The Effect of Age and Gender on the Intraocular Pressure in Koreans: A Cross-sectional Study

Sung Chul Park; Changwon Kee

doi:10.3341/jkos.2008.49.1.135

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Park and Kee: The Effect of Age and Gender on the Intraocular Pressure in Koreans: A Cross-sectional Study

Original Article

J Korean Ophthalmol Soc 2008;49(1):135-142.

Published online: 3 August 2008

DOI: https://doi.org/10.3341/jkos.2008.49.1.135

The Effect of Age and Gender on the Intraocular Pressure in Koreans: A Cross-sectional Study

Sung Chul Park, M.D., Changwon Kee, M.D., Ph.D.

Department of Ophthalmology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea

Address reprint requests to Changwon Kee, M.D. Department of Ophthalmology, Samsung Medical Center, Sungkyunkwan University School of Medicine #50 Ilwon-dong, Gangnam-gu, Seoul 130-710, Korea Tel: 82-2-3410-3564, Fax: 82-3410-0074, E-mail: cwkee@smc.samsung.co.kr

Received 7 June 2007 Accepted 21 September 2007

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

To assess the effect of age and gender on intraocular pressure (IOP) in a large Korean population.

Methods

This cross-sectional study included 102,218 healthy Koreans who were aged between 20 and 79 and had no preexisting ocular conditions that could affect the IOP. All the subjects had undergone a physical check up between 1996 and 2005, and their medical records were reviewed retrospectively. Anthropometric measurements, blood tests, noncontact tonometry, and fundus examination were performed on all participants. Subjects were grouped according to decade of age. For all subjects and each age group, age and systemic variables were analyzed by multiple regression analysis on their relationship with IOP.

Results

A significant trend of decreasing IOP was observed in the 40s, 50s, and 60s in men, while a significant trend of increasing IOP was found in the 50s, 60s, and 70s in women. Multiple regression analysis revealed different IOP trends with age between age groups in both men and women. In general, the IOP had a significant positive correlation with systolic blood pressure, body-mass index (BMI), hematocrit, and serum cholesterol, especially with BMI in men and hematocrit in women.

Conclusions

In a multiple regression analysis, the IOP trend in each age group was quite different from each other in a large Korean population, and it was suggested that women may have a steeper increasing slope (or less steep decreasing slope) of IOP with age than men. Further investigations with longitudinal study would be required to clarify the age- and gender-related physiologic changes of IOP.

Keywords: Age, Cross-sectional analysis, Intraocular pressure, Korean

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Figure 1.

The distribution of intraocular pressure in total subjects. (A) Before and (B) after excluding subjects with doubtable findings, such as optic disc abnormality and fundus abnormality based on fundus photography, IOP over 21 mm Hg, participant’s own history or family history of medical and/or ocular conditions that could possibly affect the IOP (glaucoma, proliferative diabetic retinopathy, hypertension, hyperlipidemia, etc.), and drug history of antiglaucoma, antihypertensive, or antihyperlipidemic medications.

Figure 2.

The distribution of mean intraocular pressure (IOP) by age group. (A) In men, there was a significant difference in the mean IOP between those in their 40s and 50s and between those in their 50s and 60s (P<0.001, respectively; by one-way ANOVA with multiple comparison)^*). (B) In women, there was a significant difference in the (mean IOP between those in their 50s and 60s and between those in their 60s and 70s (P<0.001, respectively; by one-way ANOVA with multiple comparison) (^*).

Table 1.

The number of participants by age group

	Age Groups^*						Total (n=102,218)
	20s (n=3,209)	30s (n=17,848)	40s (n=37,479)	50s (n=29,820)	60s (n=12,465)	70s (n=1,397)	Total (n=102,218)
Men	1,603	9,672	21,186	16,725	7,329	855	57,370
Women	1,606	8,176	16,293	13,095	5,136	542	44,848

^* By age at the baseline (years).

Table 2.

