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Risk Factors for Age-Related Maculopathy
The Visual Impairment Project
Catherine A. McCarty, PhD, MPH;
Bickol N. Mukesh, PhD;
Cara L. Fu, GradDip (IT);
Paul Mitchell, FRACO;
Jie Jin Wang, Mmed, MBBS;
Hugh R. Taylor, MD, FRACO
Arch Ophthalmol. 2001;119:1455-1462.
ABSTRACT
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Objective To describe the risk factors and associated population attributable
risk for age-related maculopathy (ARM) and age-related macular degeneration
(AMD) in Australians aged 40 years and older.
Methods Residents were recruited from 9 randomly selected urban clusters and
4 randomly selected rural clusters in Victoria, Australia. At locally established
test sites, the following information was collected: visual acuity, medical
and health history, lifetime sunlight exposure, dietary intake, and fundus
photographs. Age-related maculopathy and AMD were graded from the fundus photographs
using an international classification and grading system. Backwards logistic
regression was used to identify the independent risk factors for ARM and AMD.
Results The participation rate was 83% (n = 3271) among the urban residents
and 92% (n = 1473) among the rural residents. Gradable fundus photographs
of either eye were available for 4345 (92%) of the 4744 participants. There
were 656 cases of ARM, giving a weighted prevalence of 15.1% (95% confidence
limit [CL], 13.8, 16.4); and there were 30 cases of AMD, giving a weighted
prevalence of 0.69% (95% CL, 0.33, 1.03). In multiple logistic regression,
the risk factors for AMD were as follows: age (odds ratio [OR], 1.23; 95%
CL, 1.17, 1.29), smoked cigarettes for longer than 40 years (OR, 2.39; 95%
CL, 1.02, 5.57), and ever taken angiotensin-converting enzyme inhibitors (OR,
3.26; 95% CL, 1.33, 8.01). The magnitude of all of these risk factors was
slightly less for ARM, and having ever taken blood cholesterol–lowering
medications was also significant (OR, 1.67; 95% CL, 1.12, 2.47; P = .001).
Conclusion Smoking is the only modifiable risk factor for ARM and AMD, among the
many environmental and systemic factors that were assessed.
INTRODUCTION
LATE AGE-RELATED maculopathy (ARM) or age-related macular degeneration
(AMD) is the most common cause of vision impairment in most developed countries,
including Australia.1-2 With the
changing demographic profiles that will lead to a further increase in the
number of elderly persons, AMD will become even more common in the future.
We do not know how to prevent ARM or AMD, and treatment is only partially
effective for a few patients with AMD. Therefore, research efforts need to
be directed at the primary and secondary prevention of AMD.
Several studies3-9
have reported the risk factors for ARM and AMD in population-based and case-control
studies. There have been numerous other reports of specific risk factors,
modifiable and nonmodifiable, for ARM and AMD. They include genetic influences,10-15
refractive error,16-17 iris color,18-19 heart disease and hypertension,20-22 smoking,23-29
alcohol consumption,30-31 and
sunlight.32-34
Antioxidants have been shown in some studies35-39
to be protective for ARM and AMD. Despite this extensive body of research
into the risk factors for ARM and AMD in various study populations, to our
knowledge, there have been only 2 reports24, 40
of the population attributable risk associated with any of these risk factors.
Mitchell et al40 recently estimated that the
attributable risk for AMD in former and current smokers ranges from 20% to
68%. This information is necessary to design appropriate public health interventions
to maximize the potential for decreasing the prevalence and incidence of ARM
and AMD in the community.
This study describes the risk factors and associated population attributable
risk for ARM and AMD in a population-based sample of representative Australians
aged 40 years and older.
