2018-04-18 المؤتمر العلمي الثاني للمعهد القومي لعلوم المسنين جامعة بني سويف بعنوان" التحديات والمستجدات العالمية في رعاية المسنين" http://www.bsu.edu.eg/ShowConfDetails.aspx?conf_id=217

1. Relationship between Body Mass
Index and Intraocular Pressure

2. ABSTRACT
Background: Obesity is considered a major public health problem and has
been linked with eye diseases such as cataract, glaucoma, as it has an effect
on intraocular pressure. The purpose of the current study was to investigate
the relationship between body mass index and IOP. Materials and Methods:
450 Egyptian subjects clinically and medically stable during the study without
any known systemic diseases were included in this study their mean age
ranged from (48.91±9.142) years, mean BMI was (28.4006±6.21380) Kg/m²
and mean IOP was (17.7416±3.39424). Investigation was done to evaluate
BMI and IOP. BMI was calculated by dividing weight in kilograms by the square
of height in meters and IOP was measured in mmHg by using Goldmann
Applanation Tonometer. Subjects were assigned into three groups according to
their BMI: group one: their BMI was < 25 Kg/m2 (underweight and normal
subjects), group two: their BMI was (25 to < 30) Kg/m2 (overweight subjects)
and group three: their BMI was ≥ 30 Kg/m2 (obese subjects). Data obtained
from all groups to examine intraocular pressure in relation to BMI were
statistically analysed and compared with each other.

3. Results: The study results showed a significant effect of BMI on
IOP where P value was (0.001) while there was no significant
effect of both BMI and age on IOP where P value was (0.718)
and there was positive correlation between age and IOP where P
value was (0.026) but this correlation is weak. Conclusion: BMI
has an effect on IOP as when BMI increases the IOP also
increases while change in both BMI and age doesn’t have an
effect on IOP so obesity has been reported to be an independent
risk factor for high IOP.
Key Words: body mass index, intraocular pressure, obesity and
Goldmann Applanation Tonometer.

4. INTRODUCTION
Obesity is one of the most prevalent disorders in the world. It
constitutes an important risk for several diseases such as type
2 diabetes, hypertension, stroke, osteoarthritis, and sleep
apnea syndrome (Haslam, 2005).
Some eye diseases like cataract, glaucoma, diabetic
retinopathy and age-related macular degenerations were
reported to have potential relation to obesity (Kuang et al.,
2005, Cheung et al., 2007, Van Leiden et al., 2002 and
Clemons et al., 2005).

5. In a considerable number of patients with
glaucoma, progressive damage continues despite
intraocular pressure (IOP) reduction with
treatment (Gherghel, 2001).
Obesity possesses an increased risk for both
elevated IOP and systemic vascular abnormalities
such as hypertension and arteriosclerosis. Itmay
play a role in glaucoma progression through
elevated IOP and vascular dysregulation. Body
mass index (BMI) is one of the most specific and
objective measurements to define obesity
(Haslam, 2005).

6. The need for this study was developed
because common problems such as obesity
may be a risk factor for several diseases
including eye diseases such as glaucoma,
cataract and diabetic retinopathy via
increasing IOP (Haslam, 2005).

7. MATERIALS AND METHODS
This study was conducted in the Faculty of
Physical Therapy, Cairo University from April 2014
to January 2016 and was approved by the Ethical
Committee No.: P.T.REC/012/00625.
Subjects: 450 Egyptian subjects were included in
this study their mean age was (49.91+9.142)
years, mean BMI was (28.4006+6.21380) Kg/m²
and mean IOP was (17.7416+3.39424) and
assigned into three groups according to their BMI,
investigation was done to evaluate BMI and IOP.

8. Group one: their BMI was < 25 Kg/m2
(underweight and normal subjects).
• Group two: their BMI was (25 to < 30)
Kg/m2 (overweight subjects).
• Group three: their BMI was ≥ 30 Kg/m2
(obese subjects).
The Exclusive criteria items were: subjects
with significant ocular disease, presence of
impaired mental status, diabetes mellitus,
hypertension and CNS stroke.

9. Measurments:
Goldmann Applanation Tonometer (GAT):
IOP was measured by GAT (TOPCON CORPORATION, SL-3C,
No. 641734) between 9 and 11 a.m where normal IOP is
ranged from 10-20 mmHg (according to the manufacturer
analyzer).
The probe of the GAT made contact with the cornea so a
topical anesthesia was used (Benox) and was introduced
onto the surface of the eye in the form of eye drops.
A special disinfected prism is mounted on the tonometer
head and then placed against the cornea.
A cobalt blue filter was used to view two green semi
circles.
The force applied to the tonometer head is then adjusted
using the dial until the inner edges of these green
semicircles meet.

