IOVS Papers in Press. Published on March 16, 2012 as Manuscript iovs.11-8518
Measurement of macular pigment optical density in a healthy Chinese population sample
Jie Yu,1 Elizabeth J. Johnson,2 Fu Shang,2 Apiradee Lim,3 Haiying Zhou,1 Lei Cui,1 Jun Xu,1 Torkel
Snellingen,4 Xipu Liu, 4 Ningli Wang,1 Ningpu Liu 1
From the 1Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing
Ophthalmology and Visual Sciences Key Laboratory, Beijing, China; the 2Jean Mayer US Department
of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, Massachusetts;
the 3Department of Mathematics and Computer Science, Faculty of Science and Technology, Prince of
Songkla University, Pattani Campus, Muang Pattani, Thailand; and the 4Sekwa Eye Hospital, Beijing,
China.
Address for correspondence: Ningpu Liu, M.D., Ph.D., Beijing Tongren Eye Center, Beijing Tongren
Hospital, Capital Medical University, No. 1 Dong Jiao Min Xiang, Dongcheng District, Beijing
100730, China; Email: [email protected]
Supported in part by the National Basic Research Program of China (973 Program) Grant
2007CB512201, the Beijing Municipal Health Bureau Grant 2009208, the National Natural Science
Foundation of China Grant 81070734, and an unrestricted research fund from Kemin Japan. Kemin
Health USA kindly provided the heterochromatic flicker photometer for the study.
Word count: 2463
1
Copyright 2012 by The Association for Research in Vision and Ophthalmology, Inc.
ABSTRACT
Purpose: Macular pigment may protect against age-related macular degeneration (AMD) by its
capacity to absorb blue light and scavenge free radicals. Current information on human macular
pigment density has been largely from studies on Caucasian populations. The purpose of this study
was to assess macular pigment density and its determinant factors in a Chinese population sample.
Methods: Macular pigment optical density (MPOD) was measured in a healthy Chinese population
using heterochromatic flicker photometry (HFP). Participants received a standard ophthalmic
examination and only subjects who were confirmed not to have any eye diseases except mild
age-related cataract were included in the study. Demographic and lifestyle data and general health
status were recorded by questionnaire.
Results: A total of 281 unrelated healthy Chinese individuals including 96 males and 185 females,
with age ranging from 17 to 85 years, participated in the study. The mean and standard deviation of
MPOD levels were 0.56 ± 0.19, 0.49 ± 0.18, 0.36 ± 0.15, and 0.19 ± 0.12, respectively, at 0.25°, 0.5°,
1.0°, and 1.75°eccentricity points. A significant age-related decline in MPOD was observed at 0.25°
(p=0.014). Females tended to have relatively lower levels of MPOD than males at 0.25º (p=0.21), 0.5º
(p=0.025), and 1.0º (p=0.16). No statistically significant association of MPOD was observed with
body mass index or smoking status.
Conclusions: Macular pigment density measured by HFP tends to decline with aging in this healthy
Chinese population sample. Females may have lower levels of MPOD than males.
2
INTRODUCTION
The macula is the center of the posterior retina and can be discerned clinically as the area of
yellowish pigmentation. Macular pigment, composed of three carotenoids, lutein, zeaxanthin, and
meso-zeaxanthin,1 is believed to improve visual performance by reducing chromatic aberration and
glare sensitivity.2-4 Through its ability to absorb high-energy short-wave blue light and its
anti-oxidative property, macular pigment is also hypothesized to protect the macula from light-induced
and oxidative damage, which may lead to age-related loss of function and macular diseases.5, 6
Although obtaining direct evidence for this hypothesis is difficult, a variety of indirect evidence
supports this hypothesis. For example, epidemiological studies suggest that high intake of lutein and
zeaxanthin and high blood levels of these carotenoids are related to reduced risk of age-related macular
degeneration (AMD).7-9 Lutein and zeaxanthin are entirely of dietary origin and cannot be synthesized
by the human body. Foods such as green leafy vegetables, corn, squash, broccoli, peas, and egg yolks
are rich source of lutein and zeaxanthin.10 In healthy subjects, it has been shown that blood or retinal
levels of carotenoids can be modified by dietary intake or supplementation.11-13 However, whether
increasing blood or retinal levels of carotenoids can offer additional protection from degenerative
changes of the retina remains to be proven.
