78.9)	No Metabolic Syndrome (N = 8082, 21.1)	Total (N = 38286)	P-value
Sex, N (%)				<0.01
Male	14208 (47.0)	2188 (27.0)	16396 (42.8)
Female	15996 (53.0)	5894 (73.0)	21890 (57.2)
Race, N (%)				<0.01
White	27429 (90.8)	7203 (89.1)	34632 (90.5)
Black	799 (2.65)	204 (2.52)	1003 (2.62)
Asian	873 (2.89)	387 (4.79)	1260 (3.29)
Other/unknown/refused	1103 (3.65)	288 (3.56)	1391 (3.63)
Age, N (%)				<0.01
40–59	9030 (29.9)	5030 (62.2)	14060 (36.7)
60–79	14521 (48.1)	2600 (32.2)	17121 (44.7)
80+	6653 (22.0)	452 (5.6)	7105 (18.6)
Tobacco use, N (%)				<0.01
Never	23486 (83.5)	6833 (89.4)	30319 (84.8)
Former/Current	4638 (16.5)	813 (10.6)	5451 (15.2)
Missing	2080	436	2516

Out of the patients with MetS, they were most likely to have dyslipidemia (94.7%), hypertriglyceridemia (93.0%), and systemic hypertension (83.0%) (Table 3). Almost half of patients with MetS (46%) met all 5 criteria of MetS.

Table 3: Prevalence of Components of Metabolic Syndrome.

Patients with metabolic syndrome by components present and number of components.

	Number (N = 30,204)	Percent
BMI ≥ 27 kg/m2
Yes	23194	76.8
No	7010	23.2
Hypertriglyceridemia
Yes	28082	93.0
No	2122	7.00
Dyslipidemia
Yes	28589	94.7
No	1615	5.35
Hypertension
Yes	25073	83.0
No	5131	17.0
Hyperglycemia
Yes	23355	77.3
No	6849	22.7
Number of components
3	6419	21.3
4	9889	32.7
5	13896	46.0

Patients with GON

4,653 patients had GON, as determined by diagnosis code, and of these patients, 3,971 (85.3%) had MetS and 682 (14.7%) patients did not have MetS (Table 4). In patients with GON, patients with MetS were more likely be older than those without MetS (74.1 vs 65.2, P < 0.01) and were less likely to be female in the MetS group compared to those without MetS (56.8% vs 68.6%, P < 0.01). Of those with GON, participants with MetS were more likely to be white than those without (91.6% vs 88.3%, P < 0.01). Patients with GON and MetS were more likely to report current or former tobacco use compared to patients without MetS (11.7% vs 8.7%, P = 0.03).

Table 4: Demographics of Patients with Glaucomatous Optic Neuropathy.

Demographics of patients with glaucomatous optic neuropathy as broken down by presence of metabolic syndrome.

	No Metabolic Syndrome (N=682)	Metabolic Syndrome (N=3971)	Total (N=4653)	P-value
Age at Last Eye Exam				<0.011
N	682	3971	4653
Mean (SD)	65.2 (13.26)	74.1 (12.58)	72.8 (13.07)
Median (Range)	63.0 (40.0, 99.0)	75.0 (40.0, 103.0)	74.0 (40.0, 103.0)
Sex, n (%)				<0.012
Female	468 (68.6%)	2254 (56.8%)	2722 (58.5%)
Male	214 (31.4%)	1717 (43.2%)	1931 (41.5%)
White race, n (%)				<0.012
No	79 (11.7%)	332 (8.4%)	411 (8.9%)
Yes	596 (88.3%)	3600 (91.6%)	4196 (91.1%)
Missing	7	39	46
Tobacco use, n (%)				0.032
Never	589 (91.3%)	3277 (88.3%)	3866 (88.8%)
Former/Current	56 (8.7%)	434 (11.7%)	490 (11.2%)
Missing	37	260	297

¹Wilcoxon rank sum p-value

²Chi-Square p-value

POAG was the most common glaucoma-related diagnosis, accounting for 4,284 patients (92.1%), and it represented a higher proportion of GON in patients without MetS than patients with MetS (93.8% vs 91.8%, P < 0.05) (Table 5). Pseudoexfoliation was the next most common (4.4%), followed by NTG (2.6%), and pigment dispersion (1.0%).

Table 5: Types of Glaucomatous Optic Neuropathy in Patients with and without Metabolic Syndrome.

The types of glaucomatous optic neuropathy, as broken down by presence of metabolic syndrome.

	Metabolic syndrome	No Metabolic syndrome	Total	P-value
Glaucomatous optic neuropathy, N	3971	682	4653	<0.05
Primary open angle, N (%)	3644 (91.8)	640 (93.8)	4284 (92.1)
Normal tension, N (%)	107 (2.70)	13 (1.92)	120 (2.58)
Pseudoexfoliation, N (%)	184 (4.63)	20 (2.93)	204 (4.38)
Pigment dispersion, N (%)	36 (0.907)	9 (1.32)	45 (0.967)

The odds ratio (OR) of having a diagnosis of GON, as assessed by diagnosis code, in a patient with MetS is 1.64 as compared to a patient without MetS (P < 0.01) (Table 6). However, when adjusted for the demographic variables age, sex, race, and tobacco use, the OR was no longer statistically significant at 1.04 (P = 0.39). There was also no statistically significant relationship between number of MetS components and GON after demographic adjustment (P = 0.17). When looking at phakic and pseudophakic patients separately, there was no significantly increased odds of having GON in patients with MetS after demographic adjustment (P = 0.41, P = 0.49).

Table 6: Glaucomatous Optic Neuropathy and Ocular Hypertension in Patients with and without Metabolic Syndrome.

Metabolic syndrome and its components as they relate to diagnosis of glaucomatous optic neuropathy and ocular hypertension in patients.

