Gender Difference in Intraocular Pressure and Incidence of Metabolic Syndrome: A Community-Based Cohort Study in Matsu,Taiwan

Abstract

Background:

We aimed to assess the effect of intraocular pressure (IOP) on incident metabolic syndrome (MetS) using a longitudinal follow-up of screening cohort in contrast to most of previous studies addressing the association between both.

Methods:

The empirical data were derived from a community-based integrated screening program in Matsu during the period 2003 to 2010. A total of 1347 participants older than 30 years were enrolled in this study. With the enrollment of 1056 participants with MetS free at baseline, the cohort with IOP measurement in 2003 were followed up over time to identify incident MetS to elucidate the temporal sequence of both.

Results:

The statistically significant effect noted was that elevated IOP (≥15 mmHg vs. <15 mmHg) had 1.46-fold risk for developing incident MetS (adjusted relative ratio [aRR]: 1.46; 95% confidence interval [CI]: 1.08–1.99) for both sex combined, particularly in men (aRR: 1.66; 95% CI: 1.13–2.45) but not in women. The finding that elevated IOP occurred before the presence of high blood pressure was noted in both men and women, whereas men with elevated IOP may be concomitant with more individual components (severity) of MetS earlier than women with elevated IOP.

Conclusions:

Elevated IOP leading to the risk for incident or severe MetS was noted in men but not in women. Evidence on this temporal sequence revealed the possibility of showing signs of elevated IOP before the development of MetS, which indicates the necessity of monitoring IOP in routine health check-up for prevention of MetS-related chronic diseases.

Introduction

Elevated intraocular pressure (IOP), a major risk factor for glaucoma that is one of leading causes of blindness, has been reported to be associated with metabolic syndrome (MetS)^1,2 and its related individual components such as insulin resistance³ and blood pressure (BP).⁴ Such associations have been postulated to be attributed to hyperactivation of ocular sympathetic nerve⁵ or the influence of estrogen on the target tissues in the eye^6,7 according to the disparity of findings on menopause.⁸ However, the true biological causes accounting for such an association are still elusive.

Despite this, it is still worthwhile to get a better understanding of how MetS is concomitant with eye-related diseases and also associated with the elevated IOP because the clarification of temporal sequence between the elevated IOP and MetS may provide a new insight into the surveillance of IOP-related eye diseases and MetS-related chronic diseases. If the elevated IOP is antecedent before the manifestation of MetS, the elevated IOP may be used as surveillance marker for monitoring the subjects susceptible to MetS, whereas if MetS occurs before the elevated IOP these factors composed of MetS would become an early precursor for monitoring IOP-related diseases such as glaucoma. It is difficult to disentangle this temporal sequence by using a cross-sectional study design that was adopted in most of previous studies.^1

–4,8,9 A prospective cohort study is therefore required. In addition, although the association between the elevated IOP and MetS has been demonstrated, the results of gender difference in the association between the elevated IOP and MetS are inconsistent.

In the community-based integrated screening in Matsu, an offshore island between Mainland China and Taiwan, a routine health check-up that embraces biomarker tests for MetS has been conducted annually between 2003 and 2010 and one-shot eye examinations for glaucoma and cataract and also the measurement of IOPs were provided in 2003. This offers an opportunity to assess the association between the elevated IOP and MetS in men and women (and also premenopausal and postmenopausal women) at baseline examination. More important, this screened cohort also provides an opportunity to elucidate the effect of the elevated IOP on the incidence of MetS with a normal cohort (free of MetS) at baseline (2003) following over time until 2010.

Using empirical data on this community-based cohort study in Taiwan, the major aim of this study was to investigate an alternative temporal sequence pertaining to the influence of IOP on incident MetS and its individual components in addition to the association between the elevated IOP and MetS.