It is well known that the prevalence of AMD varies among different populations. Prevalence of
early and late AMD in a Chinese population, for example, was reported to be lower than that in
Caucasians.14, 15 In addition to the differences in genetic susceptibility,16-18 traditional Chinese foods
with higher concentrations of carotenoids 19 may translate to higher macular pigment and contribute to
the relatively lower prevalence of AMD in the Chinese population. Current information regarding
human macular pigment optical density (MPOD), however, is mainly from studies on Caucasian
3
populations. To the best of our knowledge, only two studies reported MPOD in small samples of Hong
Kong Chinese.20, 21 The present study aimed to measure MPOD in a relatively larger sample of a
healthy Chinese population in urban Beijing and to evaluate its determinant factors.
SUBJECTS AND METHODS
Study Participants and Clinical Evaluation
The study was performed under approval of the Ethics Committee of Beijing Tongren Hospital.
Informed consent was obtained from participants after explanation of the purpose and procedure and
possible consequences of the study. The research procedures followed the tenets of the Declaration of
Helsinki. Healthy Chinese volunteers were recruited to the study by poster and oral advertisement in
the local community of downtown Beijing. All study participants underwent a standard ophthalmic
examination, including visual acuity, intraocular pressure, slit-lamp biomicroscopy, and fundus
examinations through dilated pupil. Color fundus photographs centered on the fovea of both eyes were
taken for each subject. Body mass index (BMI, kg/m2) was calculated according to the height and
weight of the participant. Personal and medical information was obtained using a questionnaire. Only
those subjects with self-reported healthy status and normal fundus in both eyes were included in the
study. Exclusion criteria included history of diabetes or any life-threatening disease such as
myocardial infarction or cancer, or subjects with ocular disease including corneal scar, dense cataract,
glaucoma, uveitis, vitreous hemorrhage, chorioretinal and optic nerve diseases, or any maculopathy.
Measurement of Macular Pigment Optical Density (MPOD)
MPOD was measured psychophysically in both eyes using heterochromatic flicker photometry
(HFP) in a dark room.22 The examiner familiarized the subject with the apparatus and showed an
4
instructional video that was designed to provide a uniform introduction to the task
(www.macularmetrics.com). Four foveal test configurations at 0.25º, 0.5º, 1.0º, and 1.75º eccentricity
points were measured. The former two are solid disks and the latter two are annuli. The parafoveal
reference test target is a solid disk set at 7º eccentricity. Flicker frequency of the two test wavelengths
(460nm and 530nm) usually began with 14 Hz for the foveal and 12 Hz for the parafoveal
measurement. The frequency would be decreased if the subject could not recognize sensation of
flickering or increased if the subject could not find a no-flicker zone.
The subjects were asked to fix on the exact center of the test target and perceive the flickering.
For the parafoveal test, the fixation target is a small red LED located to the left of the background field.
The task for the participant was to identify whether the target is flickering or not. The examiner
adjusted the knob from the flicker zone to no-flicker zone, clockwise first and then counterclockwise
to obtain two values indicating the border of the flicker and no-flicker zone (minimum and maximum
intensity of blue light). The exact mathematical average of the two values, which stands for the middle
of the no-flicker zone, was calculated. Measurement at each eccentricity point was repeated 5 times
and the average was used to calculate MPOD.
Throughout testing, the subject was reminded to gaze at the fixation point. They were also
advised to blink frequently or close the testing eye for a short while in order to minimize the influence
of fatigue. Both eyes were measured in a randomized order to avoid the potential order effect.
Statistical Analysis
Data analyses were performed using the open source R statistical software package.23 Mean
and standard deviation of MPOD at each eccentricity were calculated. Paired t-test was performed to
compare MPOD levels between right and left eyes at each eccentricity. MPOD levels between two
5
groups were compared using t-test for two independent samples or Ranksum test for non-normal
distributed data. Multiple comparisons were made using ANOVA followed by Tukey’s test for normal
distributed data or Kruskal-Wallis test for non-normal distributed data. Correlations between
continuous variables were evaluated using Pearson's correlation coefficient (r). Relationships between
MPOD and age, BMI, gender, and smoking status were analyzed by multiple linear regressions.
