Relationship between intraocular pressure and obesity in Japan

Keiko Moria, Fujiko Andob, Hideki Nomurab, Yuzo Satoa and Hiroshi Shimokatab

a Research Center of Health, Physical Fitness and Sports, Nagoya University, Nagoya, Japan.
b Department of Epidemiology, National Institute for Longevity Sciences, Obu, Aichi, Japan.

Reprint requests to: Keiko Mori, Department of Living Science, Chukyo Junior College, 2216 Toki-cho, Mizunami-shi, Gifu, 509–6192 Japan.


    Abstract
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Background Some cross-sectional studies have suggested that age, systolic blood pressure and obesity are positively related to intraocular pressure (IOP), but few longitudinal studies have examined this relationship. This study was carried out to evaluate the association between intraocular pressure and obesity by cross-sectional and longitudinal analyses in a large Japanese population.

Methods Data were collected from annual health examinations between 1989 and 1997 and reviewed retrospectively. Subjects of the cross-sectional analysis were 70 139 males and females aged 14–94 years. Among these subjects, 25 216 males and females who had undergone IOP measurements more than three times were analysed longitudinally. The association between IOP and obesity was examined cross-sectionally and longitudinally.

Results Cross-sectional analysis: The mean IOP at the last visit was 11.6 mmHg. The IOP decreased gradually with age and was significantly higher in males than in females in almost all age groups. Body mass index (BMI) significantly correlated with IOP after controlling for age, gender and blood pressure. Longitudinal analysis: There was a significant association between longitudinal change in IOP and change in weight. This relationship remained significant after controlling for initial BMI, initial blood pressure, change in blood pressure, gender and age.

Conclusion This study showed a significant association between IOP and obesity in both cross-sectional and longitudinal analysis. These findings suggest that obesity is an independent risk factor for increase in IOP.

Keywords Intraocular pressure, obesity, cross-sectional analysis, longitudinal analysis, blood pressure, Japanese population

Accepted 17 December 1999


    Introduction
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
The development of glaucomatous optic nerve damage, based on visual field loss and/or optic disc findings, is more likely to be associated with high intraocular pressure (IOP),1–4 although IOP is not the only risk factor for glaucomatous optic nerve damage.

In addition, a previous report demonstrated that relatively high IOP in normal-pressure glaucoma is related to optic nerve damage.5 Therefore it is important to identify factors that influence the level of IOP and prevent increased IOP. A number of studies have attempted to identify risk factors associated with the development of elevated IOP.6–21 Several cross-sectional studies in western populations have suggested that age and systolic blood pressure (SBP) related positively to IOP.6,9,11,13–21 However, there were a few studies that showed a negative association between age and IOP in a Japanese population.22,23

Moreover, some epidemiological studies examined the relationship between obesity and IOP cross-sectionally.15,22–25,28 These studies found that obesity was an independent risk factor for increase in IOP, even when considered with age, SBP and diastolic blood pressure (DBP).15,22,23 There were few longitudinal studies that showed a positive relationship between change in IOP and change in SBP.26 In addition, no longitudinal studies have shown an association between IOP and obesity in general populations. However, previous study in our laboratory showed that IOP significantly increased with age in longitudinal analysis, but significantly decreased with age in cross-sectional analysis.29

This study investigated cross-sectional and longitudinal associations between IOP and obesity in a large male and female Japanese population.


    Methods
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Subjects were 70 139 males and females, aged 14–94 years, who were office workers, and their family members. These subjects all underwent comprehensive medical check-ups in a health check facility between 1989 and 1997. Subjects receiving medical treatment for glaucoma, hypertension and/or diabetes mellitus were excluded. Most of the subjects lived in Aichi Prefecture, a region in the centre of Japan. Among these subjects, 25 216 males and females who had more than three IOP measurements were analysed longitudinally. Characteristics of these subjects are shown in Table 1Go.


