About the Author(s)


Khathutshelo P. Mashige Email symbol
Discipline of Optometry, University of KwaZulu-Natal, South Africa

Olalekan A. Oduntan
Discipline of Optometry, University of KwaZulu-Natal, South Africa

Citation


Mashige KP, Oduntan OA. Macular thicknesses and their associations with ocular and demographic variables in black South Africans. Afr Vision Eye Health. 2017;76(1), a374. https://doi.org/10.4102/aveh.v76i1.374

Original Research

Macular thicknesses and their associations with ocular and demographic variables in black South Africans

Khathutshelo P. Mashige, Olalekan A. Oduntan

Received: 31 Aug. 2016; Accepted: 04 Nov. 2016; Published: 30 Jan. 2017

Copyright: © 2017. The Author(s) Licensee: AOSIS.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Purpose: To determine normal macular thicknesses and their associations with demographic and ocular variables in healthy eyes of black South Africans.

Methods: Six hundred healthy subjects (N = 600) underwent height and weight measurements followed by a complete ophthalmic examination, which included auto-refraction, subjective refraction, slit-lamp biomicroscopy, ocular biometric measurements and tonometry. Intra-ocular pressure (IOP) was measured with the Nidek NT530P (Tonopachy™) and the axial length (AL) thickness with the Nidek Echoscan. The central corneal thickness (CCT) and macular thickness were measured using iVue-100 spectral-domain optical coherence tomography (Optovue, Inc.). The macular thickness map protocol that divides the macular area into nine regions of the Early Treatment Diabetic Retinopathy Study (ETDRS) fields was used. Variations in macular thickness measurements with body mass index (BMI), age, gender, refraction, AL, CCT and IOP were determined with partial correlation analysis.

Results: The 600 subjects had a mean age of 28.15 ± 13.09 years (range = 10–66 years), with 305 (50.83%) being males and 295 (49.17%) females. The thickness values of the central, inner and outer maculae were normally distributed, with means of 235.89 µm ± 20.04 µm, 303.56 µm ± 18.68 µm and 287.81 µm ± 14.61 µm, respectively. Mean total macular thickness for all subjects was 268.72 ± 15.04 µm. The temporal quadrant was markedly thinner than all other quadrants for both inner and outer macular regions. Macular thicknesses were greater in men than in women (p < 0.05). The thickness of mean central, mean inner and mean outer maculae increased significantly with increasing BMI (p < 0.001). Central, inner and outer maculae were significantly associated (p < 0.001) with a high hyperopic spherical equivalent refraction. AL was associated with a thin inner macula (p < 0.05) and an outer macula (p < 0.001), but not with a thinner central macula (p > 0.05). Age, CCT and IOP were not associated with macular thickness values in any quadrant (p > 0.05).

Conclusion: The macular values were thinner in women than in men and were related to BMI, gender, hyperopic spherical refraction and AL with regional variations. These differences should be considered when interpreting optical coherence tomography results for accurately diagnosing and managing retinal abnormalities.

Introduction

Measurement of macular thickness is essential for diagnosing and monitoring pathological changes in various ocular diseases such as glaucoma, macular hole and macular oedema.1 In addition, knowledge of macular thickness in comparison with population or normal values and their associations with other parameters such as demographic and ocular variables is important for the treatment and follow-up of disease severity or progression.1

The introduction of optical coherence tomography (OCT) has allowed eye care professionals to quantitatively and qualitatively assess retinal parameters to detect small changes in these parameters and to evaluate the efficacy of different treatment modalities.2 Previous studies3,4 have shown that quantitative measurement of retinal parameters using OCT can distinguish between pathology and physiology, thus emphasising the importance of understanding normal variations in different populations, races and ethnicities using the OCT.