Statistical significant level was set as p values less than 0.05.
RESULTS
A total of 281 healthy subjects aged from 17 to 85 years participated in the study. Ninety-six were
male and 185 female. Characteristics of the study subjects are given in Table 1. None of the study
subjects reported the use of lutein/zeaxanthin supplementation. A comparison of MPOD levels
between right and left eyes at 0.25º, 0.5º, 1.0º and 1.75º eccentricities is shown in Figure 1. Substantial
inter-ocular agreement was obtained at 0.25º, 0.5º, 1.0º and 1.75º eccentricities (r=0.81, 0.82, 0.74, and
0.69, respectively). The average MPOD level of right and left eyes of each study subject was thus
calculated and used for subsequent analysis.
Table 2 shows the MPOD measurement among study subjects. The measurement was defined as
successful if the subject could complete the task at test point of 0.25º, 0.5º, 1.0º, or 1.75º, respectively.
The rate of successful measurement for MPOD was 79% (222/281) at 0.25º, 96.8% (272/281) at 0.5º,
100% (281/281) at 1.0º, and 83.6% (235/281) at 1.75º eccentricities. Mean MPOD level and standard
deviation from study subjects of successful measurement was 0.56 ± 0.19 at 0.25º, 0.49 ± 0.18 at 0.5º,
0.36 ± 0.15 at 1.0º, and 0.19± 0.12 at 1.75º.
As shown in Figure 2, a significant age-related decline in MPOD levels was observed at 0.25°
6
eccentricity point (r= -0.165, p=0.014). However, there was no significant association between MPOD
and aging at 0.5° (r= -0.025, p=0.68), 1.0° (r= -0.053, p=0.38), or 1.75º (r=0.094, p=0.15)
eccentricities.
A comparison of MPOD levels between males and females is shown in Figure 3. Females tended
to have relatively lower MPOD level than males at 0.25º, 0.5º, and 1.0º eccentricities. This gender
difference was statistically significant at 0.5 º (p=0.025) but was not observed at 0.25 º (p=0.21) and
1.0 º (p=0.16). No correlation was observed between smoking status and MPOD (p=0.68 at 0.25º, 0.21
at 0.5º, 0.68 at 1.0º, and 0.67 at 1.75º) or between BMI and MPOD (p=0.84 at 0.25º, 0.71 at 0.5º, 0.79
at 1.0º, and 0.19 at 1.75º) among study subjects.
The results from a multiple linear regression model are given in Table 3. Age was found to be the
only factor showing statistically significant inverse correlation with MPOD, but only at 0.25º
eccentricity point (multiple R-squared = 0.063, p = 0.003). The effect of gender on MPOD became
insignificant in the model of multivariate analyses.
DISCUSSION
This study determined the effects of age, gender, BMI and smoking status on MPOD in a
relatively large sample of Chinese population. We found that the MPOD levels decrease with aging in
the center of the retina (at 0.25° eccentricity point). Since MPOD plays an important role in blocking
harmful blue light and in quenching reactive oxygen species, this age-related decline in MPOD may
partially explain the age-related increase in risk for macular degeneration. It should be noted, however,
that only 6.3% of the decline in MPOD in the central fovea could be attributed to aging in the multiple
linear regression model (multiple R-squared = 0.063). Thus, the hypothesized relationship between
7
MPOD and the risk of AMD may be relatively weak.