Materials and Methods

Study population

The empirical data used for analysis were derived from a community-based repeated health check-ups program in Matsu during the period 2003 to 2010. For investigating the disease burden of eye-related disease, we additionally provided inhabitants a series of one-shot eye-related examination in 2003. The details of this program were reported in a previous study.¹⁰

The study population consisted of 1347 residents older than 30 years (53% women and 47% men), ∼19.4% of the target population, who were enrolled to attend the ocular disease screening program. The mean age of the attendants was 50.7 years (SD = 12.7). It should be noted that 39 glaucoma patients who were diagnosed or had a history of glaucoma at baseline were excluded from analysis. The eligible population in our study was composed of only nonglaucomatous subjects (Supplementary Fig. S1). This study was approved by Institutional Review Board of National Yang-Ming University (No. YM102046).

Study design

This prospective cohort study followed a normal cohort (free of MetS by excluding 290 subjects having MetS at baseline) to ascertain incident cases of MetS with 5.14 years of mean follow-up time. The IOP together with other confounding factors were measured at baseline. In the primary analysis of the effect of IOP on incident MetS using such a prospective normal cohort study design, the continuous or categorical (<15, 15–18, ≥18) IOP were taken as independent variables and the incident cases of MetS were treated as dependent variables so as to evaluate the effect of baseline measurement of IOP on incident MetS during the follow-up time from 2003 to 2010. In the secondary analysis, as both IOP and MetS were measured at baseline, the association between elevated IOP and MetS as in most of the previous studies^1

–4,8,9 were also evaluated to make comparisons.

On-site community-based integrated screening

In 2003, a series of screening activities were conducted in community including registration, fasting blood drawing for biochemical test on MetS, physiological and anthropometric measurements, questionnaire, physical examination, cancer screening, eye-related examination, and health education.^10,11 Demographic characteristics, history of personal disease, and life-style information were obtained from face-to-face interviewed questionnaire. After the 15- to 20-min interview of questionnaire, BP was measured by using an upper-arm automatic BP monitor. For those with high-BP readings, the second measure with manual monitors was taken by public health nurses to validate the abnormal findings. The lower reading of BP was used in this study. With regard to the anthropometric measurements, the trained health work volunteers measured the participants' height, weight, and circumference of waist and hip. Body mass index (BMI) was calculated as weight (kilograms) divided by the square of height (meters). Current or former smokers were considered as smoking group. Similarly, current or former drinkers were considered as alcoholic drinking group.

Measurement of IOP, cataract, and glaucoma

IOP in both eyes were measured with a noncontact tonometer that was performed by trained technicians, and the mean of the values was used as outcome. The slit-lamp biomicroscopy and indirect ophthalmoscopy were used to assess cataracts. The slit-lamp examination and indirect ophthalmoscopy were performed by ophthalmologists. Subjects who had previous cataract surgery were defined as cataract cases. The classification of glaucoma cases was diagnosed by single senior ophthalmologist. This history of glaucoma from self-report was also defined as glaucoma case.

Definition of MetS

The definition of MetS used was based on modified NCEP ATP III criteria for use in Asians.¹² In the study, MetS was defined as present when subjects met three or more of the following criteria: (1) central obesity (an increased waist circumference [WC], WC ≥80 cm for women and ≥90 cm for men), (2) high triglycerides (TGs) (an elevated TG, ≥150 mg/dL), (3) low high-density lipoprotein cholesterol (HDL-C) concentration (<50 mg/dL for women and <40 mg/dL for men), (4) elevated BP (≥130 mmHg in systolic BP or ≥85 mmHg in diastolic BP), and (5) glucose intolerance (elevated fasting glucose, ≥100 mg/dL). The MetS score was defined as the number of constituents of MetS.

Statistical analysis

We used average IOP value from two eyes for each subject to categorize IOP into three groups, <15, 15–18, and >18. Descriptive analysis included the prevalence of MetS by three levels of IOP and other confounding factors presented as percentage of number of MetS at baseline divided by the eligible population. The incident rates of MetS were computed using person-years as the denominator. Multiple linear regression analysis was used to assess the association between MetS and IOP after adjusting for confounding variables using number of constituents of MetS and the measurement of IOP at baseline. The Cox regression model was used to assess the effect of IOP on the development of incident MetS with adjustment for age, BMI, and smoking. All analyses were performed using SAS statistical software, version 9.3.