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Table 1 Distribution of age and gender at the last tonometry reading (cross-sectional total sample)
 
The examinations included visual acuity, tonometry, anthropometry, blood pressure and laboratory measurements. The IOP was determined by the mean value of three successive readings of the right eye with a non-contact tonometer (Canon T-2) between 9 and 11 a.m. Height and weight were measured with the subjects wearing a lightweight hospital gown in a standing position without shoes. Body mass index (BMI) was calculated as weight (kg) divided by height (m) squared. Blood pressure was taken in the sitting position at the right upper arm.

Cross-sectional analysis was based on data obtained at the last visit of each subject. The association of IOP and BMI with age was analysed in a linear regression model. Partial correlation coefficients among IOP, SBP, DBP and BMI controlled for age were examined in males and females. Gender was entered as a dichotomous variable (male = 0, female = 1). The relationship between BMI and IOP controlled for age, gender, SBP and DBP was also studied by analysis of covariance (ANOCOVA).

For longitudinal analysis, the individual-specific linear regression model was used. For each subject, the regression slope from three or more IOP measurements against age was calculated (slope of IOP). Similarly, the slope of weight, slope of SBP, and slope of DBP against age were calculated individually. The dependence of slope of IOP on slope of weight, age, gender, slope of weight, initial SBP, slope of SBP, initial DBP, slope of DBP, initial BMI, and initial IOP was investigated by multiple regression analysis. Moreover, the relationship between slope of weight and slope of IOP were studied by ANOCOVA controlling for age, gender, initial BMI, initial SBP, slope of SBP, initial DBP, slope of DBP, and initial IOP.

All data were processed and analysed by the Statistical Analysis System30 (SAS version 6.12).


    Results
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
Cross-sectional analysis
The mean age of the 70 139 subjects was 46.2 years (range: 14–94 years); 62.0% of the subjects were male. The overall prevalence of ocular hypertension, usually defined as IOP >21 mmHg, was 0.2%. Table 1Go shows that the mean IOP value was slightly higher in males (11.7 mmHg) than in females (11.4 mmHg), with a significant difference (P < 0.001).

Age-specific IOP values estimated by the least square method in the multiple linear regression models controlled for SBP, DBP and BMI are plotted in Figure 1Go. Age-specific BMI was also plotted. The IOP decreased with age in both genders, and IOP value was generally higher in men than in women. In males, BMI sharply increased with age up to 35 years, but in females increased slowly up to 60 years old and was significantly higher in males than in females up to 60 years. Over 65 years old, BMI gradually decreased in males and there was no gender difference in BMI.



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Figure 1 Cross-sectional changes of intraocular pressure and body mass index with age (5-year moving average). Age-specific intraocular pressure and body mass index values are shown by the least square methods in the multiple linear regression model. Intraocular pressure is controlled for systolic blood pressure, diastolic blood pressure, and body mass index

 
Partial correlation coefficients among IOP, SBP, DBP, BMI and age in males and females were calculated to explore the independent effects of SBP, DBP and BMI on IOP controlled for age (Table 2Go). In both genders, SBP, DBP and BMI were positively correlated with IOP (P < 0.0001).


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Table 2 Partial correlation coefficient with intraocular pressure (cross-sectional study)
 
Intraocular pressure increased significantly after controlling for age, gender, SBP and DBP. Intraocular pressure significantly increased with BMI (trend, P < 0.0001) (Figure 2Go).



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Figure 2 Estimated intraocular pressure (mean, standard error) by body mass index in cross-sectional analysis. Intraocular pressure values are examined by ANCOVA controlled for age, gender, systolic blood pressure, and diastolic blood pressure. (Trend, P < 0.0001)

 
Longitudinal analysis
The numbers and characteristics of subjects at each visit for annual health examination between 1989 and 1997 are shown in Table 3Go. In all, 25 216 people had undergone IOP measurements more than three times and they were analysed longitudinally.


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Table 3 Numbers and characteristic of subjects in each visit (longitudinal subsamples)
 
The mean age of subjects during follow-up was 44.2 years (range: 17–81 years); 67% were male. The distribution of age, gender and the means of other values did not differ from those of the cross-sectional sample.

