| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
From the Centre for Eye Research Australia, East Melbourne, Victoria, Australia.
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsConclusionsReferences |
|---|
METHODS. Cluster, stratified sampling was used and participants were recruited through a household census. At locally established test sites, standardized clinical examinations were performed to assess cataract and personal interviews were conducted to quantify potential risk factors. Multivariate logistic regression was used to determine the independent risk factors associated with the three types of cataract, and the population attributable risk was calculated.
RESULTS. A total of 3271 (83% of eligible) of the urban residents and 1473 (92%) rural residents participated. 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 103 years (mean, 60 years), and 701 (48%) were men. The overall prevalence of cortical cataract was 12.1% (95% CL 10.5, 13.8), nuclear cataract 12.6% (95% CL 9.61, 15.7), and PSC cataract 4.93% (95% CL 3.68, 6.17). Significant risk factors for cortical cataract included age, female gender, diabetes for greater than 5 years, gout for greater than 20 years, arthritis, myopia, average annual ocular UV-B exposure, and family history of cataract (parents or siblings). Significant risk factors for nuclear cataract included age, female gender, rural residence, age-related maculopathy, diabetes for greater than 5 years, smoker for greater than 30 years, and myopia. The significant risk factors for PSC cataract were age, rural residence, thiazide diuretic use, and myopia. Of the modifiable risk factors, ocular UV-B exposure explains 10% of the cortical cataract in the community, and cigarette smoking accounts for 17% of the nuclear cataract.
CONCLUSIONS. Because of the near universal exposure to UV-B in the environment, ocular protection has one of the highest modifiable attributable risks for cortical cataract and would therefore be an ideal target for public health intervention. Quit smoking campaigns can be expanded to incorporate information about the excess cataract in the community associated with long-term smoking. Nonmodifiable risk factors such as age, gender, and long-term medication use have implications for the timely referral and treatment for those at higher risk of cataract.
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsConclusionsReferences |
|---|
Reviews of the epidemiology of age-related cataract reveal both modifiable and nonmodifiable risk factors, such as age and gender.3 4 Potential modifiable risk factors include UV light exposure, smoking, certain medications, and low antioxidant intake. Although a number of studies about the risk factors for cataract have been completed, we know of no studies that have reported the attributable risk of these various risk factors in the population and the implications for community health planning. There has been considerable discussion in the literature about the appropriate use of attributable risk estimates in public health.5 6 7 8 One of the most frequent errors noted in the interpretation of the attributable risk estimate is to equate this fraction with the proportion of cases having a given risk factor.9 Another feature of the attributable risk that is often misinterpreted is the inability to sum the estimates for the individual attributable risks; in fact, they may sum to greater than 1.0.9 Attributable risk estimates are best used to prioritize medical and public health interventions on the basis of the magnitude of potential effect on the disease outcome in the community.7
The purpose of this study was to estimate the population attributable risk associated with previously identified risk factors for cortical, nuclear, and PSC cataract in a representative sample of the Victorian population aged 40 years and older.
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsConclusionsReferences |
|---|
Lens opacities were graded clinically at the time of the examination
and subsequently from photographs using the Wilmer cataract
photograph-grading system.11
Cortical and posterior
subcapsular (PSC) opacities were assessed on retroillumination.
Cortical opacities were measured as the proportion (in 1/16) of pupil
circumference occupied by opacity, whereas the height and width of the
PSC opacities were recorded. Nuclear opacities were observed by slit
lamp. For this analysis, cortical cataract was defined as 
4/16
opacity, nuclear cataract was defined as opacity equal to or greater
than Wilmer standard 2.0, and PSC cataract was defined as PSC opacity
1 mm2, independent of visual acuity. All people
not defined as cases of cataract were used as controls for the
analyses. Previous analyses have shown that modeling the definition of
cataract as prevalent cataract, including as cases or excluding
entirely previous cataract surgery, and considering different cutoff
values for level of lens opacity does not alter the risk factors
substantially.12
In the case of previous cataract surgery (n = 249, 3.8%), the treating ophthalmologist was contacted whenever possible to obtain details about the type of opacity present before cataract surgery. Prior cataract surgeries were classified as cataract cases. Bilateral congenital cataracts or cataracts secondary to intraocular inflammation or trauma were excluded from the analysis. Three cases of bilateral secondary cataract and eight cases of bilateral congenital cataract were excluded from the analyses.
Photographs were graded separately by two research assistants and discrepancies were adjudicated by an independent reviewer. Except for missing photographs, the photogrades were used in the analyses. Photogrades were available for 4301 (91%) cortical assessments, 4147 (88%) nuclear assessments, and 4304 (91%) PSC assessments. Intraclass correlation coefficients to assess the agreement between the clinical and photogrades were 0.86 for cortical opacity, 0.89 for nuclear opacity, and 0.73 for PSC opacity. People were categorized according to the severity of the opacity in their worse eye.