PARTICIPANTS AND METHODS
The detailed methods used for the Visual Impairment Project were published
previously.41 In summary, 9 pairs of urban
census collector districts and 4 pairs of rural census collector districts
were randomly selected from which to recruit residents in Victoria, Australia,
aged 40 years and older to participate. Residents were identified and recruited
through a household census. At locally established test sites, the following
information was collected: demographic details, visual acuity when first seen
and best-corrected visual acuity on a 4-m LogMAR chart, intraocular pressure,
visual fields, personal health history and use of medications, dietary intake,42 lifetime history of time spent outdoors and ocular
protection behaviors while outdoors,43 and
clinical eye examination results. The study protocol was approved by the Royal
Victorian Eye and Ear Hospital Human Research and Ethics Committee.
The Visual Impairment Project model to quantify lifetime ocular exposure
to UV-B43 was modified to quantify lifetime
ocular exposure to visible light. This was accomplished with the use of total
global radiation data, ocular exposure ratios for visible light that revealed
no protective effect for hats,44 and information
about the transmittance of visible light through sunglasses.45
Clinical examinations and fundus photography were performed by 2 trained
ophthalmic research fellows using a standardized protocol. A retinal camera
(Topcon TRC FET; Topcon America Corp, Paramus, NJ) and film (Kodachrome 64
ASA; Kodak Australia, Mourebank, New South Wales) were used to obtain stereoscopic
photographs of the central fundus area and macular arcades. All photographs
were then graded according to the Wisconsin Age-Related Maculopathy Grading
System.46 Poor-quality photographs were not
graded. A plastic grid, comprising 3 concentric circles of radii 500, 1500,
and 3000 µm, and 4 radial lines that divided the photograph into subfields
were placed over each stereoscopic pair of slides and centered on the fovea.
Only ARM lesions present within the grid were noted. Photographs were considered
gradable if the fovea and two thirds of the macula were visible.
Age-related maculopathy and AMD were classified according to an international
classification and grading system.47 Age-related
macular degeneration was classified as "wet" (neovascular) or "dry" (atrophic),
but was combined for analysis in the present report. Neovascular AMD included
serous or hemorrhagic detachment of the retinal pigment epithelium or sensory
retina, intraretinal and/or subretinal and/or sub–retinal pigment epithelial
hemorrhages, or subretinal fibrous scars. Early ARM
was defined as the presence of soft distinct, soft indistinct, or reticular
drusen or the presence of any retinal pigmentary abnormalities in the absence
of signs of AMD lesions. Small hard drusen alone were not considered as early
ARM.
Interview data were entered directly into a data entry system (Paradox;
Carel Corp, Ottawa, Ontario) with internal consistency checks. The following
variables were created from the smoking information: current, past, or never
smoker; pack-years of smoking; total years of smoking; and years since quitting
smoking. Pack-years of smoking and total years of smoking were categorized
into 10-year groups, through to greater than 40 years. All other data were
entered twice and verified. A 5% random sample of the fundus photographs was
graded twice to assess reliability. The more severely affected eye was used
for the analysis.
SAS statistical software (SAS Institute Inc, Cary, NC) was used for
all statistical analyses. The  statistic was used to evaluate the agreement
between the 2 photogrades. Prevalence estimates were weighted to the 1996
Australian Bureau of Statistics data to reflect the population of Victoria.
Univariate analyses included the t test and the  2 test. Backwards logistic regression was used to assess the independent
risk factors for ARM and AMD. The Smith serially additive expected dose model48 was used to evaluate the association between average
annual ocular visible light exposure and ARM or AMD for case and control subjects
for each year of life. Attributable risk estimates were calculated according
to the methods of Bruzzi et al.49
RESULTS
STUDY POPULATION
A total of 3271 (83%) urban residents and 1473 (92%) rural residents
participated. Nonparticipants differed from participants only in language
spoken at home; they were more likely to speak a language other than English
at home.50 The participation rate for people
who spoke Greek at home was 76% compared with 85% for people who spoke English
at home. The study population is representative of the Victorian population
and of Australia as a whole.50 The urban residents
ranged in age from 40 to 98 years (mean, 59 years), and 1511 (46%) were men.
The rural residents ranged in age from 40 to 95 years (mean, 59 years), and
701 (48%) were men.