The multiple linear regression models disclosed the influence of slope of weight and the other variables on slope of IOP (Table 4Go). Slope of weight, initial BMI, initial SBP, slope of SBP, and initial DBP were positively associated with the slope of IOP (P < 0.0001). Age, gender and initial IOP negatively related to the slope of IOP (P < 0.0001). The slope of DBP was not significantly associated with the slope of IOP. In addition, the relationship between slope of IOP and slope of weight was examined by ANOCOVA after controlling other factors. There was a significant positive trend between slope of IOP and slope of weight after controlling for age, gender, initial BMI, initial SBP, slope of SBP, initial DBP, slope of DBP and initial IOP (trend, P < 0.0001) (Figure 3Go).


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Table 4 Multiple regression analysis for slope of intraocular pressure (longitudinal study)
 


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Figure 3 Estimated slope of intraocular pressure (mean, standard error) by slope of weight by years (in longitudinal study). Slope of intraocular pressure is shown by ANCOVA controlled for age, gender, initial body mass index, initial systolic blood pressure, slope of systolic blood pressure, initial diastolic blood pressure, slope of diastolic blood pressure, and initial intraocular pressure. (Trend, P < 0.0001)

 

    Discussion
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
This study evaluated risk factors for increased IOP in a large Japanese population using cross-sectional and longitudinal methodology. Thus, this study may provide clearer information than other studies about IOP and the factors which increase IOP such as, age, gender, blood pressure and obesity.

In this cross-sectional study, the mean IOP using non-contact tonometry was 11.7 mmHg in males and 11.4 mmHg in females. These values were substantially lower than the findings of other surveys using applanation tonometry; the values are between approximately 14–17 mmHg.4,11,13–15,18,19 Shiose et al., using non-contact tonometers, showed mean IOP values in an apparently normal population of males and females (12.0, 11.5 mmHg, respectively) which were almost equal to our findings.23,24

In our longitudinal study, the initial IOP was highly negatively associated with the slope of IOP. This may be due to regression toward the mean. This phenomenon is widespread in applied science, especially physiological variability. In longitudinal studies, examinations are repeated over time in the same individual. If the initial value is unusually high, it can be expected that the subsequent readings are likely to be closer to the centre of distribution. Because of this phenomenon, the initial value of the examinations tends to correlate negatively with subsequent changes in value.

Many cross-sectional studies in western populations have reported a positive correlation between IOP and age.10,11,13,17–21 While there are individual variations, the effects of ageing become more apparent in females than in males over 40–45 years old.17–19 In cross-sectional studies by Shiose et al.23,24 and Kurokawa27 in Japanese, the IOP decreased with age in both genders. Such a paradoxical result seems to be difficult to explain without considering the effects of other factors. In addition, true changes in IOP with age cannot be determined by cross-sectional statistics alone. A report from the Baltimore Longitudinal Study of Aging showed that there was no consistent relationship between 2-year longitudinal change in IOP and age in a healthy white male, after controlling for other factors.26 However, we found that IOP decreases with age, even when analyses were considered with blood pressure and BMI in cross-sectional study. We also found that longitudinal change in IOP was more strongly influenced by change in weight and change in blood pressure than ageing.

In our cross-sectional data, we confirmed that an increase of SBP and DBP related to IOP, after controlling for age, gender and BMI. For longitudinal study, we recognized that the slope of SBP correlated with an increase in IOP. In addition, slope of SBP was an independent factor influencing increase in IOP, although the standardized coefficient of multiple regression analysis was slightly less than that of the slope of weight. The relationship between IOP and the slope of DBP in longitudinal analyses was smaller than slope of SBP.

A number of papers have reported the positive correlation between IOP and SBP. However, the relation between DBP and IOP was shown in few studies. In addition, data from a longitudinal study by Mcleod et al.26showed that change in IOP was positively correlated with change in SBP over both 1- and 2-year periods. However, change in DBP was negatively correlated with change in IOP over a 2-year period. It appears that our data are generally consistent with previous studies. The results of our cross-sectional and longitudinal study support the hypothesis that increased SBP is closely associated with increased IOP.