	Unadjusted		Adjusted1
	Odds ratio (95% CI)	P-value	Odds ratio (95% CI)	P-value
Association of glaucomatous optic neuropathy and
MetS	1.64 (1.51, 1.79)	< 0.01	1.04 (0.95, 1.15)	0.39
MetS components	1.16 (1.14, 1.19)	< 0.01	1.02 (0.99, 1.04)	0.17
MetS (phakic)	1.48 (1.33, 1.64)	<0.01	1.05 (0.94, 1.18)	0.41
MetS (pseudophakic)	1.09 (0.93, 1.27)	0.31	0.94 (0.80, 1.11)	0.49
Association of ocular hypertension and
MetS	1.89 (1.62, 2.21)	< 0.01	1.66 (1.40, 1.97)	< 0.01
MetS components	1.22 (1.18, 1.27)	< 0.01	1.18 (1.13, 1.24)	< 0.01

¹age, sex, race, and smoking history adjusted logistic regression

CI = confidence interval

The mean VA was 0.1 in patients with MetS and 0.0 in patients without MetS (P < 0.01) (Table 7). When adjusted for demographics, patients with MetS had greater odds of having an IOP 5 mmHg higher when compared to patients without MetS (OR = 1.23, P < 0.01). There was no significant difference in C:D in those with MetS compared to those without MetS (0.65 vs 0.60, P = 0.92). The mean CCT in patients with MetS was 557 μm, compared to 553 μm in those without MetS (P = 0.01).

Table 7: Eye Exam and Treatment in Patients with Glaucomatous Optic Neuropathy.

Findings on eye exam, testing results, and treatment of patients with glaucomatous optic neuropathy as broken down by presence of metabolic syndrome.

						Unadjusted analysis		Adjusting for age, sex, race (white vs. non-white), and smoking history
Association between metabolic syndrome and:	N	Median (minimum, maximum) or No. (%) for the given group	N		Association measure	Estimate (95% CI)	P-value	Estimate (95% CI)	P-value
		No Metabolic Syndrome		Metabolic Syndrome
VA OD (0.1 logMAR unit)	351	0.0 (−0.1, 1.0)	993	0.0 (−0.1, 5.0)	Odds ratio	1.43 (1.26, 1.62)	<0.01	1.19 (1.06, 1.35)	<0.01
VA OS (0.1 logMAR unit)	351	0.0 (−0.1, 0.5)	995	0.0 (−0.1, 5.0)	Odds ratio	1.43 (1.26, 1.62)	<0.01	1.19 (1.05, 1.34)	<0.01
VA mean (0.1 logMAR unit)	351	0.0 (−0.1, 0.7)	989	0.1 (−0.1, 4.0)	Odds ratio	1.55 (1.34, 1.79)	<0.01	1.25 (1.09, 1.44)	<0.01
IOP OD (5 mmHg)	661	15.0 (4.0, 35.0)	3802	15.0 (2.0, 76.0)	Odds ratio	1.01 (0.92, 1.11)	0.81	1.21 (1.07, 1.37)	<0.01
IOP OS (5 mmHg)	665	15.0 (2.0, 30.0)	3808	15.0 (0.0, 68.0)	Odds ratio	0.97 (0.88, 1.07)	0.55	1.18 (1.05, 1.33)	<0.01
IOP mean (5 mmHg)	660	15.0 (3.5, 30.0)	3785	15.0 (2.5, 63.0)	Odds ratio	0.99 (0.89, 1.10)	0.81	1.23 (1.08, 1.40)	<0.01
C:D OD (0.10)	652	0.60 (0.00, 1.00)	3831	0.65 (0.00, 1.00)	Odds ratio	1.06 (1.02, 1.10)	<0.01	0.99 (0.95, 1.04)	0.69
C:D OS (0.10)	653	0.60 (0.00, 1.00)	3849	0.65 (0.00, 1.00)	Odds ratio	1.07 (1.03, 1.11)	<0.01	1.00 (0.96, 1.04)	0.93
C:D mean (0.10)	648	0.60 (0.00, 1.00)	3797	0.65 (0.00, 1.00)	Odds ratio	1.08 (1.04, 1.12)	<0.01	1.00 (0.95, 1.05)	0.92
Total Number of Drops	682		3971		Odds ratio	1.29 (1.18, 1.40)	<0.01	1.08 (0.99, 1.18)	0.08
0		471 (69.1%)		2228 (56.1%)
1		100 (14.7%)		795 (20.0%)
2		62 (9.1%)		459 (11.6%)
3		38 (5.6%)		324 (8.2%)
4		11 (1.6%)		155 (3.9%)
5		0 (0.0%)		10 (0.3%)
Drops 1+	682	211 (30.9%)	3971	1743 (43.9%)	Odds ratio	1.75 (1.47, 2.08)	<0.01	1.20 (0.99, 1.45)	0.07
Incisional Glaucoma Surgery	682	40 (5.9%)	3971	333 (8.4%)	Odds ratio	1.47 (1.05, 2.06)	0.03	1.07 (0.74, 1.53)	0.73
Minor Glaucoma Procedure	682	48 (7.0%)	3971	373 (9.4%)	Odds ratio	1.37 (1.00, 1.87)	<0.05	1.08 (0.77, 1.50)	0.66
CCT OD (20 μm)	306	551.5 (435.0, 649.0)	1841	557.0 (409.0, 740.0)	Odds ratio	1.07 (1.01, 1.14)	0.03	1.09 (1.02, 1.17)	0.01
CCT OS (20 μm)	307	554.0 (440.0, 658.0)	1840	558.0 (379.0, 812.0)	Odds ratio	1.07 (1.00, 1.13)	0.04	1.09 (1.02, 1.16)	0.01
CCT mean (20 μm)	305	553.0 (437.5, 647.0)	1834	557.3 (394.0, 718.5)	Odds ratio	1.07 (1.00, 1.14)	0.04	1.09 (1.02, 1.17)	0.01
VFMD OD (1 dB)	138	0.2 (−20.3, 4.3)	412	−0.5 (−29.2, 3.3)	Odds ratio	0.94 (0.90, 0.99)	0.01	0.97 (0.92, 1.02)	0.29
VFMD OS (1 dB)	139	−0.4 (−27.0, 2.9)	408	−0.9 (−30.0, 5.0)	Odds ratio	0.95 (0.90, 0.99)	0.02	0.97 (0.92, 1.02)	0.26
VFMD mean (1 dB)	138	−0.2 (−16.3, 3.1)	406	−0.7 (−27.5, 3.7)	Odds ratio	0.93 (0.89, 0.98)	0.01	0.97 (0.91, 1.03)	0.26
RNFL OD (10 μm)	207	83.0 (50.0, 147.0)	1057	79.0 (37.0, 133.0)	Odds ratio	0.78 (0.70, 0.88)	<0.01	0.97 (0.85, 1.10)	0.61
RNFL OS (10 μm)	208	83.0 (50.0, 143.0)	1061	78.0 (30.0, 124.0)	Odds ratio	0.78 (0.70, 0.87)	<0.01	0.89 (0.79, 1.01)	0.07
RNFL mean (10 μm)	207	82.5 (56.0, 123.5)	1048	78.0 (41.0, 126.0)	Odds ratio	0.74 (0.66, 0.84)	<0.01	0.91 (0.60, 1.05)	0.20