Gradable fundus photographs of either eye were available for 4345 (92%)
of the 4744 participants. In multivariate analyses, 2 factors remained significantly
associated with the availability of gradable fundus photographs: age and rural
residence (P = .001 for both). There was no significant
difference in the frequency of the diagnosis of ARM or AMD on clinical examination
(P = .94) in those subjects who had or did not have
gradable photographs. There were 656 cases of ARM, giving a weighted prevalence
of 15.1% (95% confidence limit [CL], 13.8, 16.4); and 30 cases of AMD, giving
a weighted prevalence of 0.69% (95% CL, 0.33, 1.03). The number of people
with any pigmentary abnormalities was 356; 316 people had soft distinct drusen,
178 had soft indistinct drusen, and 266 had large drusen ( 125 µm).
These features are not mutually exclusive.
RISK FACTORS FOR ARM AND AMD
The following potential risk factors for any ARM and AMD were assessed
with univariate analyses: age, sex, rural residence, educational level, country
of birth, parents' country of birth, iris color, smoking history, alcohol
intake, family history of AMD, body mass index, glaucoma, self-reported diagnosed
hypertension, self-reported diagnosed diabetes, use of blood cholesterol–lowering
medications, use of hormone replacement therapy, refractive status (myopia
or hyperopia), intake of dietary and supplementary antioxidants, cataract,
prior cataract surgery, and average annual ocular visible light exposure.
After controlling for age, borderline significant (P<.10)
univariate risk factors are summarized in Table 1 and Table 2.
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Table 1. Univariate Risk Factors for ARM*
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Table 2. Univariate Risk Factors for AMD*
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The Smith serially additive expected dose model48
was used to explore the relationship of lifetime ocular sun exposure and ARM.
Although the mean annual ocular sun exposure was greater for people with ARM
than for people without ARM for those aged 28 to 80 years, this finding was
not significant (P = .76). We conducted a restricted
analysis of the sunlight data to determine if more recent sunlight exposure
was associated with ARM. We found that the mean annual ocular sun exposure
(expressed in Melbourne sun years) over the previous 20 years was not significantly
different between people with and without ARM (mean, 0.33 and 0.32, respectively; t = 0.84; P = .40).
The significant (P<.10) univariate risk
factors were then placed into a logistic regression model. Family history
of AMD was not included in the multivariate models because the data were not
available for most of the cohort. The following risk factors were found to
be significantly associated with the prevalence of any ARM: age (P = .001), having smoked cigarettes for longer than 40 years (P = .03), angiotensin-converting enzyme (ACE) inhibitor
use (P = .001), and use of blood cholesterol–lowering
medication (P = .01) (Table 3). The magnitude of all of these risk factors was greater
for AMD, except for blood cholesterol–lowering medication use, which
was not significant (P = .71) (Table 3).
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Table 3. Multivariate Risk Factors and Population Attributable Risks
for AMD and ARM*
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The attributable risk estimates reveal that age has the greatest impact
on the prevalence of ARM in the community, followed by ACE inhibitor use and
smoking (Table 3). The population
attributable risks were all higher for AMD (Table 3).The multivariate risk factors were further evaluated by
using the definition of ARM that was used by the Beaver Dam Eye Study21 and the Blue Mountains Eye Study.2
The results were nearly identical, although use of blood cholesterol–lowering
medication was no longer statistically significant (P
= .18; data not shown).
The association of smoking and ARM and AMD was explored further by evaluating
the age-adjusted odds ratios (ORs) for various categories of smoking behavior
(Table 4 and Table 5, respectively). These data reveal that only the duration,
not the amount, of smoking is associated with ARM and AMD. Current smoking
status was not related to ARM, and although persons with AMD were more than
2 times more likely to be current smokers than never smokers, this finding
was not statistically significant (P = .11). In ever
smokers, a dose-response relationship with years of cigarette smoking was
observed for ARM (Mantel-Haenszel 2 = 33.6; P<.001) but not for AMD (P>.10). Significant
dose-response relationships were not observed for any of the other measures
of cigarette smoking (data not shown, P>.10).