The iVue-100 (Optovue, Inc.) is a new-generation spectral-domain OCT (SD-OCT) instrument with high axial and lateral resolution compared with the previous generations of this technology such as time-domain OCT (TD-OCT).5 As different types of OCTs have become more widely available and used, normative data have become important in interpreting pathological features affecting retinal structures, such as with glaucoma. Several OCT-based studies conducted on macular thickness measurements and their variations with age, gender, race, refractive error and axial length (AL) in normal subjects have yielded conflicting results.6,7,8,9,10 Some of the major sources of inconsistencies in these studies lie in the variability of age groups, techniques used and limited focus on ethnicities, such as in Africans. In addition, the effects of body mass index (BMI), spherical equivalent (SE) refractive error, AL, central corneal thickness (CCT), intra-ocular pressure (IOP) and other ocular biometric variables have not been taken into consideration in many of these studies. The purpose of this study was to determine the distribution of macular thicknesses and to assess any associations with demographic (BMI, age and gender) and ocular variables (SE, AL, CCT and IOP) in normal black South African subjects using iVue SD-OCT. To the best of our knowledge, this is the first report on the distribution of macular thicknesses and their associations with other ocular variables in a large sample of black South Africans.

Methods

The study adhered to the tenets of the Helsinki Declaration, and ethical approval was obtained from the Biomedical Research and Ethics Committee of the University of KwaZulu-Natal. Informed consent to participate in the research study was obtained from all the participants. The study was conducted at the Eye Clinic of the Department of Optometry at the University of KwaZulu-Natal in Durban, South Africa. The Eye Clinic is situated inland of the central business district of Durban. Participants were selected through stratified random cluster sampling from geographically contiguous areas of Durban, South Africa, that consisted of urban, peri-urban and rural areas. Two fieldworkers were involved in the study. One fieldworker worked in advance of the other recruiting participants in the selected clusters and the other transporting participants to the examination site. The study took place after consulting with and approval from the local authorities (city councillors, key community figures and traditional leaders), school administrators and civil society. During the fieldwork, the head of the household was informed of the nature and details of the study, the date of the clinical examination as well as transportation arrangements.

All subjects underwent a complete ocular examination, including non-cycloplegic refraction, assessment of IOP, slit-lamp biomicroscopic evaluation, fundus examination and ocular biometry. To eliminate inter-examiner variability that negatively impacts on validity, subjective refraction, AL, CCT, IOP and macular thickness measurements were performed by one optometrist experienced in performing these techniques. Other tests such as case history, visual acuity, height and weight measurements, auto-refraction, slit-lamp and fundus examinations were also performed by one optometrist. Inclusion criteria included a best-compensated visual acuity of 6/6 or better, and normal ocular findings on slit-lamp, perimetry and ophthalmoscopic examinations. Subjects with previous histories of ocular surgery, trauma, contact lens wear and those on medications that could affect the measured variables were excluded.

Height was measured in metres with a tape measure, and weight was measured in kilograms with a digital Adam equipment scale, these being used to determine the BMI (BMI = weight/height2), the internationally accepted measure of obesity. Refractive errors were assessed with the Nidek AR-310A auto-refractor followed by subjective refraction, which was defined as the SE (sphere power + cylinder power/2). The Nidek NT530P (Tonopachy™) device was used to measure IOP. AL was measured with the Nidek US-500 Echoscan, and CCT was measured with the iVue-100 OCT (Optovue, Inc.). The same OCT was used to take retinal thickness scans of the macula. Retinal thickness is defined as ‘the distance between the vitreoretinal interface and the inner border of retinal pigment epithelium (RPE)’.11 All OCT devices generally identify the vitreoretinal interface as the inner retinal border,11 but the segmentation of the outer retinal border identified by different OCT devices varies significantly. The iVue-100 OCT considers the inner border of the RPE as the outer retinal border.11,12 Retinal thickness was, therefore, automatically determined by the instrument software as the distance between the internal limiting membrane and the inner border of the RPE, with measurements being obtained for three concentric regions (Figure 1). The central disc (fovea), called the central macula, is a region with a radius of 1 mm, while the inner and the outer rings have an outer radius of 3 mm and 6 mm, respectively, and were each divided into four quadrants. Average retinal thickness was provided for each of the nine regions.

FIGURE 1: Example of macular thickness measurements obtained using iVue-100 optical coherence tomography.