CI=confidence interval. Logistic regression model.

VA and VFMD analyses exclude patients with cataract, macular degeneration, other forms of optic neuropathy, retinal vascular occlusion, and proliferative diabetic retinopathy

RNFL analysis excludes patients with other forms of optic neuropathy, retinal vascular occlusion, and proliferative diabetic retinopathy

There was not a statistically significant difference between patients with and without MetS that were using IOP lowering drops (43.9% vs 30.9%, P = 0.07), underwent a glaucoma procedure (9.4% vs 7.0%, P = 0.66) or incisional glaucoma surgery (8.4% vs 5.9%, P = 0.73). There was no significant difference in VFMD in patients with and without MetS (−0.7 vs −0.2, P = 0.26). In analysis of RNFL, there was no significant difference between patients with and without MetS (78.0 μm vs 82.5 μm, P = 0.20).

Patients with GON were more likely to be prescribed a medication for systemic hypertension (OR 1.66, P < 0.01) and for dyslipidemia (OR 1.45, P < 0.01) compared to patients without GON (Table 8). The association for both medication classes lost significance, however, when adjusted for demographics. There was no significant association between GON and medication for hyperglycemia and hypertriglyceridemia, whether or not the results were demographically adjusted.

Table 8: Association between Medications and Glaucomatous Optic Neuropathy.

Likelihood of glaucomatous optic neuropathy in association with concurrent treatment for hyperglycemia, systemic hypertension, dyslipidemia, and hypertriglyceridemia.

						Unadjusted analysis		Adjusting for age, sex, race (white vs. non-white), and smoking history
Association examined	N	Median (minimum, maximum) or No. (%) for the given group	N		Association measure	Estimate (95% CI)	P-value	Estimate (95% CI)	P-value
Association between glaucoma and:		No Glaucoma (N=33633)		Glaucoma (N=4653)
Medication for Hyperglycemia	33633	6669 (19.8%)	4653	931 (20.0%)	Odds ratio	1.01 (94, 1.09)	0.77	0.97 (0.89, 1.05)	0.46
Medication for Hypertension	33633	19643 (58.4%)	4653	3258 (70.0%)	Odds ratio	1.66 (1.56, 1.78)	<0.01	1.05 (0.97, 1.13)	0.21
Medication for Dyslipidemia	33633	16805 (50.0%)	4653	2753 (59.2%)	Odds ratio	1.45 (1.36, 1.54)	<0.01	1.05 (0.98, 1.12)	0.18
Medication for Hypertriglyceridemia	33633	1523 (4.5%)	4653	202 (4.3%)	Odds ratio	0.96 (0.82, 1.11)	0.57	0.99 (0.84, 1.15)	0.87

CI=confidence interval. Logistic regression model.

For patients with GON, those with MetS and no history of IOP-lowering treatment had a significantly thicker average CCT than those with MetS on IOP-lowering treatment (561.8 μm vs 554.4 μm, P < 0.001) and those without MetS on IOP-lowering treatment (561.8 μm vs 551.3 μm, P < 0.001) (Table 9). Patients with MetS and no history of IOP-lowering treatment also had significantly higher CCT than patients without MetS and no history of IOP-lowering treatment (561.8 μm vs 555.0 μm, P = 0.03), but this lost significance once adjusted for demographic variables (P = 0.09). Patients with MetS and IOP-lowering treatment also had thicker CCT than patients without MetS on IOP-lowering treatment, when adjusted for demographic factors (554.5 μm vs 551.3 μm, P = 0.04).

Table 9: Comparison of Central Corneal Thickness by Presence of Metabolic Syndrome and Treatment.

Central corneal thickness in patients with glaucomatous optic neuropathy and ocular hypertension, broken down by presence of metabolic syndrome and treatment.

			Unadjusted			Adjusting for age, sex, race (white vs. non-white), and smoking history
Group	N	Median (minimum, maximum) CCT mean (20 μm)	No MetS, treatment	MetS, no treatment	MetS, treatment	No MetS, treatment	MetS, no treatment	MetS, treatment
Glaucomatous optic neuropathy
No MetS, no treatment	149	555.0 (456.0, 647.0)	0.17	0.03	0.78	0.12	0.09	0.90
No MetS, treatment	156	551.3 (437.5, 646.0)	----	<0.001	0.15	----	<0.001	0.04
MetS, no treatment	636	561.8 (430.5, 718.5)	----	----	<0.001	----	----	<0.001
MetS, treatment	1198	554.5 (394.0, 704.5)	----	----	----	----	----	----
Ocular hypertension
No MetS, no treatment	40	570.8 (482.5, 670.0)	0.61	0.26	0.65	0.33	0.11	0.76
No MetS, treatment	55	565.0 (478.0, 678.5)	----	0.04	0.80	----	0.02	0.28
MetS, no treatment	231	580.0 (481.0, 708.5)	----	----	0.003	----	----	0.04
MetS, treatment	258	573.5 (465.0, 733.0)	----	----	----	----	----	----

P-values result from logistic regression models.