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Table 4. Relation of Smoking and ARM*
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Table 5. Relation of Smoking and AMD*
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The risk factors for women were modeled in separate multivariate logistic
regression models. Women who reached menopause at or before the age of 40
years were found to have a higher prevalence of ARM or AMD (OR, 1.78; 95%
CL, 1.16, 2.74). The number of years between menarche and menopause was not
significant (P = .57) in multivariate analyses (data
not shown).
The potential effect of the cluster sampling strategy was evaluated
by including in the logistic model a fixed term for the cluster and by modeling
the risk factors separately by cluster. There was no significant difference
in the results (data not shown).
COMMENT
To our knowledge, this is the first population-based study to report
the risk factors and the population attributable risk associated with these
risk factors for ARM. An advantage of the Visual Impairment Project is that
the sampling scheme has provided a study population that is representative
of Victorians and Australians aged 40 years and older. That allows meaningful
interpretation of the attributable risk estimates that can then be used for
public health planning in Australia.
Several studies5, 10-15
have revealed a possible genetic link for ARM. Although the persons with ARM
in our study were more than twice as likely as controls to report a family
history of ARM, we were not able to explore this relationship in multivariate
analyses because of missing data. Many members of the study population were
not asked further questions about family history of AMD because they had never
heard of the disease. Identification of a gene for AMD could lead to screening
programs for the early detection and treatment of AMD.
We did not find a significant association with sex in our multivariate
analyses. Similar results were also observed in the pooled data from the Beaver
Dam Eye Study, the Rotterdam Study, and the Blue Mountains Eye Study.51 However, when the analyses were rerun using the same
definition of ARM as given in these 3 studies, we did find a significantly
increased risk of ARM in women (OR, 1.37; 95% CL, 1.02, 1.84). Age-related maculopathy was defined in these 3 studies as the presence
of soft indistinct or reticular drusen or the presence of soft distinct and
retinal pigmentary abnormalities. In the international classification of ARM
that we used,47 ARM
was defined as the presence of soft indistinct or reticular drusen, soft distinct
drusen, or retinal pigmentary abnormalities. The definition that we used resulted
in more cases of early ARM.
There have been 2 reports7, 52
in the literature of a possible association between estrogen and AMD, with
a suggestion of an indirect link between estrogen use, cardiovascular disease,
and AMD. In the Eye Disease Case-Control Study,7
researchers found that persons with AMD were more likely to be former or current
estrogen users. In the Blue Mountains Eye Study,52
researchers found a protective effect for early AMD, with increasing years
from menarche to menopause. In the present study, persons with ARM were slightly
less likely than controls to have ever taken hormone replacement therapy and
had more years between menarche and menopause, but these findings were not
significant in multivariate analyses. We did find in multivariate analyses,
however, that persons with ARM or AMD were significantly more likely to have
reached menopause at an earlier age. These results suggest that estrogen may
somehow be protective for AMD, but this hypothesis requires further investigation.
Hyperopia has been demonstrated to be a risk for AMD in several studies,4-6,9, 16-17
although there is no underlying hypothesis for this association. Although
persons with ARM in the present study were significantly more likely in univariate
analyses to have hyperopia, even when controlling for the presence of a nuclear
opacity (21 = 4.4, P =
.04), this finding was not significant in multivariate analyses.
Age-related macular degeneration has been found to be associated with
cataract and cataract surgery in several studies,9, 53-54
although the results have been inconsistent in the type of lens opacity associated
with AMD. In the present study, we found that prevalent cataract of each type
and prior cataract surgery were significantly associated with ARM in univariate
analyses, but not in multivariate analyses. Prospective data from the Beaver
Dam Eye Study revealed that cataract surgery was significantly associated
with the progression of ARM and late AMD, but that no specific lens opacities
were associated with the incidence or progression of ARM.55
Although an association between light-colored irides and AMD has been
demonstrated in several studies,5, 9, 18-19
an association was not observed in either the Eye Disease Case-Control Study7 or the National Health and Nutrition Examination Survey
in the United States.6 There is no agreed hypothesis
as to why iris color might be related to AMD, although it has been suggested
that there might be an indirect link with skin sun sensitivity or the ability
to repair sun-induced damage.19 Recent data
on macular pigment density could be considered to underlie this finding. In
the present study, we did not find a significant relationship between iris
color and ARM or AMD.
