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ORIGINAL ARTICLE
Year : 2019  |  Volume : 22  |  Issue : 4  |  Page : 539-545

Evaluation of intraocular pressure and retinal nerve fiber layer, retinal ganglion cell, central macular thickness, and choroidal thickness using optical coherence tomography in obese children and healthy controls


1 Clinics of Pediatric Endocrinology, Antalya Training and Research Hospital, Antalya, Turkey
2 Clinics of Ophthalmology, Antalya Training and Research Hospital, Antalya, Turkey
3 Clinics of Physical Therapy and Rehabilitation, Antalya Training and Research Hospital, Antalya, Turkey
4 Clinics of Pediatric Allergy, Antalya Training and Research Hospital, Antalya, Turkey
5 Department of Pediatric Endocrinology, Faculty of Medicine, Hacettepe University, Ankara, Turkey

Date of Acceptance18-Dec-2018
Date of Web Publication11-Apr-2019

Correspondence Address:
Dr. R T Baran
Clinics of Pediatric Endocrinology, Antalya Training and Research Hospital, Antalya
Turkey
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/njcp.njcp_471_18

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   Abstract 


Objective: Obesity affects many organ systems. There have been few studies on the ophthalmological effects of obesity. The aim of the present study was to evaluate the changes in the ophthalmological parameters in obese children. Subjects and Methods: The study included 61 obese and 35 age-and gender-matched control subjects. Obesity was defined as body mass index-standard deviation score (BMI-SDS) >2 SD. Children with a BMI-SDS between >−1 SD and <+1 SD whilst otherwise healthy were recruited as the control group. All clinical and ophthalmological investigations were performed by a pediatric endocrinologist and an experienced ophthalmologist. The ophthalmological examination and intraocular pressure (IOP) measurement was performed. The average retinal fiber layer (RNFL), retinal ganglion cell (RGC), central macular thickness (CMT), cup-to-disk ratio (C/D), and central choroidal thickness (CT) were measured using spectral domain optical coherence tomography. The anthropometric, biochemical, and ophthalmological parameters of the obese and control subjects were compared. Results: IOP was higher in the obese group compared to the control group (P = 0.008), whereas the average RNFL was lower in the obese group (P = 0.035). There was a negative correlation between the average RNFL and BMI-SDS (P = −0.044) and waist–hip ratio (P = 0.015). There was no statistically significant difference between the RGC, C/D, CMT, and CT of the obese and control groups. IOP was negatively correlated with HOMA-IR, body fat mass, body fat percentage, and diastolic blood pressure. Conclusion: In the present study, which evaluated obesity and its effects on ophthalmological parameters, the elevated IOP and decreased RNFL thickness detected in the obese group may suggest an increased risk for these patients of developing glaucoma at a younger age. Therefore, regular ophthalmological examinations of obese children are essential for prompt diagnosis and appropriate management.

Keywords: Childhood obesity, choroidal thickness, intraocular pressure, retinal ganglion cell, retinal nerve fiber layer


How to cite this article:
Baran R T, Baran S O, Toraman N F, Filiz S, Demirbilek H. Evaluation of intraocular pressure and retinal nerve fiber layer, retinal ganglion cell, central macular thickness, and choroidal thickness using optical coherence tomography in obese children and healthy controls. Niger J Clin Pract 2019;22:539-45

How to cite this URL:
Baran R T, Baran S O, Toraman N F, Filiz S, Demirbilek H. Evaluation of intraocular pressure and retinal nerve fiber layer, retinal ganglion cell, central macular thickness, and choroidal thickness using optical coherence tomography in obese children and healthy controls. Niger J Clin Pract [serial online] 2019 [cited 2019 Jul 24];22:539-45. Available from: http://www.njcponline.com/text.asp?2019/22/4/539/255930




   Introduction Top


Childhood obesity is a global health problem with an increasing trend in both developing and developed countries regardless of age, gender, and ethnicity. Approximately 10% of the 22 million children worldwide aged <5 years are estimated to be overweight and obese.[1] Obesity affects the physical and mental health of individuals and increases the risk of cardiometabolic disorders such as atherosclerosis, nonalcoholic fatty liver disease (NAFLD), steatohepatitis, hypertension, and diabetes mellitus. Obesity also increases the risk of visual loss associated with senile macular degeneration, diabetic retinopathy, cataract, and glaucoma.[2]