Three circular scans deemed to be of satisfactory quality were obtained for each eye, these being repeated in succession without any breaks. Three consecutive readings for macular thickness scans were taken and the averages computed. Satisfactory scan quality was defined as good centring on the disc and macula, and as per the manufacturer’s recommendations, repeat scans were taken if the signal strength was less than 40.12

Statistical analysis

All analyses were conducted with the Stata: data analysis and statistical software (version 11.0, Stata Corp., TX, USA). The Kolmogorov–Smirnov test was used to test for normal distributions with macular thickness data. Variables such as percentages, means and standard deviations were generated using descriptive statistics. Independent two-sample t-tests were used to test for differences in the relevant variables between the two genders. Analysis of variance (ANOVA) enabled a comparison of the mean thicknesses across the regions and quadrants with respect to the demographic and ocular variables. Pearson partial correlation analysis was used to examine the associations between macular thickness and demographic and ocular variables. A 95% confidence interval and a 5% level of significance were adopted, the results with a p ≤ 0.05 being considered significant.

Results

A total of 600 healthy subjects (305 males and 295 females) with a mean age of 28.15 ± 13.09 years (range = 10–66 years) and a mean BMI of 21.90 kg/m2 ± 2.85 kg/m2 were included. The ages of males ranged from 10 to 59 years with a mean of 27.52 ± 12.42 years, and those of females ranged from 10 to 66 years with a mean of 28.79 ± 13.77 years. The mean BMI for males was 20.24 kg/m2 ± 2.49 kg/m2, with a range of 17.74 kg/m2 – 26.82 kg/m2. The mean BMI for females was 23.05 kg/m2 ± 3.16 kg/m2, with a range of 20.31 kg/m2 – 29.66 kg/m2. Preliminary statistical analysis showed that there was no difference in macular thicknesses between right and left eyes for every participant (Pearson correlation coefficient, r = 0.89; p = 0.02). Due to this, and to avoid possible lack of independence13 and correlation effects, only the right eye data from each participant were used for further data analysis and presentation. The mean SE was -0.46 ± 1.54 D (range = -7 ± 3 D), and the mean AL was 23.05 mm ± 0.98 mm. The mean CCT and IOP measurements were 495.05 µm ± 32.40 µm and 14.22 mmHg ± 2.33 mmHg, respectively. Males had significantly greater ALs than their female counterparts (all p-values < 0.05). No significant differences were found between the genders for BMI, age, SE, CCT and IOP (independent samples t-tests: p = 0.19, 0.30, 0.26, 0.54 and 0.19, respectively). Independent two-sample t-tests also showed that the central, inner and outer macular thicknesses were significantly lower in women (all p-values < 0.05).

Macular thicknesses were normally distributed, according to the Kolmogorov–Smirnov tests. The mean thickness of the whole macular region was 268.72 µm ± 15.04 µm. The macula was thinnest at the centre or fovea (innermost 1-mm ring), with a mean value of 235.89 µm ± 20.04 µm. The mean for the inner macula was 303.56 µm ± 18.68 µm, whereas at the outer macula it was 287.81 µm ± 14.61 µm. There were variations across quadrants within the inner and outer macular regions. In the inner macular region, the superior quadrant was the thickest (308.47 µm ± 17.21 µm), followed by the nasal (306.28 µm ± 18.71 µm), inferior (302.12 µm ± 15.63 µm) and temporal (292.77 µm ± 21.55 µm) quadrants. In the outer macular region, the nasal quadrant was the thickest (296.58 µm ± 20.30 µm), followed by the superior (290.32 µm ± 18.44 µm), inferior (273.39 µm ± 15.04 µm) and temporal (270.77 µm ± 17.16 µm) quadrants. Macular thickness for both genders in each of the nine regions of the Early Treatment Diabetic Retinopathy Study (ETDRS) map is presented in Table 1, with the thicknesses by ETDRS region in the 600 healthy eyes being stratified by age in Table 2.

TABLE 1: Macular thickness measurements in each Early Treatment Diabetic Retinopathy Study region by gender in 600 healthy eyes using the iVue-100 spectral-domain optical coherence tomography system.
TABLE 2: Macular thickness measurements by Early Treatment Diabetic Retinopathy Study region in 600 healthy eyes stratified by age.