A standardized questionnaire was used to obtain information about education, employment, and ethnic background. Specific information was elicited on the occurrence, duration, and treatment of a number of medical conditions, including ocular trauma, arthritis, diabetes, gout, hypertension, and mental illness. Information about the use, dose, and duration of smoking, alcohol, analgesics, and steroids were collected. A food frequency questionnaire was used to determine current consumption of dietary sources of antioxidants and use of vitamin supplements.13 Lifetime ocular UV-B exposure was determined for each individual from information about place of residence, time spent outdoors, and the use of ocular protective devices, including hats, spectacles, and sunglasses.14
Data were collected either by direct computer entry with a questionnaire programmed in Paradox (Borland International Inc., Scotts Valley, CA) with internal consistency checks or on self-coding forms. Open-ended responses were coded at a later time. Data that were entered on the self-coded forms were entered into a computer with double data entry and reconciliation of any inconsistencies. Data range and consistency checks were performed on the entire data set. SAS version 6.1 (SAS Institute, Cary, NC) was used for statistical analyses.
Ninety-five percent confidence limits (CL) around the age-specific rates were calculated according to Cochran15 to account for the effect of the cluster sampling. Ninety-five percent CLs around age-standardized rates were calculated according to Breslow and Day.16 The strata-specific data were weighted according to the 1996 Australian Bureau of Statistics census data17 to reflect the cataract prevalence in the entire Victorian population.
Bivariate analyses with t-tests and
2 were first used to evaluate risk factors for
cataract. Any factors with P < 0.10 were then fitted
in a backwards, stepwise, logistic regression model. For the final
multivariate models, P < 0.05 was considered
statistically significant. Design effect was assessed in two manners.
First, cluster-specific models where all variables from the overall
model were forced into models stratified by cluster were calculated.
Second, the final model was run with cluster as a fixed effect. The
design effect was assumed to be additive, and an adjustment made in the
variance by adding the variance associated with the design effect
before constructing the 95% CLs. The adjusted method of attributable
risk estimation based on regression models was used to quantify the
attributable risks for the three cataract types.18
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsConclusionsReferences |
|---|
Cataract Prevalence and Risk Factors
The prevalence of all three types of cataract increases with
age; however, the relative distribution of the three types of
cataract changes with age (Fig. 1)
. Cortical cataract is more common than nuclear cataract until 70 years
of age. PSC is the least common type of cataract at ages greater than
50 years but is the most prevalent cataract in the age group 40 to 49
years. PSC cataract has been shown to have the greatest impact on
vision. The overall prevalence of cortical cataract was 12.1% (95% CL
10.5, 13.8), nuclear cataract 12.6% (95% CL 9.61, 15.7), and PSC
cataract 4.93% (95% CL 3.68, 6.17). A total of 1057 (23% of the
study population) cases of cataract were identified. The distribution
and overlap of cataract type was as follows: 342 (32%), pure cortical
cataract; 344 (33%), pure nuclear cataract; 91 (8.6%), pure PSC
cataract; 143 (14%), cortical and nuclear cataract combined; 57
(5.4%), nuclear and PSC cataract combined; 36 (3.4%), cortical and
PSC cataract combined; and 44 (4.2%), all three types of cataract.
|
- and
ß-blockers, thiazide diuretics, potassium-sparking diuretics, loop
diuretics, family history of cataract (parents or siblings),
myopia -1 diopters (D), age-related maculopathy, eye injury,
body mass index, vitamin A intake and supplements, vitamin C intake and
supplements, vitamin E intake and supplements, ß-carotene intake and
supplements, selenium intake and supplements, zinc intake and
supplements, glaucoma, use of insulin, and ocular UV-B
exposure. For the nutrient supplements, duration of use was also
investigated. Continuous variables were evaluated as both continuous
variables and categorical (ordinal) variables.