Once the IOP was adjusted for CCT using all five formulas, there was no significant association between IOP and MetS in patients with GON, both without correction for demographics (P ≥ 0.07) and with correction for demographics (P ≥ 0.14) (Table 10).

Table 10: Intraocular pressure adjusted by central corneal thickness.

Intraocular pressure measurements adjusted by central corneal thickness, using five different formulas, in patients with glaucomatous optic neuropathy and patients with ocular hypertension.

						Unadjusted analysis		Adjusting for age, sex, race (white vs. non-white), and smoking history
Association between metabolic syndrome and:	N	Median (minimum, maximum) or No. (%) for the given group	N		Association measure	Estimate (95% CI)	P-value	Estimate (95% CI)	P-value
		No Metabolic Syndrome		Metabolic Syndrome
Glaucomatous optic neuropathy
CCT adjusted IOP mean (5 mmHg)36	301	12.2 (1.5, 24.3)	1825	11.7 (−1.7, 58.4)	Odds ratio	0.88 (0.77, 1.01)	0.07	1.02 (0.87, 1.19)	0.84
CCT adjusted IOP mean both eyes (5 mmHg)39	301	13.8 (5.2, 26.9)	1825	13.5 (2.8, 61.7)	Odds ratio	0.92 (0.79, 1.07)	0.29	1.15 (0.96, 1.38)	0.14
CCT adjusted IOP mean both eyes (5 mmHg)35	301	13.6 (4.2, 26.0)	1825	13.3 (1.9, 60.6)	Odds ratio	0.89 (0.77, 1.03)	0.11	1.07 (0.90, 1.27)	0.48
CCT adjusted IOP mean both eyes (5 mmHg)37	301	14.4 (5.4, 27.0)	1825	14.0 (2.8, 61.6)	Odds ratio	0.89 (0.77, 1.04)	0.14	1.09 (0.91, 1.30)	0.36
CCT adjusted IOP mean both eyes (5 mmHg)38	301	15.5 (5.8, 28.3)	1825	15.1 (3.2, 62.5)	Odds ratio	0.91 (0.79, 1.05)	0.18	1.10 (0.93, 1.30)	0.28
Ocular hypertension
CCT adjusted IOP mean both eyes (5 mmHg)36	95	13.5 (2.7, 30.2)	489	13.8 (2.0, 36.3)	Odds ratio	1.01 (0.80, 1.28)	0.95	1.09 (0.83, 1.41)	0.54
CCT adjusted IOP mean both eyes (5 mmHg)39	95	16.0 (6.2, 28.3)	489	16.8 (5.8, 35.3)	Odds ratio	1.08 (0.83, 1.42)	0.56	1.30 (0.95, 1.77)	0.10
CCT adjusted IOP mean both eyes (5 mmHg)35	95	15.3 (4.9, 30.1)	489	15.9 (4.8, 36.2)	Odds ratio	1.04 (0.80, 1.34)	0.79	1.17 (0.87, 1.55)	0.30
CCT adjusted IOP mean both eyes (5 mmHg)37	95	16.2 (5.9, 30.4)	489	16.8 (5.7, 36.4)	Odds ratio	1.05 (0.81, 1.36)	0.73	1.20 (0.89, 1.61)	0.23
CCT adjusted IOP mean both eyes (5 mmHg)38	95	17.5 (7.4, 35.5)	489	18.0 (7.0, 43.4)	Odds ratio	1.03 (0.80, 1.32)	0.83	1.16 (0.87, 1.55)	0.30

CI=confidence interval. Logistic regression model.

Patients with OHTN

1,483 patients had OHTN, including 1,296 (87.4%) with MetS and 187 (12.6%) without MetS (Table 11). In patients with OHTN, patients with MetS were more likely to be older than those without (69.3.1 vs 64.0, P < 0.01). There was a trend toward a higher percentage of females in the non-MetS group, but this was not statistically significant (53.9% vs 61.0%, P = 0.07). There was no difference in self-identified white race between those with and those without MetS in this cohort (91.8% vs 90.3%, P = 0.50). Patients without MetS were more likely to never have used tobacco than patients with MetS (90.7% vs 81.2%, P < 0.01).

Table 11: Demographics of Patients with Ocular Hypertension.

Demographics of patients with ocular hypertension as broken down by presence of metabolic syndrome.

	No Metabolic Syndrome (N=187)	Metabolic Syndrome (N=1296)	Total (N=1483)	P-value
Age				<0.011
N	187	1296	1483
Mean (SD)	64.0 (11.94)	69.3 (12.52)	68.6 (12.57)
Median (Range)	63.0 (42.0, 96.0)	69.0 (40.0, 103.0)	68.0 (40.0, 103.0)
Sex, N (%)				0.072
Female	114 (61.0%)	699 (53.9%)	813 (54.8%)
Male	73 (39.0%)	597 (46.1%)	670 (45.2%)
White race, N (%)				0.502
No	18 (9.7%)	106 (8.2%)	124 (8.4%)
Yes	168 (90.3%)	1179 (91.8%)	1347 (91.6%)
Missing	1	11	12
Smoking History, N (%)				<0.012
Never	156 (90.7%)	990 (81.2%)	1146 (82.4%)
Former/Current	16 (9.3%)	229 (18.8%)	245 (17.6%)
Missing	15	77	92

¹Wilcoxon rank sum p-value

²Chi-Square p-value

Patients with MetS were more likely to have a diagnosis of OHTN, with OR of 1.89 (P < 0.01) (Table 6). After adjusting for demographics, the OR remained significant at 1.66 (P < 0.01). The adjusted OR for OHTN as related to number of MetS components was 1.18 (P < 0.01).