10. BMI
BMI
=
Mass(kg)
(height (m)2)
=
Mass (Ib)2
X703(height (in))2
Body Mass Index (BMI):
•BMI was measured by the individuals’ body weight in kilograms divided by the square of their height in meters (Ekmoyan, 2007).
(Barlow, 2007)

11. BMI Chronic disease risk
Below 18.5 Underweight
18.5-24.9 Normal
25.0-29.9 Overweight
30.0 and
above
Obese
Table (1): Classification of adult underweight, overweight and obesity
according to BMI (Centers for Disease Control and Prevention, 2009).

12. *Cut offs may not be appropriate for >65 year
olds.
Weight and height were measured by (weighting
scale ZT-150, Made in china) in a standing
position without shoes.
When measuring height we ensure the
consistent posture and head positioning of
participants.

13. Data analysis:
• IOP was measured for both right and left eyes and their
mean was calculated.
• Descriptive statistics were conducted to compare BMI, IOP
and age between three groups.
• One-way analysis of variance (ANOVA) was conducted to
compare independent (unrelated) groups.
• Post hoc tests multiple comparisons LSD was conducted to
determine the difference between each pair of means.
• Pearson correlation test was conducted to determine the
correlations between age, BMI and IOP.
• Two-way ANOVA was conducted to compare the mean
differences between groups that have been split on two
independent variables (called factors).
• The level of significance for all statistical tests was set at p
< 0.05.

14. N Mean Min. Max.
BMI(kg/m2) 450
28.4006
± 6.21380
15.10 46.20
IOP(mmHg.avar
age±S.D)
450
17.7416
± 3.39424
10.00 25.00
Age
(year.avarage ±
S.D)
450 48.91±9.142 30 60
RESULTS
Demographic data:
450 subjects their age ranged from (30-60 yrs.) and table (2) show the descriptive statistics of the all subjects.
Table (2): Mean, S.D and min. max. of (BMI, IOP and age).
BMI: Body mass index; MIN: Minimm; MAX: Maximum; IOP: Intra ocular pressure and SD: Standard deviation.

15. Groups Mean N P-value
less than 25kg/m² 22.4398±2.03850 1166
0.0001**
(25 less than 30) kg/m² 27.5604±1.50745 1126
(greater than or equal 30) kg/m² 35.3334±4.21210 1158
Total 28.4006±6.21380 4150
Table (3): Comparison between groups according to their BMI
P-value: Probability value and ** significant at 0.05.

16. BMI
group(1)(<25Kg/m²)
group(2)
(25≤BMI<30Kg/m²
)
group(3) (≥30Kg/m²)
N Mean N Mean N Mean
IOP 166 15.77±3.07 126 18.1±3.04 158 19.52±2.89
Age 166 47.2±9.39 126 49±9.59 158 50.64±8.19
There was significant statistical difference between three groups according to their BMI as in table (3).
Table (4): Comparison between groups according to IOP and Age
BMI: Body mass index and IOP: Intra ocular pressure.

17. SS df Mean Square F P-value
Between
Groups
1160.652 2 580.326
64.654 0.0001**
Within
Groups
4012.211 447 8.976
Total 5172.863 449
Table (5): One –Way ANOVA
SS: Sum of squares; DF: Degree of freedom; P-value: Probability value; F: Analysis of variance and **
significant at 0.05.
There were statistical significant differences at 0.05 between groups of BMI and IOP as shown in table
(5).

18. Groups
MD
(I-J)
Std. Error Sig.
95% CI
Lower Bound Upper Bound
<25
25-30 -2.33098-* 0.35399 0.0001 -3.0267 -1.6353
≥30 -3.74893-* 0.33299 0.0001 -4.4033 -3.0945
25-30
<25 2.33098* 0.35399 0.0001 1.6353 3.0267
≥30 -1.41795-* 0.35784 0.0001 -2.1212 -0.7147
≥30
<25 3.74893* 0.33299 0.0001 3.0945 4.4033
25-30 1.41795* 0.35784 0.0001 0.7147 2.1212
Post Hoc Tests Multiple Comparisons LSD:
Table (6): Post Hoc Tests Multiple Comparisons LSD
Std Error: Standard error; CI: Confidence interval; MD: Mean
difference and * the mean difference is significant at the 0.05 level.
There was a significant difference between groups as
when BMI increased the IOP also increased as shown
in table (6).

19. Table (7):Correlations between age and BMI
Age BMI
Age
Pearson Correlation 1 .137**
Sig. (2-tailed) 0.004
N 450 450
BMI
Pearson Correlation .137** 1
Sig. (2-tailed) 0.004
N 450 450
Correlations between age, BMI and IOP:
BMI: Body mass index and ** Correlation is significant at the 0.01 level (2-tailed).
There was a positive correlation between age and BMI as shown in table (7).