Results

Prevalence of MetS by IOP, eye diseases, and relevant confounding factors

Table 1 provides the prevalence and incidence of MetS by demographic features, Helicobacter pylori infection, smoking and drinking, three levels of IOP, cataract, and glaucoma. The prevalence of MetS increased with advancing age. Men had higher prevalence than women. Those with H. pylori infection had slightly higher prevalence than those without. The prevalence was similar between smokers and nonsmokers or between drinkers and nondrinkers. The prevalence of three levels of IOP was also identical. The prevalence rate almost doubled in those diagnosed as cataract and glaucoma compared with those free of two respective eye diseases.

Table 1.

Demographic Characteristics and Eyes Conditions of Matsu Cohort Together with the Associated Prevalence and Incidence rate of Metabolic Syndrome

Characteristics	Subjects (n)	%	MetS
Characteristics	Subjects (n)	%	Prevalent cases	Prevalence (%)	Person-years	Incident cases	Incidence rate (%)
Overall	1347		290	21.5	5833	220	3.77
Age, years
<40	263	19.5	19	7.2	1395	39	2.80
40–49	451	33.5	78	17.3	2185	81	3.71
50–59	331	24.6	78	23.6	1390	66	4.75
60–69	165	12.3	61	37.0	532	23	4.32
70+	136	10.1	54	39.7	331	11	3.32
Gender
Male	631	46.8	155	24.6	2491	126	5.06
Female	716	53.2	135	18.9	3342	94	2.81
Helicobacter pylori infection
Negative	430	31.9	81	18.8	1701	51	3.00
Positive	917	68.1	209	22.8	4132	169	4.09
Smoking
No	1024	76.5	219	21.4	4584	143	3.12
Yes	314	23.5	67	21.3	1238	77	6.22
Alcohol drinking
No	626	47.5	137	21.9	2693	74	2.75
Yes	692	52.5	148	21.4	3003	141	4.70
IOP, mmHg
<15	1054	78.2	225	21.4	4597	157	3.42
15–18	215	16.0	48	22.3	887	43	4.85
>18	78	5.8	17	21.8	349	20	5.73
Cataract, %
No	1136	84.3	207	18.2	5264	188	3.57
Yes	211	15.7	83	39.5	569	32	5.62
Glaucoma, %
No	1308	97.1	274	20.9	5695	213	3.74
Yes	39	2.9	16	41.0	138	7	5.07

IOP, intraocular pressure; MetS, metabolic syndrome.

In contrast to prevalence, the incidence of MetS was constant with age. Men still had higher incidence rate than women. The incidence rates of MetS were higher in smokers and drinkers than nonsmokers and nondrinkers. The incidence rates of MetS increased with baseline IOP level. The similar but less remarkable contrasts of incidence rate of MetS were noted for both eye diseases.

Association between MetS and IOP

Tables 2 and 3 gives the estimated gender-specific results of the linear regression model that regressed those on the measure of IOP (regarded as continuous dependent variable), including the independent variables of interest (MetS with binary outcome, MetS score, and individual components of MetS) and confounding factors. A dichotomous MetS association was statistically significantly noted in women but not in men after adjustment for age, gender, and BMI. In women, the adjusted effect size (an increase in beta unit of IOP in the presence of MetS) of such an association was stronger in postmenopause (P = 0.025) than premenopause (P = 0.05). When using MetS score (number of constituents of MetS), the adjusted effect size (an increase in β unit of IOP per one additional MetS score) was the greatest in postmenopausal women (β = 0.50, P = 0.001), followed by premenopausal women (β = 0.34, P = 0.008) and men (β = 0.27, P = 0.011), although those adjusted effect sizes were statistically significant. The significant correlations between abdominal obesity and high BP and the elevated IOP were noted in men (Table 2), whereas three corresponding components, abnormal TG, high BP, and abnormal fasting glucose were noted in women, particularly in postmenopausal women (Table 3). Only high BP was noted in premenopausal women, which were possibly because of sparse cases.

Table 2.