After adjustment for demographic factors, there was no significant difference in mean VA between patients with MetS and those without (0.0 vs 0.0, P = 0.17) (Table 12). When adjusted for demographic factors, there was no difference in mean IOP between patients with and without MetS (17.5 mmHg vs 17.5 mmHg, P =0.18). There was no significant difference in mean CCT in patients with or without MetS (576 μm vs 569 μm, P = 0.06). The mean C:D was slightly higher in patients without MetS (0.45 vs 0.40, P < 0.01).

Table 12: Eye Exam and Treatment in Patients with Ocular Hypertension.

Findings on eye exam, testing results, and treatment of patients with ocular hypertension as broken down by presence of metabolic syndrome

						Unadjusted analysis		Adjusting for age, sex, race (white vs. non-white), and smoking history
Association between metabolic syndrome and:	N	Median (minimum, maximum) or No. (%)	N	Median (minimum, maximum) or No. (%)	Association measure	Estimate (95% CI)	P-value	Estimate (95% CI)	P-value
		No Metabolic Syndrome (N=187)		Metabolic Syndrome (N=1296)
VA OD (0.1 logMAR unit)	94	0.0 (−0.1, 0.5)	393	0.0 (−0.1, 5.0)	Odds ratio	1.27 (1.00, 1.63)	0.06	1.12 (0.88, 1.42)	0.37
VA OS (0.1 logMAR unit)	96	0.0 (−0.1, 0.8)	393	0.0 (−0.1, 5.0)	Odds ratio	1.22 (0.98, 1.51)	0.08	1.19 (0.95, 1.50)	0.14
VA mean (0.1 logMAR unit)	94	0.0 (−0.1, 0.7)	392	0.0 (−0.1, 3.0)	Odds ratio	1.31 (1.01, 1.70)	0.05	1.20 (0.92, 1.56)	0.17
IOP OD (5 mmHg)	184	18.0 (8.0, 39.0)	1236	18.0 (3.0, 52.0)	Odds ratio	0.98 (0.82, 1.17)	0.82	1.06 (0.87, 1.30)	0.55
IOP OS (5 mmHg)	184	17.0 (2.0, 30.0)	1237	18.0 (1.0, 37.0)	Odds ratio	1.11 (0.92, 1.33)	0.30	1.23 (1.00, 1.52)	0.05
IOP mean (5 mmHg)	183	17.5 (7.5, 30.0)	1229	17.5 (2.0, 36.0)	Odds ratio	1.05 (0.86, 1.27)	0.66	1.16 (0.94, 1.45)	0.18
C:D OD (0.10)	173	0.40 (0.10, 0.95)	1247	0.40 (0.00, 1.00)	Odds ratio	0.95 (0.88, 1.02)	0.17	0.91 (0.83, 0.99)	<0.01
C:D OS (0.10)	175	0.40 (0.10, 1.00)	1241	0.40 (0.00, 1.00)	Odds ratio	0.90 (0.84, 0.97)	<0.01	0.86 (0.79, 0.94)	<0.01
C:D mean (0.10)	172	0.45 (0.10, 0.98)	1227	0.40 (0.00, 1.00)	Odds ratio	0.92 (0.85, 0.99)	0.03	0.87 (0.79, 0.95)	<0.01
Total Number of Drops	187		1296		Odds ratio	0.89 (0.77, 1.03)	0.13	0.85 (0.73, 1.00)	<0.05
0		119 (63.6%)		897 (69.2%)
1		38 (20.3%)		218 (16.8%)
2		14 (7.5%)		92 (7.1%)
3		8 (4.3%)		66 (5.1%)
4		8 (4.3%)		21 (1.6%)
5		0 (0.0%)		2 (0.2%)
Drops 1+	187	68 (36.4%)	1296	399 (30.8%)	Odds ratio	0.78 (0.57, 1.07)	0.13	0.70 (0.49, 1.00)	<0.05
Incisional Glaucoma Surgery	187	10 (5.3%)	1296	31 (2.4%)	Odds ratio	0.43 (0.21, 0.90)	0.03	0.38 (0.17, 0.83)	0.02
Minor Glaucoma Procedure	187	12 (6.4%)	1296	37 (2.9%)	Odds ratio	0.43 (0.22, 0.84)	0.01	0.42 (0.21, 0.87)	0.02
CCT OD (20 μm)	95	567.0 (477.0, 686.0)	493	576.0 (462.0, 685.0)	Odds ratio	1.02 (0.92, 1.14)	0.68	1.08 (0.96, 1.22)	0.20
CCT OS (20 μm)	95	569.0 (476.0, 674.0)	492	576.0 (446.0, 816.0)	Odds ratio	1.08 (0.97, 1.20)	0.14	1.15 (1.02, 1.29)	0.02
CCT mean (20 μm)	95	569.5 (478.0, 678.5)	489	576.5 (465.0, 733.0)	Odds ratio	1.06 (0.95, 1.18)	0.31	1.12 (0.99, 1.27)	0.06
VFMD OD (1 dB)	45	0.4 (−26.7, 9.4)	126	0.0 (−12.5, 3.5)	Odds ratio	1.00 (0.90, 1.11)	0.94	1.02 (0.91, 1.14)	0.76
VFMD OS (1 dB)	46	−0.4 (−8.9, 3.2)	125	−0.2 (−30.6, 3.9)	Odds ratio	0.91 (0.81, 1.04)	0.16	0.89 (0.78, 1.03)	0.11
VFMD mean (1 dB)	45	0.0 (−14.8, 4.1)	124	−0.3 (−16.6, 3.7)	Odds ratio	0.94 (0.83, 1.07)	0.35	0.94 (0.83, 1.07)	0.36
RNFL OD (10 μm)	59	84.0 (54.0, 139.0)	282	83.0 (44.0, 116.0)	Odds ratio	0.92 (0.73, 1.15)	0.44	0.96 (0.76, 1.22)	0.76
RNFL OS (10 μm)	59	83.0 (54.0, 110.0)	280	81.0 (42.0, 114.0)	Odds ratio	0.93 (0.74, 1.16)	0.52	0.98 (0.76, 1.26)	0.86
RNFL mean (10 μm)	59	82.5 (57.5, 112.0)	279	82.0 (43.0, 113.5)	Odds ratio	0.91 (0.71, 1.17)	0.45	0.97 (0.74, 1.27)	0.80

CI=confidence interval. Logistic regression model.