Two previous studies6-7
have demonstrated nonsignificant inverse associations between educational
level attained and AMD. We did not find a significant relationship between
educational level and ARM or AMD. Cross-sectional findings related to socioeconomic
status are difficult to interpret because the higher socioeconomic groups
live longer and are, therefore, able to participate in studies. Prospective
data are needed to properly assess the potential association of education
or other sociodemographic variables with the incidence of ARM, after accounting
for selective mortality.
A vascular basis for AMD has been suggested in several studies, with
associations between hypertension,3, 6, 9, 20, 22
cerebrovascular disease,5-6 atherosclerosis,9, 22 serum cholesterol level,7, 23
plasma fibrinogen level,56 and AMD having been
documented. Underlying mechanisms proposed for this association have included
effects on the choroidal circulation and lipid deposition within Bruch's membrane.
However, the data have not been consistent for the systemic diseases and the
medications for these systemic diseases. Similarly, in the present study,
we found that use of either ACE inhibitors or blood cholesterol–lowering
medications was significantly associated with the prevalence of ARM and AMD,
but the presence of the systemic diseases (hypertension or hypercholesterolemia)
was not significantly related to ARM in multivariate analyses. The statistically
significant finding with ACE inhibitors is potentially spurious due to the
many factors investigated. Prospective data are needed to confirm the significance
and temporality of these cross-sectional observations and to address the issue
of causality.
One of the most consistently observed risk factors for AMD that has
been documented in epidemiologic studies5, 7, 23-29
is smoking, possibly directly due to oxidative stress, indirectly due to the
promotion of atherosclerosis, or due to its effect in decreasing macular pigment
density. In the present study, we found that number of pack-years of smoking
was not related to the prevalence of ARM. However, the total duration of smoking,
regardless of amount, was significantly associated with the prevalence of
ARM. Although people with AMD were 2.4 times as likely to be current smokers
in our study, this finding was not statistically significant, probably because
of the relatively few cases. Although not statistically significant, the magnitude
of the OR for current smoking and late AMD observed in the present study is
not significantly different from the OR of 4.46 for current smoking and AMD
in the Blue Mountains Eye Study,26 the OR of
2.2 for neovascular AMD in the Eye Disease Case-Control Study,7
the OR of 3.6 for late AMD in the POLA Study,29
the OR of 3.6 for neovascular AMD in the Rotterdam Study,27
and the OR of 2.5 for women and 3.29 for exudative AMD in the Beaver Dam Eye
Study.23
Smoking is an important risk factor when considered from the public
health perspective, as smoking habits in the community are potentially modifiable
through intervention. Mitchell et al40 recently
estimated that 20% of all cases of blindness in Australia may be attributable
to smoking, and they advocated a new warning for cigarette packs about the
risk of blindness associated with smoking. Our present data suggest that 14%
of AMD cases are due to cigarette smoking for longer than 40 years. Although
there is a disparity between the attributable risk estimates for ARM and AMD,
the finding has public health significance because smoking was the only identified
modifiable risk factor. Also, people should continue to be encouraged to quit
smoking for other health reasons, including the risk of lung cancer and heart
disease.
Another weak-purported risk factor for AMD, potentially due to oxidative
damage again, is alcohol use.30-31
Again, this is an important potential risk factor because of the possibility
for modification of the prevalence of alcohol use in the community through
education and intervention. Although we found a significant univariate association
between alcohol intake and ARM, this relationship did not persist in multivariate
analyses.
A third source of oxidative damage to the retina that has been suggested
as a possible risk factor for AMD is ocular sunlight exposure, specifically
visible light as opposed to UV light.32-34
No such association was seen in the Eye Disease Case-Control Study7 or in a large Australian study.34
In the present study, we found in univariate analyses that persons with ARM
had higher annual ocular sun exposure levels than controls for most of their
lives, but this finding was not statistically significant. In the Chesapeake
Bay Watermen Study,32 researchers found that
ocular sun exposure in the previous 20 years was significantly associated
with the presence of AMD. We were not able to support this finding in our
study.