Significant bivariate risk factors for cortical cataract included the
following: lifetime ocular UV-B exposure, female gender, education
level, occupation, hypertension, use of calcium channel blockers, use
of ACE inhibitors, use of -blockers, duration of ß-blocker use,
duration of thiazide diuretic use, use of loop diuretics, duration of
diabetes, use of insulin, duration of gout, duration of allopurinol
use, arthritis, duration of aspirin use, duration of acetaminophen use,
duration of hormone replacement therapy, duration of diazepam use,
cigarette smoker, alcohol use, family history of cataract, age-related
maculopathy, higher body mass index, previous eye injury, and lower
intakes of ß-carotene or vitamin E.12
Significant
bivariate risk factors for nuclear cataract included the following:
lifetime ocular UV-B exposure, female gender, rural residence,
education, country of birth, occupation, iris color, duration
hypertension, duration of calcium channel blocker use, duration of ACE
inhibitor use, use of -blockers, years of ß-blocker use, duration
of thiazide diuretic use, use of loop diuretics, duration of diabetes,
duration of gout, use of allopurinol, duration of arthritis, duration
of aspirin use, duration of acetaminophen use, use of systemic or
inhaled corticosteroids, duration of hormone replacement therapy, any
treatment for mental condition, duration of diazepam use, cigarette
smoking, alcohol drinking, myopia, glaucoma, age-related maculopathy,
higher body mass index, prior eye injury, and lower vitamin C, vitamin
E, or ß-carotene consumption.12
Bivariate risk factors
for PSC cataract included the following: lifetime ocular UV-B exposure,
rural residence, country of birth, hypertension duration, use of
calcium channel blocker, use of ACE inhibitor, use of ß-blocker, use
of thiazide diuretic, diabetes, gout, arthritis duration, use of
aspirin, use of acetaminophen, family history of cataract, myopia,
glaucoma, age-related maculopathy, alcohol use, and lower intakes of
vitamin C, vitamin E, or ß-carotene.12
These significant risk factors from the bivariate analyses were then evaluated in backwards, stepwise, logistic regression models. The significant risk factors from the multivariate models varied by cataract type (Tables 1 2 3) . Significant risk factors for cortical cataract included age, female gender, diabetes for greater than 5 years, gout for greater than 20 years, arthritis, myopia, average annual ocular UV-B exposure, and family history of cataract (parents or siblings). Significant risk factors for nuclear cataract included age, female gender, rural residence, age-related maculopathy, diabetes for greater than five years, smoker for greater than 30 years, and myopia. The significant risk factors for PSC cataract were age, rural residence, thiazide diuretic use, and myopia. The potential affect of study design was assessed by modeling the cluster and by conducting cluster-specific models but did not affect the estimates of the odds ratios or SEs.
|
|
|
|
Conclusions |
|---|
|
TopAbstractIntroductionMethodsResultsConclusionsReferences |
|---|
The risk factors for the three types of cataract are similar to what has been reported previously,3 4 with the exception that we did not find steroid use to be associated with PSC cataract, even at the bivariate level. The primary difference with the present study is that sampling strategy resulted in a study sample that is representative of the entire population, and therefore a meaningful estimate of population attributable risk can be made. If the prevalence of a risk factor in the population is very low (as we found for the use of steroids), the population attributable risk will also be low.
The risk factors for cataract identified can be divided into those that are modifiable and those that are not modifiable. The modifiable risk factors are potentially amenable to change through public health interventions, whereas some of the nonmodifiable risk factors have implications for timely detection and treatment by health care practitioners. The majority of risk factors for all three types of cataract are nonmodifiable.
For all three types of cataract, age had the greatest attributable risk. For cortical and nuclear cataract, female gender had the second highest attributable risk. The third highest attributable risk for cortical cataract was family history of cataract. Although all none of these three risk factors are amenable to primary intervention, they do have implications for secondary prevention. People at higher risk of developing cataract should be advised to be alert for changes in their vision associated with the development of cataract. Furthermore, health care providers should be informed about the high-risk groups so that they can refer these patients for timely treatment of cataract before the onset of severe functional impairment. Systemic diseases (such as diabetes, gout, and arthritis) or medication for systemic diseases (thiazide diuretic use) were associated with cataract. Therefore, primary prevention of the systemic diseases would also serve as primary prevention for cataract, although the attributable risks were quite low, with the exception of arthritis and cortical cataract (PAR = 11%).
Although we found that myopia was associated with all three types of cataract, we do not think that this association was causal. We have previously reported in this population that a myopic shift occurs in the presence of increasing nuclear opacity.20 The myopic shift with increasing opacity, especially nuclear sclerosis, has long been recognized.
The largest attributable risks for cataract were documented for ocular UV-B exposure and cortical cataract (PAR = 10%), and long-term smoking and nuclear cataract (PAR = 17%). The large percentage of the population with these exposures contributes to their high attributable risks. These data provide further support for public health campaigns to decrease the prevalence of smoking in the community and to increase ocular protection from UV-B by avoidance of the midday sun and use of shade, sunglasses, and brimmed hats. These factors are especially important because they are the most obvious targets for primary public health prevention strategies of the identified risk factors for the three types of cataract.
In conclusion, knowledge of attributable risk as well as odds ratios associated with risk factors for cataract will allow informed decision making to prioritize primary and secondary prevention strategies for cataract in the community.
|
Acknowledgements |
|---|
|
Footnotes |
|---|
Submitted for publication September 17, 2000; revised July 10, 2000; accepted July 25, 2000.