VA and VFMD analyses exclude patients with cataract, macular degeneration, other forms of optic neuropathy, retinal vascular occlusion, and proliferative diabetic retinopathy

RNFL analysis excludes patients with other forms of optic neuropathy, retinal vascular occlusion, and proliferative diabetic retinopathy

Patients without MetS were statistically more likely to be using at least one topical IOP lowering agent (36.4% vs 30.8%, P < 0.05, Table 12), undergo a glaucoma procedure (6.4% vs 2.9%, P = 0.02), and undergo incisional glaucoma surgery (5.3% vs 2.4%, P =0.02). We did not find a significant difference in VFMD between patients with and without MetS (−0.3 vs 0.0 P = 0.36). We also found no difference in RNFL between patients with and without MetS (82.0 μm vs 82.5 μm, P = 0.80).

In patients with OHTN, the average CCT in patients with MetS without history of IOP treatment was significantly higher than the average CCT in patients with MetS with history of IOP treatment (580 μm vs 573.5 μm), both before (P < 0.01) and after adjustment for demographic variables (P = 0.04) (Table 9). Patients with MetS and without IOP-lowering treatment also had significantly thicker CCT compared to patients without MetS on IOP-lowering treatment (580.0 μm vs 565.0 μm, P = 0.04), even after adjustment for demographic factors (P = 0.02).

In patients with OHTN, the CCT adjusted IOP using five formulas was not significantly different between patients with and without MetS (P ≥ 0.56 ), and this held true after multifactorial adjustment for demographics (P ≥ 0.10) (Table 10).

Discussion

Our study examined the association of GON and OHTN with MetS in Olmsted County, MN. In our study, patients with MetS were more likely to be older and male than those without, consistent with prior data.^45–47 Since age and sex are each potential risk factors for OHTN and GON,^{48, 49} it was necessary to adjust for both variables in our study. It is also already known that race is a risk factor in GON, with black patients having greater prevalence and more severe GON,⁵⁰ but the relationship between tobacco use and GON is less clear, with current evidence showing a weak causal association, if any.^{51, 52} Nevertheless, we adjusted our data for tobacco use given the significant difference between patients with and without MetS. In our study, after adjusting for these demographic factors, GON, as defined by diagnosis code, was not associated with MetS. An increasing number of MetS components was also not associated with GON, as defined by diagnosis code. Patients with GON and MetS, however, did have higher IOP and CCT than those without MetS. Although MetS was associated with higher IOP in patients with GON, it was not associated with higher rates of treatment or more severe disease as measured by C:D, VFMD, and RNFL.

Both before and after adjustment for demographic factors, patients with MetS were more likely to have OHTN, as defined by diagnosis code. Furthermore, increasing numbers of MetS components was also associated with OHTN. Patients with a diagnosis of OHTN would be expected to have optic nerve structure and function within normal limits. Consistent with this, patients in our study had little to no evidence of GON as assessed by VFMD and RNFL. Interestingly, patients with OHTN and without MetS had higher C:D and higher rate of treatment compared to patients with MetS.

A limited body of literature suggests an association between MetS and GON,²⁹ which is not consistent with this study. There are, however, notable differences between our study and prior reports including study design, exclusion criteria, definitions of disease, and patient demographics. For example, some studies defined their patient population by MetS and then looked for an association with GON,^{9, 11, 53} as we did, while other studies began with patients with GON and then looked for an association with MetS.^{10, 12} Another variable was the time course over which patients were followed. Our study encompassed all available data over the study period to assess for MetS based on laboratory values, medication use, and/or diagnosis code of individual components of MetS, rather than strictly a diagnosis of MetS by diagnosis code, with subsequent eye exams to look for current or newly diagnosed GON. Only one prior study on MetS and GON was longitudinal,⁹ which is important in assessing the relationship between two chronic and potentially asymptomatic diseases. Another major difference was that of the available studies, the majority excluded patients with pre-existing GON ^{9, 10} or OHTN,¹³ while we included these patient populations. Finally, prior studies were inconsistent in their exclusion of other ocular comorbidities, as some did not assess for ocular comorbidities,^{9, 11, 53} while others excluded patients on the basis of prior intraocular surgery.^{10, 12} Only one study excluded patients with AMD and diabetic retinopathy.¹⁰ MetS or its components are associated with increased risk of RVO,⁵⁴ diabetic retinopathy,⁵⁵ non-glaucomatous optic neuropathy,⁵⁶ and macular degeneration.⁵⁷ Therefore, since these ocular comorbidities may affect the VFMD and OCT RNFL and confound the diagnosis of GON, prior studies that did not exclude these diagnoses may be difficult to interpret.

Another important distinction in our study is that our patient population is primarily of European descent, with 90% identifying as white, in contrast to the predominantly Korean population in many of the prior studies.^{9–11, 13} The prevalence of obesity in North America (30%) is about 6 times higher than that of East Asia (5%).⁵⁸ This is in part related to the differences in dietary habits. Consumption of Western diets, which contain high amounts of processed foods including meats and sugars, with fewer vegetables, grains, nuts, and fish, are associated with systemic hypertension, abnormal cholesterol levels,⁵⁹ obesity,⁶⁰ cardiovascular disease,⁵⁹ diabetes, and MetS.³¹ Furthermore, NTG is more common in Asian populations, including Koreans, than Caucasians.⁶¹ MetS may also have a differing phenotype across ethnic groups, as Asian populations have a lower cutoff for WC.⁶² It is possible that these differences between the European and Asian lifestyle and phenotype result in modification of any association between MetS and GON.