Males had greater macular thicknesses than females in all nine regions of the ETDRS map, except for the temporal and inferior quadrants of outer regions, which did not show any significant differences. Partial correlation analysis was used to assess the relationship between macular thickness and BMI, age, SE, AL, CCT and IOP. As the participants’ mean BMI increased, overall macula, central macula, average inner macula and average outer macular thickness increased significantly (partial correlation analysis adjusted by age, gender, SE, AL, CCT and IOP: r = 0.29, p < 0.001; r = 0.32, p < 0.001; r = 0.21, p < 0.001 and r = 0.24, p < 0.001, respectively; Table 3). No significant correlation was found between macular thickness and age (with adjustments for BMI, SE, AL, CCT and IOP), CCT (with adjustment for BMI, age, SE, AL and IOP) and IOP (with adjustments for BMI, age, SE, AL and CCT) for either gender. Macular thickness in all the quadrants showed a significant positive correlation with SE (with adjustments for BMI, age, gender, AL, CCT and IOP), being thinner in myopia and thicker in hyperopia. Apart from the central macula, and the superior, inferior and nasal quadrants of the inner macula, significant negative correlations were evident between macular measurements and AL in all other quadrants (Table 3).

TABLE 3: Correlations between macular measurements and body mass index, age, spherical equivalent, axial length, central corneal thickness and intra-ocular pressure.

Discussion

Accurate diagnosis and appropriate management of retinal abnormalities, such as glaucoma and macular degeneration, using the OCT depend on comparisons of the normative values.14,15 This study is, therefore, relevant in that it reports the baseline normative data of macular thickness and their associations with demographic and ocular variables from healthy African individuals. Macular thicknesses were normally distributed according to the Kolmogorov–Smirnov test, this being an expected finding, as most biological variables are normally distributed.1 There was a high degree of mirror image symmetry between the right and left eyes in the macular thickness measurements, a finding similar to a previous report.16

We found a mean macular thickness of 268.72 µm ± 15.04 µm and a mean central macular thickness of 235.89 µm ± 20.04 µm among all (N = 600) the study participants. The mean central macular thickness from our study is higher than the 181 µm ± 3.7 µm and 200.27 µm ± 2.7 µm reported by Kashani et al.10 in African-Americans and white people, respectively; higher than the 173.8 µm ± 18.16 µm reported by Gella et al.11 in Indians; and lower than the 252.0 µm ± 20.1 μm reported by Harb et al.17 in white people. Studies by Adhi et al.,16 Sull et al.18 and Giani et al.19 reported mean central macular thicknesses of 229.01 µm ± 20.64 µm, 231 µm ± 16 µm and 229 µm ± 24 µm, respectively, which are comparable with our results. Interestingly, all the above-mentioned studies that reported results similar to ours used a SD-OCT. This could suggest that quantitative analysis of retinal thickness may depend on the OCT device used.

Although direct comparisons are not easy to make due to differences in the age cohorts, methodologies, statistical estimation methods, segmentation algorithms of the OCT devices and scan protocols used, it does suggest that racial and ethnic variations in central macular thicknesses exist, as reported in previous studies.10,17 The exact causes for racial and ethnic differences in central macular thickness remain obscure, with several reasons having been postulated. For example, it has been suggested that higher amounts of melanin in darkly pigmented populations ‘weaken the OCT light signal’, resulting in reduced thickness measurements.20 This hypothesis contradicts with our findings because central macular thickness values were higher than the previously reported African and Indian population values, which have similar melanin levels. Another hypothesis is that the differences in the depth and diameter of the foveal pit may account for the central macular thickness differences observed in different races and ethnic groups.21 Studies would be necessary to further explore these hypotheses.

Macular thickness decreased from the centre towards the periphery of the retina, due to the anatomical arrangement of retinal layers, with the thickness of the central macula (fovea) being devoid of the retinal nerve fibre layer. This decrease in thickness was consistent with findings reported elsewhere.18,22 The temporal and nasal quadrants were thinnest and thickest, respectively, for the outer macular (perifoveal) region (Table 2), which is consistent with the arrangement of fibres in the papillo-macular region.23 We found that the BMI was positively correlated with macular thicknesses (Table 3). The association between obesity and diabetes mellitus (DM), particularly type 2 (non-insulin-dependent) DM, has been known for several hundred years.24 The BMI affects the measurement of macular thickness and should, therefore, be taken into consideration when comparing the macular thicknesses of diabetic and non-diabetic groups in future studies.25