20. Table (8): Correlations between BMI and IOP
BMI IOP
BMI
Pearson Correlation 1 .440**
Sig. (2-tailed) 0.0001
N 450 450
IOP
Pearson Correlation .440** 1
Sig. (2-tailed) 0.0001
N 450 450
IOP: Intra ocular pressure; BMI: Body mass index and ** Correlation is
significant at the 0.01 level (2-tailed).
There was a positive correlation between BMI and IOP, This means when BMI
increases the IOP increases as shown in table (8).

21. Age IOP
Age
Pearson Correlation 1 .105*
Sig. (2-tailed) 0.026
N 450 450
IOP
Pearson Correlation 0.105* 1
Sig. (2-tailed) 0.026
N 450 450
Table (9): Correlations between AGE and IOP
IOP: Intra ocular pressure and * Correlation is significant at the 0.05
level (2-tailed).
There was a positive correlation between age and IOP but this correlation is
weak as shown in table (9).

22. Value Label N
BMI (category)
1.00 <25 166
2.00 25-30 126
3.00 ≥30 158
AGE (category)
1.00 30-49 191
2.00 Above 49 259
Two-way ANOVA
Table (10): Between-Subjects Factors
BMI: Body mass index and N: Number.

23. Source Type III SS df
Mean
Square
F P-value
Corrected Model 1166.803a 5 233.361 25.864 0.000
Intercept 135461.103 1
135461.10
3
15013.438 0.000
BMI 1105.970 2 552.985 61.289 0.000
AGE 0.022 1 0.022 0.002 0.961
BMI* AGE. 5.978 2 2.989 0.331 0.718
Error 4006.060 444 9.023
Total 146816.120 450
Corrected Total 5172.863 449
a. R Squared = 226 (Adjusted R Squared = .217)
Table (11): Tests of Between-Subjects Effects
SS: Sum of squares; BMI: Body mass index; P value: Probability value; DF: Degree of freedom and F:
Analysis of variance.
There was a significant effect of BMI on IOP, while there was non-significant effect of age on IOP as shown in
table (10 and 11).
The effect of both BMI and age on IOP was non-
significant.

24. DISCUSSION
These findings are in agreement with the study of Tina et al.,
(2009), where they conducted a study on the relationship of
intraocular pressure with age, systolic blood pressure, and
central corneal thickness in an Asian population and found
that IOP increased with age to the sixth decade, also systolic
BP increased linearly with age. In the Beaver Dam longitudinal
Eye Study of Klein et al., (2005), the relationship between
intraocular pressure and systemic blood pressure was
investigated and studies showed that there were significant
direct correlations between changes in systemic blood
pressures and changes in intraocular pressure over five years
of the study. Blood pressure has been found to increase with
age in most populations, and intraocular pressure (IOP) has
been found to be associated with systemic blood pressure
levels in population based studies.

25. The findings on blood pressure is in agreement
with the study of Tesfay et al., (2007), on the
association between body mass index and blood
pressure across three populations in Africa and
Asia which showed that Mean BP levels increased
with increasing BMI. It was also confirmed with the
study of Stamler et al., (1978), in Caucasian
populations where a positive association between
body mass and BP has been documented but
there are no documented studies on the
relationship between BMI, IOP and blood pressure
in the black population.

26. In a study led by Mori et al., (2000), conducted a cross-
sectional analysis on 25,296 Japanese men and
women. Patients were measured multiple times during
a 10-year period for IOP, blood pressure and weight.
Mean IOP measurements at baseline were 11.6 mm
Hg. After controlling for age, sex and blood pressure,
researchers found a significant association between
longitudinal change in IOP and change in weight. These
findings suggest that obesity is an independent risk
factor for increase in IOP.

27. Furthermore, Lee et al., (2002), compared the
incidence of elevated IOP in patients who were
systolic or diastolic hypertensive and obese
(group 1) and patients who were systolic or
diastolic hypotensive and lean (group 2). IOP
increased significantly with increasing systolic
blood pressure, diastolic blood pressure and
obesity index (P < .05). The mean IOP of group 1
was higher than that of group 2. The difference
in IOP was statistically significant.

28. In contrast, Remzi et al., (2012), demonstrated 140 subjects without any
known systemic diseases were included in the study. IOP and OPA were
measured with DCT under topical anesthesia. There is a quality grading
for DCT measures. Based on this grading, score number 1 is identified as
"the best," score number 2 and 3 are identified as "acceptable," and 4
and 5 are identified as "not acceptable". The results showed no significant
statistical difference between the groups in terms of age, gender, IOP,
systolic and diastolic blood pressure (value, 0.406, 0.707, 0.124, 0.124,
0.081 respectively). Mean of OPA was the lowest in group3 and highest in
Group1. There was a significant statistical difference between the groups
in terms of the mean OPA value (P=0.001). In addition, a negative
correlation was found between the OPA and BMI values (P=0.006, r= -
0.231).
In contrast, many cross-sectional studies in western populations have
reported a positive correlation between IOP and age (Martin et al., 1985).

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