The age-related decline in MPOD was also reported in several previous studies,20, 24-30 however,
there were studies that did not detect this age-related difference in MPOD.31-35 The discrepancy in the
age-MPOD relationship between different studies may be related to differences in sample size, subject
selection or methods of measurement. In a comparative study which used different methods to
investigate the possible effect of age on MPOD levels, a small but statistically significant age-related
decline of MPOD was detected by the method of HFP, but this age-related difference in MPOD was
not observed when the fundus reflectance spectroscopy or scanning laser ophthalmoscope was used.33
Among all the available methods for non invasive measurement of MPOD, including HFP,
auto-fluorescence,36 Raman spectroscopy,37 fundus reflectance spectroscopy,38 and motion
photometry,39 the HFP method has been the most commonly used in research studies.20, 21, 26, 40-44 The
advantages of the HFP method include the relatively inexpensive instrument,22, 45, 46 easy training of
research staff to operate the machine,22, 46 and no requirement for pupil dilation.22, 45, 46 In addition,
HFP remains the only validated technique and uniquely unaffected by changes in the ocular media with
aging,22, 45, 46 thus robust to patients with mild age-related cataract. It should be noted, however, that
this method of HFP, as well as other techniques except Raman spectroscopy, uses peripheral points of
the retina as reference. If there were an age-related diffusion of the macular pigment from macula to
the periphery,32 the use of HFP technique may result in an age-related decrease of MPOD due to the
increase of MPOD at the parafoveal reference point.33 Future studies using complementary methods of
MPOD measurement are warranted to verify the age-related decline in MPOD in this Chinese
population.
It has been reported that body fat 25, 47 and smoking status 26, 30 affect the level of macular pigment.
8
However, the present study did not detect an association between MPOD and BMI or smoking status.
The association between MPOD levels and gender has been reported in several previous studies, with
females having relatively lower levels of MPOD than males.20, 26, 48 A similar trend of gender-related
difference in MPOD was observed in this study. However, the impact of gender on MPOD became
insignificant in the model of multivariate analyses. Given the fact that several studies that did not find
this gender-associated difference in MPOD,41, 43 our data indicate that the gender-related difference in
MPOD is marginal. The level of MPOD and its distribution in retina may be affected by factors such as
genetic background, demographics or lifestyle characteristics.49 It has been reported, for example, that
females tend to have broader distribution of macular pigment than males.50 Females therefore are more
likely to have higher residual pigment density at the parafoveal reference point, which could lead to a
relatively lower MPOD measurement. Moreover, it is thought that females tend to have higher
percentage of body fat and adipose tissue than males, which may compete with the retina for uptake of
lutein and zeaxanthin.25 If the relatively higher body fat in females contributes to the association
between gender and MPOD in the previous publications, the lack of association between BMI and
MPOD may partially explain the weak gender-MPOD association in this study. It is plausible that the
higher dietary intake of lutein and zeaxanthin in Chinese population 19 may saturate the adipose tissue
with these carotenoids and attenuate the competition with the retina for lutein and zeaxanthin, thus
negating the effects of BMI and body fat on MPOD.
The level of macular pigments varies among different populations. MPOD in blacks, for
example, has been reported to be 41% lower than that in whites,43 although another study did not find
such difference.51 It should be noted, however, that comparison of MPOD levels among studies are
difficult or even impossible since different studies may employ different methodologies or study
9
protocols. MPOD measured by HFP at the same eccentricity point with a 4º reference point, for
example, would be expected to be lower than that with a 7º reference point due to relatively higher
residual pigment at 4º reference point, which could lead to underestimation of MPOD levels.21, 26
MPOD levels measured by HFP at 0.5º eccentricity point are reported to be 0.18-0.22 log unit in the
U.S. population with a 4º parafoveal reference point 26, 40, 41, 47 and 0.29-0.30 log unit in Europeans with
5.5º or 6º parafoveal reference point.24, 30 Using the same psychophysical method of HFP and 7º
parafoveal reference point, the MPOD levels measured in the present study were in good agreement
with the data obtained from a study in Hong Kong Chinese.20 However, the MPOD levels reported in
the present study were higher as compared to studies in other populations that used the similar
parameters (Table 4).24, 26, 30, 40, 41, 43, 46, 47 The relatively higher measurement of MPOD levels reported
in Chinese in the present study and in Hong Kong Chinese 20 is in agreement with the reports that the
Chinese population consumes more lutein and zeaxanthin 19 and may have relatively higher serum
concentration of carotenoids.52 The lack of dietary information, however, is a limitation of this current
study.
In summary, we reported measurement of MPOD levels using a method of HFP in a relatively
large sample of healthy Chinese population and observed a significant age-related decline in MPOD
levels at the fovea. Approximately 6.3% of the decline in MPOD in the central fovea could be
attributed to the age. No significant association of MPOD levels was found with BMI and smoking
status. This age-related decline in MPOD may contribute to the increased risk of AMD with aging. The
Chinese population has relatively higher dietary intake of lutein and zeaxanthin 19 and higher MPOD,
which may partially explain the relatively lower prevalence of AMD in Chinese.14, 15 Future studies to
verify the age-related decline in MPOD and to elucidate the underlying mechanisms are warranted.