Cross-sectional analysis between intraocular pressure (IOP) and other variables (age, body mass index (BMI), systolic blood pressure (SBP), hematocrit, and cholesterol) using a multiple regression model

Men (OD)	Age Groups (at the baseline)						Total
Men (OD)	20s	30s	40s	50s	60s	70s	Total
R²	0.042^*	0.028^*	0.026^*	0.019^*	0.020^*	0.016^*	0.024^*
Age (years)	-0.04±0.026	0.004±0.010	-0.006±0.006	-0.034^*±0.006	-0.016±0.010	-0.069^†±0.028	-0.019^*±0.001
BMI (kg/m²)	0.076^*±0.020	0.070^*±0.010	0.066^*±0.006	0.063^*±0.007	0.098^*±0.011	0.082^‡±0.027	0.074^*±0.004
SBP (mmHg)	0.027^*±0.006	0.022^*±0.002	0.024^*±0.001	0.017^*±0.001	0.015^*±0.002	0.011^‡±0.004	0.019^*±0.001
Hematocrit (%)	0.062^†±0.028	0.015±0.010	0.013^†±0.006	0.011±0.006	-0.020^†±0.009	-0.027±0.022	0.009^†±0.003
Cholesterol (mg/dL)	0.002±0.002	0.006^*±0.001	0.004^*±0.001	0.011^*±0.001	0.003^*±0.001	0.002±0.002	0.004^*±0.001
Women (OD)	Age Groups (at the baseline)						Total
Women (OD)	20s	30s	40s	50s	60s	70s	Total
R²	0.016^*	0.021^*	0.022^*	0.020^*	0.030^*	0.026^‡	0.027^*
Age (years)	-0.076^‡±0.027	-0.017±0.011	0.020^‡±0.007	0.004±0.007	0.001±0.013	0.029±0.045	0.006±0.001
BMI (kg/m²)	0.066^†±0.027	0.064^*±0.011	0.028^*±0.007	0.002±0.007	-0.025^†±0.012	0.031±0.034	0.020^*±0.004
SBP (mmHg)	0.008±0.006	0.022^*±0.002	0.019^*±0.001	0.018^*±0.001	0.020^*±0.002	0.005±0.005	0.019^*±0.001
Hematocrit (%)	0.082^†±0.028	0.030^‡±0.010	0.025^*±0.006	0.036^*±0.008	0.078^*±0.012	0.112^‡±0.034	0.037^*±0.004
Cholesterol (mg/dL)	-0.004±0.003	0.006^*±0.001	0.006^*±0.001	0.004^*±0.001	0.006^*±0.001	0.005±0.003	0.005^*±0.001

The results from both eyes were very similar, so data from the left eye are not presented.

Values are described as partial regression coefficient±standard error.

Above 4 systemic factors (BMI, SBP, hematocrit, and cholesterol) were included in multivariate linear regression analysis, because these showed significant correlations with IOP overall and in nearly all age groups by Pearson’s correlation analysis.

^† P<0.05

^‡ P<0.01

^* P<0.001.

Table 3.

Previous cross-sectional studies on the physiologic changes in the intraocular pressure (IOP) with age

Ethnic Group	Previous Study	Range of Age (years)	The No. of Subjects	Method of IOP Measurement	Association with Age
Ethnic Group	Previous Study	Range of Age (years)	The No. of Subjects	Method of IOP Measurement	Univariate Analysis	Multivariate Analysis
Cross-sectional Studies
Caucasian	The USA Beaver Dam Eye Study¹⁵	43-86	4,926	Applanation (GAT^*)	Positive	Not significant
	The USA Framingham Eye Survey¹⁴	52-85	2,631	Applanation (GAT^*)	Positive^†	Not done
	The Italian Egna-Neumarkt Study¹¹	≥40	4,297	Applanation (GAT^*)	Positive	Not done
	The Australia Melbourne Visual Impairment Project¹⁸	≥40	4,576	Applanation (Tono-Pen)	Negative	Not significant
	The Blue Mountains Eye Study¹⁷	≥49	3,260	Applanation (GAT^*)	Positive	Not significant
	The Baltimore Longitudinal Study of Aging¹⁹	19-89	572	Schiotz	Not significant	Not significant
African	The Barbados Eye Study²⁰	40-84	4,601	Applanation (GAT^*)	Positive	Positive
American
Japanese	Shiose Y²¹	10s-70s	27,969 S	Schiotz or noncontact	Negative	Negative
	Nomura H et al²²	40-80	1,317	Noncontact	Negative	Negative
	Nomura H et al²³	20-79	69,643	Noncontact	Negative	Negative
	Mori K et al²⁴	14-94	70,139	Noncontact	Negative	Negative
Korean	Lee et al²⁷	20s-70s	13,212	Noncontact	Not	Negative
					significant
Longitudinal Studies
Caucasian	The Baltimore Longitudinal Study of Aging¹⁹	21-85	413	Schiotz	Not significant
Japanese	Nakano T et al²⁵	21-49	2,330	Applanation (GAT^*)	Negative
	Kashiwagi K et al²⁶	≥40	219	Noncontact	Negative
	Nomura H et al²³	20-79	38,554	Noncontact	Positive

^* Goldmann applanation tonometry.

^† Up to the age of 74.

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