The mean BMI in our study was 22.9 for males and 21.6 for females. The prevalence of obesity (BMI >= 26.4) was 10.9% in males and 6.5% in females. These percentages were slightly lower than those obtained by the National Nutrition Survey conducted in 1990–1994 in Japan.31 The cross-sectional curve of BMI with age and the prevalence of obesity were similar to reports from other medical centres in Japan.32,33

Obesity is a strong risk factor for hypertension and diabetes mellitus.

In addition to hypertension and diabetes mellitus, the Barbados Eye Study found several other factors associated with an increase in IOP using multiple regression analysis. Larger body size, as measured by BMI, was associated with increasing IOP.22 A high prevalence of obesity has been reported in Barbados. However, the association between larger size and IOP was found to be independent of hypertension and diabetes mellitus, but not directly related with open angle glaucoma. A relation between obesity and IOP was also found in studies by Shiose et al.,23,24 Klein et al.15 and Bulpitt et al.25 (Japanese, American and British populations, respectively). Our cross-sectional data demonstrated that BMI was significantly correlated with IOP after adjusting for age, gender, SBP and DBP. In addition, our longitudinal results provided evidence that, among the factors studied, the strongest relation existed between change in IOP and change in weight and change in weight was an independent risk factor for increase in IOP. In other words, these data suggested a strong positive association between obesity and IOP.

The mechanism has been explained in previous reports22,23,25,34 as follows; IOP may increase due to excess intraorbital fat tissue, an increase in episcleral venous pressure and a consequent decrease in outflow facility. Obesity increases blood viscosity through increasing red cell count, haemoglobin and haematocrit, and consequently increased outflow-resistance of episcleral veins results. Further, obesity is also a risk factor for hypertension. Elevated blood pressure increases IOP by increasing ciliary artery pressure and ultrafiltration of the aqueous humour.

Thus, the combined evidence from several studies now suggests that high levels of BMI and increased BMI are strongly associated with risk of increased IOP. Our outcome reaffirms the importance of weight control in preventing increased IOP.


    Acknowledgments
 
The authors would like to express sincere gratitude to late professor Fumio Kuzuya, Oriental Industrial Health Associates, for support of this study.


    References
 Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 
1 Sommer A. Intraocular pressure and glaucoma. Am J Ophthalmol 1989;107:186–88.[ISI][Medline]

2 Leske MC, Connell AM, Wu SY et al.. Risk factors for open-angle glaucoma. The Barbados Eyes Study. Arch Ophthalmol 1995;113: 918–24.[Abstract]

3 Tielsh JM, Katz J, Sommer A, Quigley HA, Javitt HA. Hypertension, perfusion pressure, and primary open-angle glaucoma. Arch Ophthalmol 1995;113:216–21.[Abstract]

4 Mitchell P, Smith W, Attebo K, Healey PR. Prevalence of open-angle glaucoma in Australia. The Blue Mountains Eye Study. Ophthalmology 1996;103:1661–69.[ISI][Medline]

5 Jonas JB. Pressure-dependent neuroretinal rim loss in normal-pressure glaucoma. Am J Ophthalmol 1998;125:137–44.[ISI][Medline]

6 Carel RS, Korczyn AD, Rock M, Goya I. Association between ocular pressure and certain health parameters. Ophthalmology 1984;91: 311–14.[ISI][Medline]

7 Kahn HA, Leibowitz HM, Ganley JP et al. The Framingham Eye Study: II. Association of ophthalmic pathology with single variables previously measured in the Framingham Heart Study. Am J Epidemiol 1977;106:33–41.[Abstract]

8 Wilson MR, Hertzmark MA, Walker AM, Childs-Shaw K, Epstein DL. A case-control study of risk factors in open angle glaucoma. Arch Ophthalmol 1987;105:1066–71.[Abstract]

9 Leske MC, Podgor MJ. Intraocular pressure, cardiovascular risk variables and visual field defects. Am J Epidemiol 1983;118:280–87.[Abstract]

10 Martin MJ, Sommer A, Gold EB, Diamond EL. Race and primary open angle glaucoma. Am J Ophthalmol 1985;99:383–87.[ISI][Medline]

11 Klein BEK, Klein R. Intraocular pressure and cardiovascular risk variables. Arch Ophthalmol 1981;99:837–39.[Abstract]

12 Morgan RW, Drance SM. Chronic open angle glaucoma and ocular hypertension: an epidemic study. Br J Ophthalmol 1975; 59:211–15.[Abstract]

13 Bengtssone B. Some factors affecting the distribution of intraocular pressure in a population. Acta Ophthalmology 1972;50:33–46.