10
REFERENCES
1. Bone RA, Landrum JT, Tarsis SL. Preliminary identification of the human macular pigment.
Vision Res 1985;25:1531-1535.
2. Stringham JM, Hammond BR, Jr. The glare hypothesis of macular pigment function. Optom Vis
Sci 2007;84:859-864.
3. Stringham JM, Hammond BR. Macular pigment and visual performance under glare conditions.
Optom Vis Sci 2008;85:82-88.
4. Wooten BR, Hammond BR. Macular pigment: influences on visual acuity and visibility. Prog
Retin Eye Res 2002;21:225-240.
5. Jr Ham WT, Mueller HA, Sliney DH. Retinal sensitivity to damage from short wavelength light.
Nature 1976;260:153-155.
6. Beatty S, Koh H, Phil M, . The role of oxidative stress in the pathogenesis of age-related macular
degeneration. Survey of ophthalmology 2000;45:115-134.
7. Seddon JM, Ajani UA, Sperduto RD. Dietary carotenoids, vitamins A, C, and E, and advanced
age-related macular degeneration. Eye Disease Case-Control Study Group. JAMA
1994;272:1413-1420.
8. Loane E, Kelliher C, Beatty S, Nolan JM. The rationale and evidence base for a protective role of
macular pigment in age-related maculopathy. The British journal of ophthalmology
2008;92:1163-1168.
9. Group EDC-CS. Antioxidant status and neovascular age-related macular degeneration. Eye
Disease Case-Control Study Group. Arch Ophthalmol 1993;111:104-109.
10. Khachik F, Beecher GR, Goli MB, Lusby WR. Separation and quantitation of carotenoids in foods.
Methods Enzymol 1992;213:347-359.
11. Berendschot TT, Goldbohm RA, Klopping WA, van de Kraats J, van Norel J, van Norren D.
Influence of lutein supplementation on macular pigment, assessed with two objective techniques.
Invest Ophthalmol Vis Sci 2000;41:3322-3326.
12. Bone RA, Landrum JT, Cao Y, Howard AN, Alvarez-Calderon F. Macular pigment response to a
supplement containing meso-zeaxanthin, lutein and zeaxanthin. Nutr Metab (Lond) 2007;4:12.
13. Bone RA, Landrum JT, Guerra LH, Ruiz CA. Lutein and zeaxanthin dietary supplements raise
macular pigment density and serum concentrations of these carotenoids in humans. J Nutr
2003;133:992-998.
14. Li Y, Xu L, Jonas JB, Yang H, Ma Y, Li J. Prevalence of age-related maculopathy in the adult
population in China: the Beijing eye study. Am J Ophthalmol 2006;142:788-793.
15. Yang K, Liang YB, Gao LQ, et al. Prevalence of age-related macular degeneration in a rural
Chinese population: the Handan Eye Study. Ophthalmology 2011;118:1395-1401.
16. Cruickshanks KJ, Hamman RF, Klein R, Nondahl DM, Shetterly SM. The prevalence of
age-related maculopathy by geographic region and ethnicity. The Colorado-Wisconsin Study of
Age-Related Maculopathy. Arch Ophthalmol 1997;115:242-250.
17. Klein R, Klein BE, Cruickshanks KJ. The prevalence of age-related maculopathy by geographic
region and ethnicity. Prog Retin Eye Res 1999;18:371-389.
18. Frank RN, Puklin JE, Stock C. Race, iris color, and age-related macular degeneration. Trans Am
Ophthalmol So 2000;98:109-115, 115-117.
19. Wang G, Brun TA, Geissler CA, et al. Vitamin A and carotenoid status in rural China. The British
11
journal of nutrition 1996;76:809-820.
20. Lam RF, Rao SK, Fan DS, Lau FT, Lam DS. Macular pigment optical density in a Chinese sample.
Curr Eye Res 2005;30:799-805.