Given the potential risk factors for AMD that are suspected of eliciting
oxidative damage in the retina, it would make biological sense if antioxidants
were found to be protective for AMD, as has been reported in several studies.6-7,35-39
However, several other studies39, 57-60
have found no association between antioxidants and ARM. Given these inconsistent
data, most researchers have advocated clinical trials to further assess the
association of antioxidants and ARM. There are several studies under way to
evaluate the effect of antioxidant supplementation on the incidence and/or
progression of ARM, including the Vitamin E, Cataract, and Age-Related Maculopathy
study61-62 in Australia and the
Age-Related Eye Disease Study63 in the United
States. If found to be effective, antioxidant supplementation would be one
of the first opportunities for the primary prevention of AMD. In the present
study, neither vitamin E or C supplementation nor total daily vitamin E or
C intake was found to be associated with ARM or AMD. There is a potential
for misclassification of the nutrient status of the cases and controls, however,
because the dietary instrument used comprises approximately 58% of the total
dietary vitamin C intake and 65% of the total dietary vitamin E intake.42
Population attributable risk estimates are useful public health tools,
although researchers and policy makers should be aware that attributable risk
estimates from cross-sectional data may not correspond with estimates from
prospective data. Valid figures allow estimates to be made of the potential
decrease in disease prevalence that could be expected through intervention
on a given risk factor because they combine the size of the OR and the prevalence
of the risk factor in the population.49 They
can be useful in prioritizing strategies for public health intervention and
the education of health care professionals. In the present study, the highest
attributable risk for ARM was associated with increasing age. Although this
may reinforce the recommendation that elderly persons have regular eye examinations,
it clearly is not a modifiable risk factor. The attributable risk estimates
for ACE inhibitor and blood cholesterol–lowering medication use were
not extremely great. More corroborative data from other studies and evidence
from longitudinal studies about the significance of these potential risk factors
are necessary before making any public health recommendations.
The strengths of this study lie in the representativeness of the study
cohort, the relatively high response rate, and the standardized protocol that
was used. The limitations of the study include the relatively few cases of
AMD, which decreases the power of the study to identify significant risk factors.
As with any cross-sectional study, potential for bias exists due to differential
mortality, ie, people with a certain risk factor or with ARM or AMD may have
higher mortality rates and, thus, may not have participated in this study.
Finally, self-reported data have the potential for error.
In conclusion, although several risk factors for ARM have been identified
in this study, prospective data are needed to confirm the cross-sectional
findings before public health and medical interventions can be recommended.
AUTHOR INFORMATION
Accepted for publication February 12, 2001.
The Visual Impairment Project was funded in part by grants from the
National Health and Medical Research Council, Canberra, Australia; the Victorian
Health Promotion Foundation, Carlton, Australia; the estate of the late Dorothy
Edols; and the Jack Brockhoff Foundation, Melbourne. Dr McCarty is the recipient
of the Wagstaff Research Fellowship in Ophthalmology from the Royal Victorian
Eye and Ear Hospital, East Melbourne, Australia.
The fundus photographs were graded by Dr Mitchell and the Blue Mountains
Eye Study team, which included Dr Wang and Mireille Moffitt.
Corresponding author and reprints: Bickol N. Mukesh, PhD, Centre
for Eye Research Australia, University of Melbourne, 32 Gisborne St, East
Melbourne, VIC 3002, Australia (e-mail: mukeshbn{at}unimelb.edu.au).
From the Centre for Eye Research Australia, University of Melbourne,
East Melbourne (Drs McCarty, Mukesh, and Taylor and Ms Fu); and the Department
of Ophthalmology and the Save Sight Institute, University of Sydney, Westmead
Hospital, Sydney, Australia (Drs Mitchell and Wang).
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