Glaucoma is a chronic optical neuropathy, which is characterized by increased intraocular pressure (IOP), optic nerve cupping, retinal ganglion cell (RGC) degeneration, and visual field defects.[3] Wu and Leske reported a strong association between IOP and systolic hypertension, diabetes, and age. Female gender, pulse rate, higher BMI, dark skin, family history of glaucoma, alcohol, and smoking have also been found to be related to an increased risk of IOP.[4]

While a positive relationship has been reported between BMI and IOP in some studies,[5],[6] others have reported no relationship.[7],[8] Oh et al. demonstrated a positive relationship between metabolic syndrome, particularly insulin resistance, and IOP.[9] There are few studies evaluating the relationship between obesity and increased IOP in children. In one such study, increased IOP was reported in 9.7% of obese children and normal IOP in all control subjects, whereas another study reported that there was no difference between the IOP of obese and healthy children.[2],[10]

The evaluation of retinal fiber layer (RNFL) is a useful tool in the diagnosis and assessment of the severity of glaucoma. The most reliable method for evaluation is spectral domain-optical coherence tomography (SD-OCT), which was first developed by Huang et al.[11] SD-OCT is a valuable method in the evaluation of ophthalmological disorders of the macula and optical nerve. As SD-OCT is a rapid, noninvasive, reproducible, and easily applicable method, it is suitable for use in children.[11]

RNFL defect is expected to have already developed in 10–50% of patients with visual field defect and cupping of the optical nerve. Therefore, evaluation of peripapillar RNFL using SD-OCT can be used not only in the follow-up but also in the early diagnosis of glaucoma. Retinal ganglion cell (RGC) complex is also measured by SD-OCT. In glaucoma, the RGC layer becomes thinner due to the death of ganglion cells.[12]

There have been few studies evaluating RNFL thickness in obese children. The aim of present study was to evaluate the BMI and adiposity markers, metabolic parameters, and ocular parameters such as IOP, mean RNFL thickness, RGC, C/D, central macular thickness (CMT), and choroidal thickness (CT) in obese children in comparison to their healthy counterparts.


   Patients and Methods Top


The present prospective cross-sectional observational study included 61 (40 female, 21 male) obese subjects (age range: 10.3–18) and 35 (20 female, 15 male) healthy controls (age range: 9.8–17.6) admitted to Pediatric Endocrinology Clinic of Health Sciences University Antalya Training and Research Hospital. Exclusion criteria included systemic diseases which may affect the IOP (such as diabetes, infectious or inflammatory diseases, hypertension, thyroid disorders), sleep apnea, pseudotumor cerebri, family history of glaucoma, pharmacological treatments, orbital and ocular diseases (previously known glaucoma and uveitis, amblyopia, any retinal or optic disk anomaly, ocular trauma, history of intraocular surgery, exophthalmos), children not sufficiently cooperative for OCT measurement, patients with retinal or optic nerve disorders, refractive error more than ±0.5 dioptres of spherical equivalence, cup-to-disk ratio (C/D) more than 0.5, asymmetry in the excavations more than 0.2, and signal strength of the OCT less than 7.

The study was conducted in accordance with the tenets of the Declaration of Helsinki. Ethical approval was obtained from the Local Ethics Committee of Antalya Training and Research Hospital (Document number: 70/01). Informed consent and an oral assent were obtained from all the patients and/or their legal guardians.

Physical examination

Height and weight measurements of patients were taken using a digital scale and wall-mounted Harpender stadiometer. Body mass index was calculated using the formula of weight in kilograms divided by the square of the height in meters (kg/m2). The height standard deviation score, weight standard deviation score, and body mass index-standard deviation score (BMI-SDS) were calculated using the age- and sex adjusted standard growth charts for Turkish children.[13] Obesity was defined as BMI-SDS >2 SD, and the normal group was defined as BMI between −1 and +1 SD. Pubertal staging was performed according to the Tanner method.[14] Blood pressure was measured using a digital automatic sphygmomanometer (Omron® M2 HEM-7121-E, Omron® Healthcare Co, Japan) after a period of resting and was repeated at least three times with 10-min intervals. Patients with a systolic and/or diastolic blood pressure higher than 95th percentile were considered hypertensive.[15]

To evaluate the body fat content and distribution, a bioelectrical impedance Tanita body composition analyzer MC-180 MA 8-contact electrode system (Tanita Corp. Tokyo, Japan) device was used according to the standardized manufacturer instructions. Blood pressure was calculated as the average of a total of three consecutive measurements made after an appropriate resting period.