21. Tang CY, Yip HS, Poon MY, Yau WL, Yap MK. Macular pigment optical density in young
Chinese adults. Ophthalmic Physiol Opt 2004;24:586-593.
22. Wooten BR, Hammond BR, Jr., Land RI, Snodderly DM. A practical method for measuring
macular pigment optical density. Invest Ophthalmol Vis Sci 1999;40:2481-2489.
23. R Development Core Team. R: A language and environment for statistical computing. R
Foundation for Statistical Computing, Vienna, Austria. R-2.9.0 and epicalc package for windows.
Available at http://www.R-project.org.
24. Beatty S, Murray IJ, Henson DB, Carden D, Koh H, Boulton ME. Macular pigment and risk for
age-related macular degeneration in subjects from a Northern European population. Invest Ophthalmol
Vis Sci 2001;42:439-446.
25. Nolan J, O'Donovan O, Kavanagh H, et al. Macular pigment and percentage of body fat. Invest
Ophthalmol Vis Sci 2004;45:3940-3950.
26. Hammond BR, Jr., Caruso-Avery M. Macular pigment optical density in a Southwestern sample.
Invest Ophthalmol Vis Sci 2000;41:1492-1497.
27. Bernstein PS, Zhao DY, Wintch SW, Ermakov IV, McClane RW, Gellermann W. Resonance
Raman measurement of macular carotenoids in normal subjects and in age-related macular
degeneration patients. Ophthalmology 2002;109:1780-1787.
28. Gellermann W, Ermakov IV, Ermakova MR, McClane RW, Zhao DY, Bernstein PS. In vivo
resonant Raman measurement of macular carotenoid pigments in the young and the aging human
retina. Journal of the Optical Society of America 2002;19:1172-1186.
29. Obana A, Hiramitsu T, Gohto Y. Macular carotenoid levels of normal subjects and age-related
maculopathy patients in a Japanese population. Ophthalmology 2008;115:147-157.
30. Nolan JM, Stack J, O OD, Loane E, Beatty S. Risk factors for age-related maculopathy are
associated with a relative lack of macular pigment. Exp Eye Res 2007;84:61-74.
31. Bone RA, Landrum JT, Fernandez L, Tarsis SL. Analysis of the macular pigment by HPLC: retinal
distribution and age study. Invest Ophthalmol Vis Sci 1988;29:843-849.
32. Chen SF, Chang Y, Wu JC. The spatial distribution of macular pigment in humans. Curr Eye Res
2001;23:422-434.
33. Berendschot TT, van Norren D. On the age dependency of the macular pigment optical density.
Exp Eye Res 2005;81:602-609.
34. Ciulla TA, Hammond BR, Jr. Macular pigment density and aging, assessed in the normal elderly
and those with cataracts and age-related macular degeneration. Am J Ophthalmol 2004;138:582-587.
35. Mellerio J, Ahmadi-Lari S, van Kuijk F, Pauleikhoff D, Bird A, Marshall J. A portable instrument
for measuring macular pigment with central fixation. Curr Eye Res 2002;25:37-47.
36. Delori FC. Autofluorescence method to measure macular pigment optical densities fluorometry
and autofluorescence imaging. Arch Biochem Biophys 2004;430:156-162.
37. Bernstein PS, Zhao DY, Sharifzadeh M. Resonance Raman measurement of macular carotenoids
in the living human eye. Arch Biochem Biophys 2004;430:163-169.
38. Berendschot TT, van Norren D. Objective determination of the macular pigment optical density
using fundus reflectance spectroscopy. Arch Biochem Biophys 2004;430:149-155.
39. Moreland JD. Macular pigment assessment by motion photometry. Arch Biochem Biophys
12
2004;430:143-148.
40. Ciulla TA, Hammond BR, Jr., Yung CW, Pratt LM. Macular pigment optical density before and
after cataract extraction. Invest Ophthalmol Vis Sci 2001;42:1338-1341.
41. Ciulla TA, Curran-Celantano J, Cooper DA, et al. Macular pigment optical density in a
midwestern sample. Ophthalmology 2001;108:730-737.
42. Nolan JM, Stack J, O'Connell E, Beatty S. The relationships between macular pigment optical
density and its constituent carotenoids in diet and serum. Invest Ophthalmol Vis Sci 2007;48:571-582.