Results of Regression Analysis for Intraocular Pressure Among Nonglaucomatous Men (N = 618)

Variables	Univariate model ^a		Multivariate model ^b
Variables	Regression coefficient	P	Regression coefficient	P
Age, years	−0.0719	<0.0001	−0.0714	<0.0001
High BMI	0.0975	<0.0011	0.0964	0.0038
HP infection (yes vs. no)	−0.0067	0.9782
MetS (yes vs. no)	0.5169	0.0514	0.1195	0.6840
MetS score (0–5)	0.3559	<0.0001	0.2672	0.0108
Individual MetS components
Abdominal obesity	0.8162	0.0006	0.6277	0.0369
High triglyceride	0.3751	0.1434	0.1711	0.5115
Low high-density lipoprotein cholesterol	0.0539	0.8505	−0.1464	0.6111
High blood pressure	0.7785	0.0009	0.6504	0.0064
High fasting glucose	0.5493	0.0346	0.4116	0.1170
Smoking (yes vs. no)	0.4496	0.0461	0.4869	0.0299
Drinking (yes vs. no)	0.3048	0.2499

The bold values indicate statistical significance.

Adjusting age.

Adjusting age, smoking, and BMI.

BMI, body mass index; HP, helicobacter pylori.

Table 3.

Results of Regression Analysis for Intraocular Pressure Among Nonglaucomatous Women (N = 690)

Variables	Univariate model ^a		Multivariate model ^b
	Univariate model ^a		All women		Premenopause (n = 490)		Postmenopause (n = 200)
	Regression coefficient	P	Regression coefficient	P	Regression coefficient	P	Regression coefficient	P
Age, years	−0.0485	<0.0001	−0.0573	<0.0001	−0.0347	0.0370	−0.0941	<0.0001
High BMI	0.0504	0.0526	0.0224	0.3854	0.0463	0.2008	−0.0547	0.2392
HP infection (yes vs. no)	−0.1732	0.4118
MetS (yes vs. no)	0.8698	0.0016	0.7607	0.0104	0.8013	0.0501	0.9884	0.0249
MetS score (0–5)	0.3910	<0.0001	0.3925	<0.0001	0.3443	0.0080	0.5039	0.0012
Individual MetS components
Abdominal obesity	0.4746	0.0333	0.3904	0.1581	0.2857	0.4064	0.6489	0.1769
High triglyceride	0.9238	0.0054	0.8111	0.0174	0.6837	0.1421	1.0496	0.0362
Low high-density lipoprotein cholesterol	0.2118	0.3409	0.1735	0.4397	0.1903	0.4935	0.2637	0.4953
High blood pressure	0.9226	<0.0001	0.8718	0.0002	0.6607	0.0222	1.1805	0.0024
High fasting glucose	0.7664	0.0044	0.7005	0.0099	0.5374	0.1463	0.9644	0.0158
Smoking (yes vs. no)	−0.6899	0.2826
Drinking (yes vs. no)	0.2387	0.2748

The bold values indicate statistical significance.

Adjusting age.

Adjusting age and BMI.

Effect of IOP on incidence of MetS

The results of crude analysis of the effect of IOP, in addition to other confounding variables, on incident MetS are given in Supplementary Table S1. Table 4 gives the effect of IOP on the risk of developing MetS after adjusting for other conventional risk factors, such as age, BMI, and smoking. An incremental unit of IOP led to 6% (adjusted relative ratio [aRR]: 1.06; 95% confidence interval [CI]: 1.01–1.11) increase in incident MetS. However, the influence of IOP on incident MetS in women was noted but not statistically significant (aRR: 1.03, 95% CI: 0.96–1.12). When the IOP was classified into two categories, the elevated IOP compared with the lower one resulted in around one-and-half risk for developing incident MetS (aRR: 1.46; 95% CI: 1.08–1.99) for both sex combined. The stronger effect was noted in men (aRR: 1.66; 95% CI: 1.13–2.45) but not in women. We also assessed the effect of IOP on the risk of newly developed individual MetS components as given in Table 5. IOP was statistically associated with all the other components: abdominal obesity, high TG, high BP, and high fasting glucose except HDL, for both sex combined. The effect of IOP was also statistically noted in most individual components, including abdominal obesity, high TG, high BP, and high fasting glucose in men, whereas the impacts of IOP were noted in only two individual components, high BP and high fasting glucose in women. By the stratification of menopause status, only high BP was statistically noted in both premenopausal and postmenopausal women. However, the effect could be attenuated because of sparse cases after the stratification of menopause status.