Because MetS is a definable endpoint for assessing a patient’s overall health status, pharmacologic intervention is often used to treat the components of MetS. Therefore, medications used in the treatment of components of MetS may be confounding variables in the assessment of risk attributed to MetS. For example, prior studies have suggested that metformin, statins, angiotensin converting enzyme inhibitors, and angiotensin receptor blockers reduce the risk of GON.^63–65 These medications are all used to treat systemic associations of MetS, and thus, it is possible that any true association between MetS and GON was obscured by concurrent systemic treatment. To further explore the potential interaction between medications and GON, we assessed prevalence of GON in patients, as broken down by prescription of medications for components of MetS. Once adjusted for age, sex, race, and tobacco use, we did not find a significant association between treatment for components of MetS and GON (data not shown). Our study was not designed or powered to examine whether systemic medications modify the risk of GON, but this data suggests that medications likely did not influence the overall relationship between GON and MetS.

The existing literature on the relationship between OHTN and MetS is more extensive and consistent in showing that patients with MetS have a higher IOP.²⁹ Our data is in line with other studies showing that MetS is associated with OHTN by diagnosis code.

Patients with GON and MetS also had higher CCT than patients without MetS, and patients with OHTN and MetS trended toward higher CCT than patients without MetS. These findings are consistent with other studies linking MetS to thicker CCT^{12, 33}, but this was not duplicated in a general population without GON or OHTN.³² Since CCT influences IOP readings, it was unclear whether the significant difference in CCT between those with and without MetS in the GON cohort explained the difference in IOP.³⁵ To assess the potential impact of CCT on IOP, we used previously published formulas that adjust IOP based on CCT.^35–39 After IOP was adjusted for CCT, there was no significant association between MetS and adjusted IOP in patients with GON and patients with OHTN. Thus, our data suggests that the primary driver of increased IOP in patients with MetS is increased CCT. Prior studies suggested that MetS was associated with increased IOP, but CCT was not reported.^{15–25, 27, 66, 67} Further studies are needed to assess the relationship between MetS and CCT, including for patients where IOP correction based on CCT may be challenging, including those with particularly thick or thin corneas, history of refractive surgery, or other corneal conditions that may affect the measurement of CCT.

Though in our study, CCT appears to play a major role in higher IOP in patients with MetS, it is possible that there are other factors that may lead to an increase in IOP in similar patient populations. For example, obese patients have been found to have larger volumes of retrobulbar adipose tissue and higher IOP,⁶⁸ Additionally, obese patients have increased IOP as measured by Goldman applanation tonometry, secondary to difficulty positioning at the slit lamp.⁶⁹ Our study recorded IOP that was taken by various forms of tonometry, which do not all require positioning at the slit lamp, so it is unclear how this may have impacted the results.

Another hypothesis of this study was that patients with MetS would have more severe GON compared to patients without MetS. After adjustment for demographic factors, we did not find that there was a significant difference in C:D, treatment rate, VFMD, or RNFL between patients with and without MetS. In the analysis of the VFMD and RNFL metrics, we did differentially exclude patients with ocular comorbidities. We did this because there is evidence that MetS or its components are associated with cataract,^70–72 AMD,⁵⁷ non-glaucomatous optic neuropathy,⁵⁶ RVO,⁵⁴ and PDR,⁵⁵ and these ocular comorbidities will impact VFMD and RNFL. With these exclusions, we did not find that MetS was associated with worse optic nerve damage in patients with GON.

In patients with OHTN, those without MetS were more likely to be treated for their elevated IOP, as evidenced by greater use of glaucoma drops, greater chance of glaucoma procedure, and greater chance of incisional glaucoma surgery. Patients with OHTN and without MetS also had a higher C:D, but there was no significant difference in VFMD or RNFL between patients with and without MetS. These findings are difficult to explain since there was no difference in measured IOP. One possible explanation is that a subset of patients with MetS progressed from OHTN to GON and were no longer categorized in the OHTN group, even though when taken as group, MetS was not associated with GON. Alternatively, since the CCT trended higher patients with MetS and OHTN, it is also possible that clinicians deemed these patients lower risk for conversion to GON and therefore were treated less aggressively. Patients without MetS with IOP lowering treatment had the lowest CCT, while patients with MetS without IOP lowering treatment had the highest CCT. This was a statistically significant difference, which suggests a potential explanation for the differences in treatment in ocular hypertensive patients with and without MetS. This trend of higher CCT in patients with MetS without IOP lowering treatment was also demonstrated in the GON cohort, which emphasizes the likely impact of CCT on risk stratification.

The Ocular Hypertension Treatment Study, suggested that diabetes mellitus was protective in the progression of OHTN to GON, while systemic HTN had no significant effect.⁷³ Therefore, since diabetes mellitus is a component of MetS, it is possible that the protective effect of conversion from OHTN to GON seen in some populations and some studies may at least partially explain the difference in IOP treatment of patients with and without MetS. It remains unclear what role other components of MetS or MetS itself may have in the natural history of OHTN and progression to GON.

Our study identified 78% of people age 40 or older with MetS based on laboratory criteria, medication use, and diagnosis codes. Our preliminary data suggested an underestimation of identifying MetS simply by diagnosis code, and other large studies on the prevalence of MetS have also used preexisting bloodwork and medical treatment to diagnose MetS.^{45, 46} Therefore, we chose to employ a more vigorous approach to capture every patient that met the defined criteria of MetS, as the true defined syndrome may be missed clinically. In trying to capture all patients with MetS, only patients with available bloodwork were included, which may have selected for a population more likely to have diagnoses related to components of MetS.