43. Iannaccone A, Mura M, Gallaher KT, et al. Macular pigment optical density in the elderly:
findings in a large biracial Midsouth population sample. Invest Ophthalmol Vis Sci
2007;48:1458-1465.
44. LaRowe TL, Mares JA, Snodderly DM, Klein ML, Wooten BR, Chappell R. Macular pigment
density and age-related maculopathy in the Carotenoids in Age-Related Eye Disease Study. An
ancillary study of the women's health initiative. Ophthalmology 2008;115:876-883 e871.
45. Bone RA, Landrum JT. Heterochromatic flicker photometry. Arch Biochem Biophys
2004;430:137-142.
46. Snodderly DM, Mares JA, Wooten BR, Oxton L, Gruber M, Ficek T. Macular pigment
measurement by heterochromatic flicker photometry in older subjects: the carotenoids and age-related
eye disease study. Invest Ophthalmol Vis Sci 2004;45:531-538.
47. Hammond BR, Jr., Ciulla TA, Snodderly DM. Macular pigment density is reduced in obese
subjects. Invest Ophthalmol Vis Sci 2002;43:47-50.
48. Hammond BR, Jr., Curran-Celentano J, Judd S, et al. Sex differences in macular pigment optical
density: relation to plasma carotenoid concentrations and dietary patterns. Vision Res
1996;36:2001-2012.
49. Curran Celentano J, Burke JD, Hammond BR, Jr. In vivo assessment of retinal carotenoids:
macular pigment detection techniques and their impact on monitoring pigment status. J Nutr
2002;132:535S-539S.
50. Delori FC, Goger DG, Keilhauer C, Salvetti P, Staurenghi G. Bimodal spatial distribution of
macular pigment: evidence of a gender relationship. Journal of the Optical Society of America
2006;23:521-538.
51. Bone RA, Sparrock JM. Comparison of macular pigment densities in human eyes. Vision Res
1971;11:1057-1064.
52. Zhou H, Zhao X, Johnson EJ, et al. Serum carotenoids and risk of age-related macular
degeneration in a chinese population sample. Invest Ophthalmol Vis Sci 2011;52:4338-4344.
13
FIGURE LEGENDS
Figure 1. Comparison of macular pigment optical density levels in subjects with successful
measurements (mean ± 95% confidence interval) between right and left eyes at 0.25º (n=222), 0.5º
(n=272), 1.0º (n=281), and 1.75º (n=235) eccentricity points
Figure 2. The relationship between macular pigment optical density at 0.25° eccentricity point and
aging (r= - 0.165, p=0.014) in 222 subjects with successful measurement
Figure 3. Comparison of macular pigment optical density levels (mean ± 95% confidence interval)
between males (96 subjects) and females (185 subjects) at 0.25º, 0.5º, 1.0º, and 1.75º eccentricity
points
14
Table 1. Characteristics of the study subjects (n=281)
Subjects
Age, years
≤30
31-40
41-50
51-60
>60
Gender
Male
Female
BMI, kg/m2
≤23
23~27
≥27
Smoking status
Non-smokers
Smokers
Number
%
54
48
46
64
69
19.2
17.1
16.4
22.8
24.6
96
185
34.2
65.8
121
123
37
43.1
43.8
13.2
226
55
80.4
19.6
15
Table 2. Macular pigment optical density measured by heterochromatic flicker photometry among
study subjects
Subjects
Age, years
≤30
31-40
41-50
51-60
>60
Total