Table 4.

The Adjusted Relative Ratios of Each Factor for the Risk of Developing Incident Metabolic Syndrome (N = 1034)

Variables	Both sex		Men		Women
	Both sex		Men		All		Premenopause		Postmenopause
	aRR (95% CI)	P	aRR (95% CI)	P	aRR (95% CI)	P	aRR (95% CI)	P	aRR (95% CI)	P
Age	1.02 (1.00–1.03)	0.0095	1.01 (1.00–1.03)	0.1346	1.03 (1.01–1.05)	0.0111	1.03 (0.99–1.06)	0.1425	1.00 (0.94–1.05)	0.9135
Gender (male vs. female)	1.36 (0.98–1.88)	0.0699	—	—	—	—	—	—	—	—
IOP, mmHg	1.06 (1.01–1.11)	0.0258	1.07 (1.01–1.14)	0.0342	1.03 (0.96–1.12)	0.3834	1.01 (0.92–1.11)	0.8418	1.02 (0.88–1.19)	0.7685
BMI (≥25 vs. <25)	1.18 (1.14–1.22)	<0.0001	1.21 (1.15–1.29)	<0.0001	1.16 (1.11–1.22)	<0.0001	1.20 (1.14–1.26)	<0.0001	1.02 (0.92–1.14)	0.7069
Smoking (yes vs. no)	1.61 (1.15–2.26)	0.0056	1.51 (1.06–2.16)	0.0236	2.14 (0.86–5.32)	0.1033	1.68 (0.41–6.93)	0.4745	3.46 (0.97–12.32)	0.0556
IOP (≥15 vs. <15)	1.46 ^a (1.08–1.99)	0.0152	1.66 ^b (1.13–2.45)	0.0099	1.15^b (0.68–1.93)	0.6036	0.90^b (0.49–1.65)	0.7238	2.00^b (0.71–5.63)	0.1892

The bold values indicate statistical significance.

Adjusting age, gender, BMI, and smoking.

Adjusting age, BMI, and smoking.

aRR, adjusted relative ratio; CI, confidence interval.

Table 5.

The Adjusted Relative Risks of Intraocular Pressure (in mmHg) for Developing Individual Metabolic Syndrome Components (N = 1034)

Strata	Abdominal obesity, aRR (95% CI)	High triglyceride, aRR (95% CI)	Low high-density lipoprotein, aRR (95% CI)	High blood pressure, aRR (95% CI)	High fasting glucose, aRR (95% CI)
Both sex^a	1.05 (1.02–1.09)	1.09 (1.03–1.15)	1.03 (0.97–1.10)	1.08 (1.05–1.12)	1.09 (1.03–1.15)
Male^b	1.08 (1.02–1.14)	1.09 (1.03–1.16)	1.08 (0.98–1.19)	1.07 (1.02–1.12)	1.07 (1.00–1.15)
Female^b	1.02 (0.97–1.07)	1.07 (0.96–1.19)	0.99 (0.91–1.08)	1.09 (1.03–1.14)	1.10 (1.00–1.21)
Premenopausal women^b	1.04 (0.98–1.10)	1.09 (0.97–1.22)	0.99 (0.90–1.09)	1.07 (1.01–1.14)	1.07 (0.95–1.21)
Postmenopausal women^b	0.97 (0.88–1.06)	0.85 (0.58–1.24)	1.02 (0.85–1.22)	1.09 (1.00–1.20)	1.12 (0.97–1.31)

Adjusting for age and gender.

Adjusting for age.

