Associations between Intraocular Pressure and Systemic Parameters according to the KNHNES 2008-2011

Ji Young Lee; Hye Bin Yim; Kwi Young Kang; Na Young Lee

doi:10.3341/jkos.2017.58.4.430

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Lee, Yim, Kang, and Lee: Associations between Intraocular Pressure and Systemic Parameters according to the KNHNES 2008-2011

Original Article

J Korean Ophthalmol Soc 2017;58(4):430-436.

Published online: 8 September 2017

DOI: https://doi.org/10.3341/jkos.2017.58.4.430

Associations between Intraocular Pressure and Systemic Parameters according to the KNHNES 2008-2011

Ji Young Lee, M.D.¹, Hye Bin Yim, MD, PhD¹, Kwi Young Kang, MD, PhD², Na Young Lee, MD, PhD^1,

^¹Department of Ophthalmology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea

^²Department of Internal Medicine, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea

Address reprint requests to Na Young Lee, MD, PhD Department of Ophthalmology, The Catholic University of Korea Incheon St. Mary’s Hospital, #56 Dongsu-ro, Bupyeong-gu, Incheon 21431, Korea Tel: 82-32-280-5110, Fax: 82-32-280-5111 E-mail: nyny5555@naver.com

Received 26 May 201614 February 2017 Accepted 24 March 2017

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Purpose

In this study, we evaluated the associations between intraocular pressure (IOP) and systemic and socioeconomic factors.

Methods

A population-based cross-sectional study using a nation-wide, stratified, multistage, clustered sampling method in-cluded 15,421 subjects aged ≥20 years with no history of ocular surgery or glaucoma who participated in the Korean National Health and Nutritional Examination Survey 2008-2011.

Results

Univariate regression analyses showed statistically significant linear relationships between IOP and body mass index (BMI), smoking status, heavy drinking, systolic blood pressure, fasting blood glucose, total cholesterol, triglycerides, insulin, ho-meostasis model assessment of insulin resistance (HOMA-IR), metabolic syndrome (p < 0.001, respectively), low density lip-oprotein cholesterol (p = 0.003), refractive error (p < 0.001), and office work (p = 0.029). In addition, analysis of variance (ANOVA) showed statistically significant differences in IOP and refraction according to occupation (p < 0.001, all).

Conclusions

We concluded that increased IOP was associated with age, BMI, heavy drinking, systolic blood pressure, total cho-lesterol, and refraction. There were statistically significant differences in IOP and refraction according to occupation.

Keywords: Blood pressure, Intraocular pressure, Occupation, Office workers, Refractive error

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Figure 1.

Flow chart of the study population. Subjects with glaucoma or ocular surgery history were excluded. IOP = in-traocular pressure.

Figure 2.

Boxplots of intraocular pressure (mmHg, mean ± SD) according to occupations. Analysis of variance (ANOVA) showed statistically significant difference in intraocular pressure according to occupations. ^* ANOVA, p-value < 0.001.

Figure 3.

Boxplots of refraction (diopters, mean ± SD) according to occupations. Analysis of variance (ANOVA) showed statistically significant difference in refraction according to occupations. ^* ANOVA, p-value < 0.001.

Table 1.