Gender
Male
Female
BMI, kg/m2
≤23
23~27
≥27
Smoking status
Non-smokers
Smokers
0.25º
Degree of Eccentricity
0.5º
1.0º
1.75º
0.61 ± 0.20 (43)
0.63 ± 0.17 (45)
0.51 ± 0.18 (41)
0.52 ± 0.16 (53)
0.55 ± 0.20 (40)
0.56 ± 0.19 (222)
0.51 ± 0.19 (54)
0.53 ± 0.17 (48)
0.44 ± 0.16 (45)
0.47 ± 0.15 (61)
0.50 ± 0.20 (64)
0.49 ± 0.18 (272)
0.38 ± 0.14 (54)
0.39 ± 0.14 (48)
0.30 ± 0.13 (46)
0.33 ± 0.13 (64)
0.37 ± 0.18 (69)
0.36 ± 0.15 (281)
0.19 ± 0.10 (44)
0.20 ± 0.12 (45)
0.15 ± 0.09 (43)
0.19 ± 0.10 (56)
0.23 ± 0.15 (47)
0.19 ± 0.12 (235)
0.59 ± 0.20 (75)
0.55 ± 0.18 (147)
0.52 ± 0.20 (92)
0.47 ± 0.17 (180)
0.37 ± 0.17 (96)
0.35 ± 0.14 (185)
0.19 ± 0.13 (80)
0.19 ± 0.11 (155)
0.57 ± 0.19 (96)
0.56 ± 0.19 (99)
0.56 ± 0.19 (27)
0.49 ± 0.17 (119)
0.49 ± 0.19 (116)
0.47 ± 0.18 (37)
0.36 ± 0.13 (121)
0.35 ± 0.16 (123)
0.35 ± 0.16 (37)
0.18 ± 0.10 (102)
0.20 ± 0.13 (106)
0.22 ± 0.13 (27)
0.56 ± 0.19 (181)
0.57 ± 0.18 (41)
0.48 ± 0.18 (219)
0.51 ± 0.19 (53)
0.35 ± 0.15 (226)
0.36 ± 0.17 (55)
0.19 ± 0.12 (191)
0.20 ± 0.13 (44)
Data are expressed as mean ± standard deviation. The number of subjects with successful
measurement is given in parentheses.
16
Table 3. Multivariate analyses for the association of macular pigment optical density measured at 0.25
degree with variable factors
Variables
Coefficient
Standard Error
Age, years
-0.003
0.001
BMI, kg/m2
0.003
0.005
0.52
Gender (reference=male)
-0.024
0.034
0.48
Smoking status (reference=non-smoker)
0.017
0.042
0.68
Light exposure
0.008
0.009
0.40
*** Multiple R-squared: 0.063
17
P value
0.003 ***
Table 4. Comparison of macular pigment optical density (MPOD) measured by heterochromatic
flicker photometry in various published studies
Author
Study
Study
Sample
(year)
Population
Subjects
Size
Age Range
Foveal
Parafoveal
MPOD
yrs.
Eccentricity
Reference
Mean ± SD
(Mean ± SD)
Iannaccone et
US
Healthy
222
al (2007) 43
Snodderly et
al (2004)
US
CAREDS
54
0.37 ± 0.19
a
b
0.5º
7º
0.22 ± 0.23
0.42 ± 0.22
50-79
0.5º
4º
0.22 ± 0.13
0.5º
4º
0.18 ± 0.12
c
d
(66)
US
Healthy
217
al (2000) 26
Hammond et
7º
0.5º
(79.1 ± 3.2)
46
Hammond et
69-86
or Range
17-92
(41.5±19.7)
US
Healthy
680
(29.6±13.1)
al (2002) 47
Ciulla et al
(2001)
Healthy
280
18-50
0.5º
4º
US
Cataract
24
48-82
0.5º
4º
0.21 ± 0.13
e
f
0.475º
6º
0.18 ± 0.12
0.29 ± 0.16
20-60
0.5º
5.5º
0.30 ± 0.17
16-85
0.5º
7º
0.30 - 0.60
41
Ciulla et al
(2001)
US
0.22 ± 0.14
0.21 ± 0.13
40
Beatty et al
(68.7±9.5)
European
Healthy
46
Irish
Healthy
828
Lam et al
Chinese
Healthy
92
(2005) 20
(Hong Kong)
Tang et al
Chinese
(2001)
24
Nolan et al
(2007)
(2004)
21-81
(51±18)
30
21
Present study
(39.1)
Healthy
67
18-23
0.5º
4º
0.48 ± 0.23
Healthy
272
17-85
0.5º
7º
0.49 ± 0.18
(Hong Kong)
Chinese
(Mainland)
a
Caucasians
African American
c
Subjects with BMI >29 kg/m2
d
Subjects with BMI<29 kg/m2
e
Patients with cataract before cataract exaction
f
Patients with cataract after cataract exaction
CAREDS: Carotenoids in Age-Related Eye Disease Study
b
18