Discussion

In contrast to previous studies that put emphasis on the association between the elevated IOP and MetS,^2
–4,8,9 the main objective of this study, in addition to corroborating the association studies, was to investigate an alternative temporal sequence pertaining to the effect of IOP on incident MetS among nonglaucomatous subjects based on a longitudinal cohort study. Statistically significant impact of elevated IOP on incident MetS was noted in men but not in women regardless of menopause status after adjusting for age, BMI, and smoking. The influences of each individual component on MetS in men were seen for all components except HDL, whereas the corresponding impacts were seen only for BP and fasting blood glucose in women and BP in postmenopausal women. The results based on the influence of IOP on incident analysis mentioned previously were different from those findings obtained from the association studies using prevalence of MetS and the measurement of IOP in cross-sectional studies.^2
–4,8,9 The association between the IOP and MetS, the severity of MetS, or its individual components were the strongest in postmenopausal women, followed by premenopause women, but less remarkable in men.

The association between MetS and IOP has been elucidated in several previous studies^1
–3,9,13 and also confirmed in this study. Specific components related to MetS that were statistically significantly associated with elevated IOP include cholesterol,¹ TG,^1,2 insulin resistance,³ hypertension, and ⁴ BMI.^8,13

–16 Our association results on individual components were consistent with these corresponding previous findings.

Regarding the disparity of gender difference, the positive association between IOP and MetS was found in nonglaucomatous women, particularly in postmenopausal women. However, the association did not exist in premenopausal women and men. Our results are in agreement with Park's study on the disparity by menopause status.⁵ Regarding individual components of MetS, our finding indicates a positive association between BP and IOP and no association between HDL-C and IOP in both genders, and abdominal obesity is associated with IOP only in men. These findings are compatible with the findings of previous studies.^4,8 A positive association between fasting glucose and IOP was found in women but not in men, whereas Lin et al.⁴ revealed a positive association between fasting glucose and IOP in both genders. TG has a positive association with IOP in women as seen in previous findings.^4,8 However, Lin et al. revealed a positive association between TG and IOP in both genders. To sum up, consistency across studies has been observed regarding the association between MetS and IOP but the results of gender differences in the association between systemic factors and IOP were not consistent. The weakness of such an association study is that it is difficult to disentangle the epidemiological causal relationship, that is, the temporal sequential between IOP and MetS. To clarify such a temporal order, a prospective cohort study is required like our study that demonstrated the impact of IOP on the overall incident MetS.

In our analysis of the effect of IOP on incident MetS, we also found the gender difference in the causal relationship between IOP and MetS but these results of incident analysis was different from those of association analysis. The presence of IOP before the development of incident MetS was only noted in men but not in women. Regarding individual components of MetS, the elevated IOP in men may be more likely to result in more components of MetS than women. It is very interesting to note that the common phenomenon of the elevated IOP resulting in high BP was observed in both men and women as also indicated in the previous cohort study.¹⁷ This may suggest that elevated IOP and BP have the same mechanism (such as sympathetic activity) in common.

Implication for our findings on incident analysis is that the baseline IOP could be used to stratify the risk of developing MetS. Among 1037 MetS free subjects, the incidence rates of MetS was from 0.0342 to 0.0573 for those subjects with baseline IOP <15 and >18, respectively. The result revealed that the baseline IOP as an independent risk factor contributed to the risk of MetS development. This stresses the necessity of measuring IOP in routine health check-up for prevention of MetS-related chronic diseases.

There are several limitations. The first is that a prospective cohort design is to elucidate the effect of IOP on MetS but not the effect of MetS on the elevated IOP because we did not have repeated IOP measurements. The direction of the latter is often held by the heart of these research people when they conducted these association studies that treat MetS as independent variable and the IOP as dependent variable although such a cross-sectional design cannot clarify such a temporal sequence. Another direction of prospective cohort studies focusing on the outcomes based on elevated IOP and glaucoma must be provided to clarify their temporal sequence in future. The second limitation is related to a short follow-up that may result in small samples sizes on incident analysis regarding the impact of IOP on MetS. This may account for why the effect of IOP on MetS was only noted in men but not in women because MetS may take more time to develop. Moreover, smoking and drinking quantity are important risk factors associated with MetS. However, the quantity of smoking and drinking was not included in this analysis is one of the limitations.