Baseline characteristics of the study subjects

	Total (N = 15,421)
Age (years)	48.9 ± 16.1
Sex: Female (n, %)	8,815 (57.16)
Body weight (kg)	62.26 ± 11.53
Height (cm)	162.1 ± 9.27
BMI (kg/m²)	23.61 ± 3.35
WC (cm)	81.07 ± 9.96
IOP (mmHg)	13.9 ± 2.7
Total body fat mass (kg)	9.1 ± 3.52
Total body fat percentage (%)	29.3 ± 8.3
Current smokers (n, %)	3,452 (22.56)
Heavy drinkers (n, %)	7,077 (46.13)
Regular exercisers (n, %)	1,822 (11.84)
SBP (mmHg)	119.1 ± 17.7
DBP (mmHg)	76.7 ± 10.9
FBS (mg/dL)	97.6 ± 23.2
TG (mg/dL)	134.2 ± 111
TC (mg/dL)	187.7 ± 35.9
Insulin (μ IU/mL)	9.9 ± 5.6
HOMA-IR	2.5 ± 2.1
HDL (mg/dL)	48.1 ± 11.1
LDL (mg/dL)	113.1 ± 32.7
Refraction (diopters)	-0.9 ± 2.3
Metabolic syndrome (n, %)	3,267 (22.02)
Education (n, %)
Elementary school	4,062 (26.6)
Middle school	1,720 (11.3)
High school	5,258 (34.4)
University or higher	4,249 (27.8)
Lowest income (n, %)	3,767 (24.8)
Occupation (n, %)
Office workers	1,222 (8.0)
Administrator, management, professional	1,782 (11.7)
Sales and related occupations	1,958 (12.9)
Farming, fishing, and foresty occupations	1,425 (9.4)
Installation, maintenance, and repair occupations, technicians	1,458 (9.6)
Laborer	1,314 (8.6)
Unemployed	6,073 (39.9)
Family history of glaucoma (n, %)	274 (1.8)

Values are presented as mean ± SD or n (%).

BMI = body mass index; WC = waist circumference; IOP = intra-ocular pressure; SBP = systolic blood pressure; DBP = diastolic blood pressure; FBS = fasting blood sugar; TG = triglycerides; TC = total cholesterol; HOMA-IR = homeostasis model assess-ment of insulin resistance; HDL = high density lipoprotein choles-terol; LDL = low density lipoprotein cholesterol.

Table 2.

Univariate and multivariate linear regression analyses of factors associated with intraocular pressure in all study subjects

	Univariate Model			Multivariate Model 1			Multivariate Model 2
	Coef	SE	p-value	Coef	SE	p-value	Coef	SE	p-value
Age	-0.004	0.001	0.001	-0.008	0.002	<0.001	-0.008	0.002	<0.001
BMI	0.066	0.006	<0.001	0.028	0.008	<0.001	0.036	0.007	<0.001
Current smoking			<0.001			0.299
Past vs. Never	0.195	0.058	0.001	0.083	0.062	0.181
Current vs. Never	0.202	0.054	<0.001	0.073	0.061	0.230
Heavy drinkers	0.275	0.044	<0.001	0.129	0.052	0.013	0.170	0.047	<0.001
Regular exercisers	0.058	0.068	0.391
SBP	0.013	0.001	<0.001	0.015	0.002	<0.001	0.016	0.002	<0.001
FBS	0.007	0.001	<0.001	0.006	0.001	<0.001	0.006	0.001	<0.001
TG	0.001	0.000	<0.001	0.000	0.000	0.784	0.003	0.001	<0.001
TC	0.004	0.001	<0.001	0.003	0.001	<0.001
Insulin	0.025	0.004	<0.001	0.009	0.011	0.411
HOMA-IR	0.070	0.010	<0.001	-0.013	0.033	0.685
HDL	-0.003	0.002	0.124
LDL	0.002	0.001	0.003
Refraction	-0.094	0.010	<0.001	-0.102	0.011	<0.001	-0.103	0.011	<0.001
Metabolic syndrome	0.466	0.053	<0.001	0.132	0.070	0.060
Family history of glaucoma	0.171	0.165	0.302
Office workers	0.176	0.081	0.029	0.069	0.083	0.405

Multivariate Model 1: included all significant factors in Univariate Model, but excluded LDL due to multicollinearity.

Multivariate Model 2: applied selected stepwise selection method on Multivariate Model 1.*

Coef = coefficient; SE = standard error; BMI = body mass index; SBP = systolic blood pressure; FBS = fasting blood sugar; TG = trigly-cerides; TC = total cholesterol; HOMA-IR = homeostasis model assessment of insulin resistance; HDL = high density lipoprotein cholesterol; LDL = low density lipoprotein cholesterol.

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