Our findings on the prevalence of MetS and its components reveal a higher disease burden compared to other population-based studies. One study from 1999–2014 showed a MetS prevalence of 47% for people aged 40–65 living in a 7 state region that includes Olmsted County, which was one of the highest in the country.⁴⁴ Given that our population is older, with 63% of patients at least 60 years-old, and that our study period is more recent, it is not surprising that we found a higher prevalence of MetS. Our data is concordant with other studies in terms of central adiposity, as 76.8% of our population had a BMI of at least 27 kg/m², and the mean BMI in the United States is around 29 kg/m².⁴⁷ Although there is data to support using BMI as a surrogate of adiposity for WC,⁷⁴ other studies have indicated that BMI is more useful for screening and its negative predictive value for cardiovascular disease,⁷⁵ rather than for its positive predictive value.^{76, 77} Thus, it is possible that using BMI as a substitute for WC overestimated the population’s prevalence of MetS and overall cardiovascular risk. Our prevalence of systemic HTN was 83%, compared to 42.1% in women and 49.1% in men in another study, but the average age of their patients was 20 years younger and systemic HTN only increases with age.⁴⁷

This study is limited by being a retrospective chart review, where it is subject variation regarding provider documentation of the exam, billing, and diagnoses. To validate diagnostic codes for identifying patients with GON and OHTN, we compared patients with MetS and GON to patients with MetS and OHTN (Table 13). As expected, the mean C:D in patients with GON was significantly larger than those with OHTN, while the mean IOP was significantly lower in patients with GON, likely related to medical or surgical treatment of the disease. Patients with GON were statistically more likely to use topical glaucoma treatment, more likely to undergo a glaucoma procedure, and more likely to have had an incisional glaucoma surgery. Furthermore, patients with GON did demonstrate greater evidence of optic nerve damage than their OHTN counterparts, with lower mean VFMD and lower mean RNFL. These findings support accurate distinguishing between GON and OHTN by diagnostic billing codes in this retrospective study.

Table 13: Glaucomatous Optic Neuropathy and Ocular Hypertension in Patients with Metabolic Syndrome.

Comparison of findings on eye exam, testing results, and treatment of glaucomatous optic neuropathy and ocular hypertension in patients with metabolic syndrome.

						Unadjusted analysis		Adjusting for age, sex, race (white vs. non-white), and smoking history
Association between glaucoma vs. ocular hypertension and:	N	Median (minimum, maximum) or No. (%) for the given group	N	Median (minimum, maximum) or No. (%) for the given group	Association measure	Estimate (95% CI)	P-value	Estimate (95% CI)	P-value
		Glaucoma (N=3971)		Ocular Hypertension (N=1296)
VA mean (0.1 logMAR unit)	3671	0.1 (−0.1, 5.0)	1186	0.1 (−0.1, 5.0)	Odds ratio	1.04 (1.03, 1.06)	<0.01	1.02 (1.00, 1.03)	0.04
IOP mean (5 mmHg)	3785	15.0 (2.5, 63.0)	1229	17.5 (2.0, 36.0)	Odds ratio	0.44 (0.40, 0.48)	<0.01	0.46 (0.42, 0.51)	<0.01
C:D mean (0.10)	3797	0.65 (0.00, 1.00)	1227	0.40 (0.00, 1.00)	Odds ratio	1.62 (1.56, 1.68)	<0.01	1.59 (1.53, 1.65)	<0.01
Total Number of Drops	3971		1296		Odds ratio	1.32 (1.24, 1.41)	<0.01	1.22 (1.14, 1.31)	<0.01
0		2228 (56.1%)		897 (69.2%)
1		795 (20.0%)		218 (16.8%)
2		459 (11.6%)		92 (7.1%)
3		324 (8.2%)		66 (5.1%)
4		155 (3.9%)		21 (1.6%)
5		10 (0.3%)		2 (0.2%)
Drops 1+	3971	1743 (43.9%)	1296	399 (30.8%)	Odds ratio	1.76 (1.54, 2.01)	<0.01	1.48 (1.28, 1.71)	<0.01
Incisional Glaucoma Surgery	3971	333 (8.4%)	1296	31 (2.4%)	Odds ratio	3.74 (2.57, 5.43)	<0.01	3.08 (2.10, 4.52)	<0.01
Minor Glaucoma Procedure	3971	373 (9.4%)	1296	37 (2.9%)	Odds ratio	3.53 (2.50, 4.97)	<0.01	3.15 (2.21, 4.50)	<0.01
CCT mean (20 μm)	1834	557.3 (394.0, 718.5)	489	576.5 (465.0, 733.0)	Odds ratio	0.79 (0.75, 0.84)	<0.01	0.81 (0.76, 0.85)	<0.01
VFMD mean (1dB)	1338	−2.3 (−31.2, 4.8)	337	−1.2 (−30.0, 3.7)	Odds ratio	0.94 (0.91, 0.96)	<0.01	0.95 (0.93, 0.98)	<0.01
RNFL mean (10 μm)	1149	78.0 (41.0, 135.5)	305	82.0 (43.0, 113.5)	Odds ratio	0.81 (0.73, 0.90)	<0.01	0.85 (0.76, 0.95)	<0.01

CI=confidence interval. Logistic regression model.

Since this is a retrospective study, we cannot demonstrate any causation or account for unknown confounding factors in how MetS relates to GON and OHTN. Our IOP measurements were also limited by being a mix of treated and untreated values, so we could not determine what effect MetS has on pre-treatment IOP values. We did not exclude any measurements of VFMD or RNFL for unreliability or poor quality. We also recognize that our cohort of patients may not capture all patients with GON or OHTN, since they may be managed by local optometrists outside the REP. This could bias our cohort toward more advanced and complex ocular disease.

In summary, though patients with MetS were not more likely to have GON than those without MetS, patients with GON and MetS had higher IOP and CCT than those without MetS. Once IOP was adjusted for CCT, however, there was no difference in IOP between patients with and without MetS, suggesting that a difference in CCT may be the reason for increased IOP in MetS patients. Patients with MetS were more likely to have OHTN than patients without MetS. Our study supports prior evidence that MetS is associated with OHTN and also suggests that this may be related to increased CCT. Further population-based studies are needed to determine how MetS impacts CCT, IOP, and risk for OHTN and GON.