Although it has been reported that macular thickness declines with age due to a decreasing density of photoreceptors, ganglion cells and retinal pigment epithelial cells,18 no statistically significant relationship could be found in this regard from this study (Tables 2 and 3). There are several potential reasons for the findings from this study. Firstly, our study had only six participants above 60 years of age. Secondly, this was a cross-sectional study, which is not appropriate to accurately present the decrease in macular retinal thickness with age. Therefore, the results of the effect of age on the macular thickness should be interpreted with caution in relation to the outlined limitations. Our findings are, however, consistent with previous studies16,26 that have shown no association between macular thickness and age. However, Sull et al.18 reported a decrease in macular thickness with age. Our results showed gender-related differences in central macular thickness and all other eight ETDRS segments, with males showing significantly larger means (Table 1). These results are in agreement with reports from other studies.2,10,16 Thus, gender-related variations should be considered when comparisons with macular thickness measurements are made, and when diagnosing and following-up macular diseases.16 It is, however, noted that Grover et al.26 reported no difference in macular thicknesses between male and female participants. Gender differences in this parameter may help to explain and understand the high prevalence of certain macular diseases in females. For example, the higher risk of macular holes (which begins with foveal thinning) in females may be due to their thinner macular thicknesses.2,27

This study found that macular thickness was significantly related to refractive error, with all macular regions being thicker with increasing hyperopia (Table 3). Previous investigations mainly explored the effect of myopia on macular thickness, with variable results.28,29,30,31,32 Although these studies used various methods to measure macular thickness, they generally found that macular thinning was associated with increasing myopia, and that it mainly occurred in the inner and outer maculae rather than at the central macula.28,32 It has been reported in several studies that the central macular thickness becomes thicker with increasing myopia28,32 or that it did not change.33 Wakinati et al.33 also suggested that the thinning of the peripheral macula could be a compensatory mechanism to preserve the more essential central macular thickness, which is critical to vision. Chui et al.34 proposed that retinal stretching unfortunately reduces peripheral visual acuity by decreasing the neural sampling density. The effect of central macular thickening on visual function in hyperopes is not yet known. A possible explanation was, however, provided by Hee et al.,35 who suggested that it would reduce vision, as acuity has been found to worsen with increasing central macular thickness in otherwise normal adult eyes.

Previous studies on the associations between macular thickness and AL have yielded conflicting results.2,17,36,37 We found a significant negative correlation between AL and overall macula (r = -0.23, p < 0.001), mean inner macula (r = -0.17, p < 0.001) and mean outer macula (r = -0.29, p < 0.001) thicknesses, but not with central macular thickness (r = 0.05, p = 0.22). Recent studies by Hwang and Kim32 and Zhao et al.28 have also shown that thinner inner and outer macular thicknesses are associated with longer ALs. However, these studies also showed that central macular thickness increased with AL. In contrast, Wakinati et al.33 reported no difference in the thickness of the central, inner and outer macular regions between the three groups of axially myopic subjects and an emmetropic group. The discrepancies in these results are probably due to the differences in the algorithms used by OCT devices, subject age and definition of the size of various macular regions.

We did not find any significant association between macular thickness and IOP (Table 3). Our study included only healthy non-glaucomatous subjects, which may have accounted for the lack of relationship between IOP and macular thicknesses. Zhang et al.38 suggested that macular thickness was affected only in the later stages of glaucoma, being less sensitive at the earlier stages and in healthy eyes. Similarly, macular thickness did not show any significant relationship with CCT. The limitations of the current study include normative data heavily weighted with younger patients, a limited number of eyes with high refractive errors and the small study sample of adults 60 years and above.

Conclusion

This study has presented normative data for macular thickness using the iVue-100 SD-OCT device in a black South African population with healthy eyes. These findings are comparable with some studies but vary from other reports using a similar OCT system. Macular thickness measurements varied with BMI, gender, hyperopic spherical equivalence, AL and retinal location. The data obtained here may enhance our ability to diagnose ocular disorders affecting the retina and optic nerve.

Acknowledgements

This work is part of the PhD vision science project of the first author supported by the South African Medical Research Council (SAMRC). The authors thank Ms Carrin Martin for reviewing this article and giving valuable comments.

Competing interests

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

Authors’ contributions

K.P.M. and O.A.O. made equal contributions in writing this article.

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Vision  vol: 5  issue: 4  first page: 48  year: 2021  
doi: 10.3390/vision5040048