Commercial relationships policy: N.
Corresponding author: Catherine Anne McCarty, Centre for Eye Research Australia, 32 Gisborne Street, East Melbourne, Victoria 3002, Australia. cathy{at}iris.medoph.unimelb.edu.au
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsConclusionsReferences |
|---|
This article has been cited by other articles:
|
|
 |
|
  G. Chodick, N. Bekiroglu, M. Hauptmann, B. H. Alexander, D. M. Freedman, M. M. Doody, L. C. Cheung, S. L. Simon, R. M. Weinstock, A. Bouville, et al. Risk of Cataract after Exposure to Low Doses of Ionizing Radiation: A 20-Year Prospective Cohort Study among US Radiologic Technologists Am. J. Epidemiol., September 15, 2008; 168(6): 620 - 631. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 Y.-B. Shui and D. C. Beebe Age-Dependent Control of Lens Growth by Hypoxia Invest. Ophthalmol. Vis. Sci., March 1, 2008; 49(3): 1023 - 1029. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. West Poverty and Human Development: Not a Stretch for Ophthalmology Arch Ophthalmol, November 1, 2007; 125(11): 1564 - 1565. [Full Text] [PDF]
|
|
|
|
|
|
V. Talla, C. Narayanan, N. Srinivasan, and D. Balasubramanian Mutation Causing Self-Aggregation in Human {gamma}C-Crystallin Leading to Congenital Cataract Invest. Ophthalmol. Vis. Sci., December 1, 2006; 47(12): 5212 - 5217. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M C Grieshaber, I Kocak, B Dubler, J Flammer, and S Orgul Retrobulbar blood flow in patients with cataract Br. J. Ophthalmol., December 1, 2006; 90(12): 1512 - 1515. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
N Congdon Self assessed benefit of cataract extraction Br. J. Ophthalmol., August 1, 2005; 89(8): 931 - 931. [Full Text] [PDF]
|
|
|
|
|
|
B. E. Lindblad, N. Hakansson, H. Svensson, B. Philipson, and A. Wolk Intensity of Smoking and Smoking Cessation in Relation to Risk of Cataract Extraction: A Prospective Study of Women Am. J. Epidemiol., July 1, 2005; 162(1): 73 - 79. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. K Pokhrel, K. R Smith, A. Khalakdina, A. Deuja, and M. N Bates Case-control study of indoor cooking smoke exposure and cataract in Nepal and India Int. J. Epidemiol., June 1, 2005; 34(3): 702 - 708. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. P. Klein, P. Duggal, K. E. Lee, J. A. O'Neill, R. Klein, J. E. Bailey-Wilson, and B. E. K. Klein Polygenic Effects and Cigarette Smoking Account for a Portion of the Familial Aggregation of Nuclear Sclerosis Am. J. Epidemiol., April 15, 2005; 161(8): 707 - 713. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M.-B. Tessem, T. F. Bathen, J. Cejkova, and A. Midelfart Effect of UV-A and UV-B Irradiation on the Metabolic Profile of Aqueous Humor in Rabbits Analyzed by 1H NMR Spectroscopy Invest. Ophthalmol. Vis. Sci., March 1, 2005; 46(3): 776 - 781. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
The Eye Diseases Prevalence Research Group Causes and Prevalence of Visual Impairment Among Adults in the United States Arch Ophthalmol, April 1, 2004; 122(4): 477 - 485. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. Hennis, S.-Y. Wu, B. Nemesure, and M. C. Leske Risk Factors for Incident Cortical and Posterior Subcapsular Lens Opacities in the Barbados Eye Studies Arch Ophthalmol, April 1, 2004; 122(4): 525 - 530. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 N. G. Congdon, D. S. Friedman, and T. Lietman Important Causes of Visual Impairment in the World Today JAMA, October 15, 2003; 290(15): 2057 - 2060. [Full Text] [PDF]
|
|
|
|
|
|
C. Younan, P. Mitchell, R. G. Cumming, E. Rochtchina, and J. J. Wang Myopia and Incident Cataract and Cataract Surgery: The Blue Mountains Eye Study Invest. Ophthalmol. Vis. Sci., December 1, 2002; 43(12): 3625 - 3632. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
N. G Congdon Prevention strategies for age related cataract: present limitations and future possibilities Br. J. Ophthalmol., May 1, 2001; 85(5): 516 - 520. [Full Text]
|
|
|
|
|
|
H. R Taylor and J. E Keeffe World blindness: a 21st century perspective Br. J. Ophthalmol., March 1, 2001; 85(3): 261 - 266. [Full Text]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