Laboratory investigations

Plasma glucose levels were measured using the hexokinase method with a commercially available kit (Beckman AU5800; Beckman Coulter Diagnostics, Brea, CA). Insulin levels were determined using a chemiluminescent assay (AccessDxI800; Beckman Coulter Inc., Brea, CA), and glycosylated hemoglobin (HbA1c) levels were measured using commercially available kits and high-performance liquid chromatography (Tosoh HLC 723 G8, Tosoh Bioscience, Tokyo, Japan). Serum triglyceride (TG), total cholesterol (TC), high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol, alanine aminotransferase, aspartate aminotransferase, and creatinine levels were measured using an autoanalyzer (Beckman AU5800; Beckman Coulter Diagnostics, Brea, CA). The homeostatic model assessment of insulin resistance (HOMA-IR) was calculated using the formula of [fasting glucose (mmol/L) × fasting insulin (IU/mL)/22.5].

Ophthalmologic examination

Ophthalmologic examinations were performed in both eyes by an experienced ophthalmologist (70 eyes of nonobese and 122 eyes of obese group). All participants have undergone an ophthalmological examination including visual acuity assessment with a Snellen chart, auto kerato-refractometry, IOP with Goldman's applanation tonometer after application of a local anesthetic (hydrochloric proxymetacaine 0.5%), measurement of central corneal thickness (CCT) with an ultrasonic pachymetry (Nidek UP-1000, Nidek Co., Ltd., Gamagori, Aichi, Japan), slit-lamp-assisted biomicroscopy of the anterior and posterior segments of the eye, and fundus. IOP of each patient was measured twice using a Goldman applanation tonometer at the most appropriate position for correct measurement. None of patients required a third measurement as there was no difference over 2 mmHg between the first and second measurements. IOP was defined as the sum of two separate measurements. IOP measurement was adjusted according to CCT.

RNFL, CMT, CT, C/D, and RGC were evaluated using SD-OCT device (Cirrus HD OCT, Carl Zeiss Meditec, Dublin, CA, USA). All OCT measurements were performed by the same experienced technician. Before the measurements, the pupils of all patients' were dilated using 1% tropicamide (Tropamid; Bilim, Istanbul, Turkey). Average peripapillary RNFL thickness was measured using optic disk cube 200 × 200 protocol. Measurement was applied on superior, nasal, inferior, and temporal quadrants; then, the arithmetic mean of these measurements was calculated and named average RNFL thickness. The average macular and macular RGC layer thicknesses were measured using macular cube 512 × 128 protocol. Measurement was applied on superior, superonasal, inferonasal, inferotemporal, and superotemporal sites; then, the arithmetic mean of these measurements was calculated and named average RGC layer thickness.

CT measurements were performed by a single experienced ophthalmologist using a high-speed and high-resolution SD-OCT device. CT was measured perpendicularly from the outer edge of the retinal pigment epithelium to the choroid–sclera boundary at the fovea using a single line of 6-mm length centered horizontally on the fovea for visualization of the choroid. The Tru-Track active eye-tracking system, which enables the capture of multiple images in the same location, and the automated real-time mean function, which combines these images, were used during each image acquisition. All measurements were performed between 9:00 and 11:00 am to eliminate diurnal fluctuations.

Statistical analysis

Statistical analysis was performed using SPSS version 18.0 software (Statistics for Windows software version 18.0, SPSS Inc., Chicago, IL, USA). The Levene test was used to assess the equality of variances and the Shapiro–Wilk test for normality distribution of the data. Descriptive statistics were expressed as number and percentage for categorical variables and as mean, standard deviation, median, minimum, and maximum values for numerical variables. χ2-test was performed for comparison of the ratios. The mean values of normally distributed data were compared using Student's t-test, and the Mann–Whitney U test was applied for comparison of medians where the data were not normally distributed. Correlation analysis was performed using Pearson correlation analysis in normally distributed data and the Spearman rank test was applied to non-normally distributed data. Multivariate linear regression analysis was performed for the evaluation of independent factors affecting the IOP and RNFL. A value of P < 0.05 was accepted as statistically significant.