In conclusion, a prospective cohort study with the design that elevated IOP is regarded as the independent variable and incident MetS is treated as the dependent variable demonstrates that the elevated IOP led to an increase in incidence of MetS but this significant temporal sequence was only noted in men but not in women. The finding that elevated IOP occurred before the presence of high BP was noted in both men and women, whereas men with elevated IOP may be concomitant with more individual components (severity) of MetS earlier than women with elevated IOP. Evidence on the temporal sequence may not suggest the aspect of etiology but indicated the possibility of showing sign of elevated IOP before the development of MetS. The measurement IOP in routine health check-up may be strongly suggested as it is helpful to enhance awareness on the prevention of developing MetS.

Footnotes

Acknowledgments

This study was supported by the Ministry of Science and Technology (Grant No. MOST 106-2118-M-002-006-MY2; MOST 106-2118-M-532-001-MY2; MOST 107-3017-F-002-003) and Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan (Grant No. NTU-107L9003).

Author Disclosure Statement

The authors stated that there are no conflicts of interest regarding the publication of this article.

Supplementary Material

Supplementary Figure S1

Supplementary Table S1

References

Tang

, Wang

, Fong

, et al.; Singapore Malay eye study. Diabetes, metabolic abnormalities, and glaucoma. Arch Ophthalmol, 2009; 127:1354–1361.

Park

, Lee

, Jargal

, et al. The distribution of intraocular pressure and its association with metabolic syndrome in a community. J Prev Med Public Health, 2010; 43:125–130.

, Lee

, Park

, et al. Elevated intraocular pressure is associated with insulin resistance and metabolic syndrome. Diabetes Metab Res Rev, 2005; 21:434–440.

Lin

, Lin

, Wu

. Age- and gender-specific association between intraocular pressure and metabolic variables in a Taiwanese population. Eur J Intern Med, 2012; 23:76–82.

Belmonte

, Bartels

, Liu

, et al. Effects of stimulation of the ocular sympathetic nerves on IOP and aqueous humor flow. Invest Ophthalmol Vis Sci, 1987; 28:1649–1654.

Ogueta

, Schwartz

, Yamashita

, et al. Estrogen receptor in the human eye: Influence of gender and age on gene expression. Invest Ophthalmol Vis Sci, 1999; 40:1906–1911.

Gupta

, Johar

Sr , Nagpal

, et al. Sex hormone receptors in the human eye. Surv Ophthalmol, 2005; 50:274–285.

Park

, Park

, Kang

, et al. Elevated intraocular pressure is associated with metabolic syndrome in postmenopausal women: The Korean National Health and Nutrition Examination Survey. Menopause, 2013; 20:742–746.

Chang

, Lin

, Wang

, et al. Association of intraocular pressure with the metabolic syndrome and novel cardiometabolic risk factors. Eye, 2010; 24:1037–1043.

10.

Chen

, Tsai

, Liou

, et al. Feasibility of tele-ophthalmology for screening for eye disease in remote communities. J Telemed Telecare, 2004; 10:337–341.

11.

Hsu

, Yen

, Liou

, et al. Prevalence and risk factors of somatic and autonomic neuropathy in prediabetic and diabetic patients. Neuroepidemiology, 2009; 33:344–349.

12.

World Health Organization. The Asia-Pacific Perspective: Redefining Obesity and Its Treatment. Geneva, Switzerland: World Health Organization; 2000.

13.

Wygnanski-Jaffe

, Bieran

, Tekes-Manova

, et al. Metabolic syndrome: A risk factor for high intraocular pressure in the Israeli population. Int J Ophthalmol, 2015; 8:403–406.

14.

Cheung

, Wong

. Obesity and eye diseases. Surv Ophthalmol, 2007; 52:180–195.

15.

Lee

, Lee

, Oum

, et al. Relationship between intraocular pressure and systemic health parameters in a Korean population. Clin Exp Ophthalmol, 2002; 30:237–241.

16.

Mori

, Ando

, Nomura

, et al. Relationship between intraocular pressure and obesity in Japan. Int J Epidemiol, 2000; 29:661–666.

17.

, Nemesure

, Hennis

, et al. Nine-year changes in intraocular pressure: The Barbados Eye studies. Arch Ophthalmol, 2006; 124:1631–1636.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.05 MB

0.02 MB