14 Dielemans I, Vingerling JR, Algra D et al. Primary open-angle glaucoma. Intraocular pressure and systemic blood pressure in the general elderly population. The Rotterdam Study. Ophthalmology 1995;102:54–60.[ISI][Medline]

15 Klein BEK, Klein R, Linton KL. Intraocular pressure in an American community: The Beaver Dam Eye Study. Invest Ophthalmol Vis Sci 1992;33:2224–28.[Abstract]

16 Graham P. Epidemiology of simple glaucoma and ocular hypertension. Br J Ophthalmol 1972;56:223–29.[ISI][Medline]

17 Hollow FC, Graham PA. Intraocular pressure, glaucoma and glaucoma suspects in a defined population. Br J Ophthalmol 1966;50:570–86.[ISI][Medline]

18 Armaly MF. On the distribution of applanation pressure. Arch Ophthalmol 1965;73:11–18.[ISI]

19 Armaly MF. Age and sex correlation of applanation pressure. Arch Ophthalmol 1967;78:480–84.[ISI][Medline]

20 Klein BEK, Klein R, Moss SE. Intraocular pressure in diabetic persons. Ophthalmology 1984;91:1356–60.[ISI][Medline]

21 Seddon JM, Schwartz B, Flowerdew G. Case-control study of ocular hypertension. Arch Ophthalmol 1983;101:891–94.[Abstract]

22 Wu SY, Leske MC. Associations with intraocular pressure in the Barbados Eye Study. Arch Ophthalmol 1997;115:1572–76.[Abstract]

23 Shiose Y. The aging effect on intraocular pressure in an apparently normal population. Arch Ophthalmol 1984;102:883–87.[Abstract]

24 Shiose Y, Kawase Y. A new approach to stratified normal intraocular pressure in a general population. Am J Ophthalmol 1986;101:714–21.[ISI][Medline]

25 Bulpitt CJ, Hodes C, Everitt MG. Intraocular pressure and systemic blood pressure in the elderly. Br J Ophthalmol 1975;59:717–20.[Abstract]

26 Mcleod SD, West SK, Quigley HA, Fozard JL. A longitudinal study of the relationship between intraocular and blood pressures. Invest Ophthalmol Vis Sci 1990;31:2361–66.[Abstract]

27 Kurokawa M. Studies on the normal intraocular pressure. The average distribution and difference of both sexes and the aging of the normal intraocular pressure. J Jpn Ophthalmol Soc 1969; 73:112–22.

28 Rouhiainen H, Terasvirta M. Correlation of some ocular and hematological factors and intraocular pressure in an aged population. Acta Ophthalmol 1991;69:76–78.

29 Nomura H, Shimokata H, Ando F, Miyake Y, Kuzuya F. Age-related changes in intraocular pressure in a large Japanese population: a cross-sectional and longitudinal study, Ophthalmology 1999;106:2016–22.[ISI][Medline]

30 SAS Institute Inc. SAS/STAT Software Changes and Enhancements through 6.12. Cary, NC: SAS Institute Inc., 1998.

31 Yoshiike N, Matumura Y, Zaman MM, Yamaguti M. Descriptive epidemiology of body mass index in Japanese adults in a representative sample from the National Nutrition Survey 1990–1994. Int J Obesity 1998;22:684–87.[ISI][Medline]

32 Sasaki A, Ikeda Y. A study of starting-age for guidance of obesity judging from the distribution of the mean BMI by decades. Proceeding of the 9th Congress of J Jpn Obesity Soc 1988, pp.258–59 (In Japanese).

33 Yoshinaga H, Sha S. Relationship between frequency of obesity and incidence of disease in a medical examination center. J Jpn Obesity Soc 1998;4:49–53 (In Japanese).

34 Shiose Y. Intraocular pressure: new perspective survey. Ophthalmology 1990;34:413–35.