   Results Top


The study included 122 eyes of 61 obese patients and 70 eyes of 35 nonobese, healthy, control subjects. On the pituitary MRI, a pituitary adenoma was detected in two patients with elevated IOP and increased C/D ratio, and one patient with high IOP who was diagnosed with glaucoma; these three patients were excluded from the statistics. The mean age was 14.7 ± 1.9 years (range 10.3–18.0 years) in the obese group and 15.5 ± 1.8 years (range 9.8–17.6 years) in the control group (P = 0.052). BMI-SDS was higher in the obese group (3.12 ± 0.44) than in the control group (0.01 ± 0.72) (P < 0.001) [Table 1].
Table 1: Clinical and biochemical data of obese children and controls

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There was no statistically significant difference between the groups in respect of the female/male ratio (P = 0.509) [Table 1]. BMI-SDS, waist/hip ratio (WHR), body fat mass, body fat percentage, systolic and diastolic blood pressure, TG, TC, LDL, fasting insulin, and HOMA-IR were higher in the obese group compared to the control group, and there was no statistically significant difference in HDL and fasting glucose levels [Table 1].

IOP was higher in the obese group (17.08 ± 2.38) compared to the control group (15.52 ± 2.84) (P = 0.008) [Figure 1]. RNFL thickness was determined to be lower in the obese group than in the control group (P < 0.05) [Figure 1]. There was no statistically significant difference between the obese and control subjects in terms of RGC, C/D, CMT, and CT [Table 2].
Figure 1: Comparison of IOP and RNFL in obese versus control subjects

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Table 2: Comparison of ophthalmological evaluation findings of obese children versus controls

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Correlation analysis revealed a positive correlation between IOP and HOMA-IR, BMI-SDS, total body fat mass, body fat percentage, and diastolic blood pressure [Table 3]. Although statistically significant, the correlation coefficients were suggestive of weak correlations and the multivariate linear regression analysis did not show any of these factors as independently affecting IOP. A weak negative correlation was determined between RNFL and BMI-SDS and WHR. In regression analysis, neither of them was seen to be an independent factor. A weak negative correlation was determined between a lower C/D and elevated TG level, and a weak positive correlation between low CT and body fat percentage [Table 3].
Table 3: Correlation analysis between anthropometric and metabolic characteristics of cases and ophthalmological parameter

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   Discussion Top


In the present study, which evaluated the effects of obesity and related metabolic changes on ophthalmological parameters, obesity was found to be related with elevated IOP and decreased RNFL thickness. RGC was also found to be decreased in obese subjects though did not reach a statistical significance.

Obesity, which affects almost all organ systems, is an increasing healthcare issue worldwide.[1] The lipid accumulation in adipose organs in obesity leads to increased secretion of adipokines and cytokines such as resistin, leptin, IL-6, and tumor necrosis factor-alpha. Adiposity increases the risk of oxidative stress and causes an imbalance in the cytokine levels. While an increase in adipose tissue leads to an increase in pro-inflammatory cytokines (leptin, IL-6, etc.), a decrease in anti-inflammatory cytokines such as adiponectine is observed.[16] The mechanism by which obesity increases oxidative stress is overproduction of free oxygen radicals due to increased mitochondrial and peroxysomal fatty acid oxidation. Oxidative stress results in inflammation and changes the microenviroment, thereby causing RGC loss and axonal injury in retinal nerve fiber.[17]

A relationship between BMI and IOP has been previously reported in adults and a limited number of pediatric studies.[6],[10] An increase in IOP has been attributed to the increase in retrobulbar fat. This in turn decreases the ocular blood flow, thereby affecting the RFNL.[18] However, increased viscosity due to an increase in red blood cell mass in obese subjects has been suggested to cause an increase in episcleral veins and further increase the IOP.[4] In a study by Akinci et al. of 72 obese patients and healthy control subjects, it was reported that IOP was elevated in obese children, even after adjustment for systolic and diastolic blood pressure.[10] However, this has not been confirmed in some other studies conducted on obese children which reported no difference between the obese children and control groups.[2] In the present study, although all the values were within the normal ranges, IOP was found to be higher in obese children compared to their healthy counterparts. Nevertheless, despite reaching statistical significance, as the difference between the IOP of the obese and control groups was very small (1.56 mmHg), it was not considered as evidence for clinical significance. Even so, this has not excluded the increased risk of developing glaucoma in later life. In addition, a positive correlation was found between IOP and HOMA-IR, body fat mass, and diastolic BP. Furthermore, in three obese patients with elevated IOP, further investigations revealed pituitary adenoma in two patients and glaucoma in one patient. These patients were excluded from the analyses and underwent a thorough investigation for differential diagnosis and management of related disorders.

Optical nerve parameters measured using OCT may vary according to age, sex, ethnicity, and geographical regions. RNFL and RGC have been shown to gradually decline after the age of 50 years.[19] Studies evaluating the RNFL thickness in healthy children have shown no relationship between RNFL thickness and age, body weight, height, and sex.[20] Khawge et al. reported a negative correlation between BMI and RNFL in adult subjects with no female–male predominance.[21] In the other childhood studies, although has not reached a statistical significance in some, obesity has been shown negatively affects the RNFL and RGC, with discrepancies among the affected and not affected quadrants.[22],[23],[24],[25],[26] In the study of Carvera et al., a negative correlation has been shown between RNFL and BMI-SDS, fat mass index, leptin, and IL-6 levels, except for the temporal quadrant.[13] Although this was attributed to the critical role of inflammatory factors in the RGC damage, authors have not made any reasonable explanation of how the inflammatory cytokines affect the some quadrant but not affect the others.

In the present study, a statistically significant lower RNFL thickness was detected, and although not statistically significant, a decreased RGC was detected in obese children compared to the control group. In addition, the difference between the RGC of obese children and control subjects was very small and could not be suggested as evidence for clinical significance. However, when it is taken into consideration that even healthy individuals develop a decline in RGC after the age of 50 years, the present results may be suggestive of increased risk of developing premature RGC loss in later life. A negative correlation was also determined between RFNL thickness and BMI-SDS and WHR. To the best of our knowledge, in previous studies, the relationship of WHR and RFNL has not been investigated. However, this finding may suggest an increased risk of ophthalmological changes in central obesity, similar to the other metabolic complications of obesity such as diabetes, hypertension, NAFLD, and cardiovascular diseases. In addition, since the HOMA-IR, plasma lipids, and systolic and diastolic blood pressure values were not related to RFNL thickness, the effect of obesity could be considered an isolated complication of obesity beyond the metabolic changes.

Although not statistically significant, the C/D value in the current study obese group was lower than that of the control group, which was consistent with previously published adult data.[27],[28] Koca et al. reported a higher disk area, cup volume mean, and vertical C/D ratio in obese children compared to the healthy control subjects.[25] In that study, male subjects were reported to have a statistically significant larger rim, lower cup volume, and vertical C/D ratio.[25]

The choroid, a part of the posterior uveal tract, has an enriched vasculature and blood flow. It functions as an oxygen and nutrient supplier for the outer retina.[29] The thickness of the choroid may physiologically decrease with age. In addition, central serous chorioretinopathy, senile macular degeneration, diabetic retinopathy, and retinitis pigmentosa are associated with changes in the choroid.[29] Microvascular changes related to obesity have previously been reported.[30] Increased BMI has been shown to be associated with low retinal artery and high venous diameters.[31] Although sympathetic activity and noradrenalin reduce the choroid blood flow, parasympathetic activity influences it by increasing the NO signaling. In obesity, elevated vasoconstrictor mediators, endothelin 1 and angiotensin II, have been shown to decrease NO, thereby affecting the choroid blood flow. In severely obese adults, a negative relationship has been found between obesity, BMI, and choroid thickness.[27],[32] In the current study, CT was thinner in the obese group, but the difference was not statistically significant. This was attributed to the younger age of the participants and studies with longer follow-up periods are required to observe the effects of obesity on choroid thickness in the long term.

In conclusion, in the present study which evaluated the relationship of obesity and its effects on ophthalmological parameters, the elevated IOP and decreased RNFL thickness determined in obese children suggested an increased risk of developing glaucoma at a younger age, particularly in those with central obesity. In addition, the detection of pituitary adenoma in two patients and glaucoma in one patient during investigation for high IOP revealed a need for regular and comprehensive opthalmological examination of obese children for prompt diagnosis and proper management of ophthalmological complications.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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