Abstract
purpose. To assess prevalence, potential risk factors, and population attributable risk percentage (PAR%) for age-related macular degeneration (AMD) in the Indian state of Andhra Pradesh.
methods. A population-based study, using a stratified, random, cluster, systematic sampling strategy, was conducted in the state of Andhra Pradesh in India from 1996 to 2000. Participants from 94 clusters in one urban and three rural areas representative of the population of Andhra Pradesh underwent a detailed interview and a detailed dilated ocular evaluation by trained professionals. In this report, the authors present the prevalence estimates of AMD and examine the association of AMD with potential risk factors in persons aged 40 to 102 years (n = 3723). AMD was defined according to the international classification and grading system. Standard bivariate and multivariate analyses were performed to identify the potential risk factors for AMD. PAR% was calculated by Levin’s formula.
results. AMD was present in 71 subjects—an age-gender-area–adjusted prevalence of 1.82% (95% confidence interval [CI], 1.39%–2.25%). Risk factors that were significant in bivariate analyses were considered for multivariate logistic regression analysis. Multivariate analysis showed that the adjusted prevalence of AMD was significantly higher in those 60 years of age or older (odds ratio [OR], 3.55; 95% CI, 1.61–7.82) and history of prior cigar smoking (OR, 3.29; 95%CI, 1.42–7.57). Presence of cortical cataract and prior cataract surgery were significantly associated with increased prevalence of AMD (adjusted OR, 2.87; 95% CI, 1.57–5.26 and 3.79; 95% CI, 2.1–6.78), respectively. The prevalence of AMD was significantly lower in light alcohol drinkers (adjusted OR, 0.38; 95% CI, 0.19–0.76) compared with nondrinkers. The PAR% for hypertension and heavy cigar smoking was 10% and 14%, respectively, in this population.
conclusions. The prevalence of AMD in this south Indian population is similar to those reported in other developed countries. Abstinence from smoking may reduce the risk of AMD in this population.
Age-related macular degeneration (AMD) is one of the common causes of irreversible vision loss among the elderly and is a major risk factor for disability in the older population. It substantially affects the quality of life of an individual.
1 It is estimated that 8 million people will be affected with AMD worldwide by the year 2020.
2 Estimates indicate that 10% to 20% of AMD is the wet form responsible for approximately 90% of severe vision loss.
2 Recent findings from a population-based study from rural India have reported the prevalence of early and late AMD at 2.7% (95% CI, 2.2–3.2) and 0.6% (95% CI, 0.4–0.8), respectively.
3 Treatment options in AMD are limited, and to date there are no established means of reliable prevention of disease progression.
4
The investigation of risk factors for AMD is important in understanding the disease and suggests preventive measures that can retard or control disease progression. Several studies have reported modifiable and nonmodifiable risk factors for AMD.
5 6 7 8 9 10 11 12 13 14 Although several factors were identified, only age, tobacco smoking, hypertension, and obesity haven been confirmed as increasing the risk of AMD.
5 6 There is also increasing evidence to suggest that cataract surgery is a significant predictor, with a four- and threefold increase in the risk of neovascular AMD and geographic atrophy, respectively.
5 6
The population attributable risk percentage (PAR%) tells us the percentage of risk in the community that is associated with exposure to a risk factor, and it is used to prioritize public health interventions.
15 16 To the best of our knowledge, although there are reports of the PAR% (13.8% for cigarette smoking) for AMD from Australia, this statistic has not been published for the Indian population.
17 We investigated possible risk factors for AMD and estimated the PAR percentage associated with these risk factors for AMD in a representative sample of the population aged 40 years and more in a state in south India.
The details of the design of the Andhra Pradesh Eye Disease Study (APEDS), conducted from 1996 to 2000, in accordance with the tenets of the Helsinki Declaration, have been described previously.
18 19 20 Approval of the Ethics Committee of the Institute was obtained for the study design.
Briefly, a multistage sampling procedure was used to select the study sample of 10,000 persons, 5,000 each older or younger than 30 years, based on the assumption that a 0.5% prevalence of an eye disease in either of these groups may be of public health significance. This sample would estimate the prevalence as 0.3% to 0.8% at the 95% confidence level. One urban and three rural areas from different parts of the southern Indian state of Andhra Pradesh were selected, with the purpose of including approximately 2500 participants in each area, such that these would roughly reflect the urban–rural and socioeconomic distribution of the population of this state. These four areas were located in Hyderabad (urban), West Godavari district (well-off rural), and Adilabad and Mahabubnagar districts (poor rural).
For the urban (Hyderabad) component of the APEDS, the blocks (clusters) of Hyderabad were stratified by socioeconomic status and religion. The socioeconomic strata (SES) were extreme lower (monthly per capita income in rupees ≤200 [$US 5:1]), lower (201–500), middle (501–2000), and upper (>2000); the religions were Hindu and Muslim. After this stratification, 24 clusters were chosen by using stratified random sampling, with equal probability of selection, such that the socioeconomic and religious distribution in the sample would be similar to that in the population. The selected clusters were mapped, and households were selected systematically by using a sampling interval of three to five to obtain a similar number of households in the various clusters. A total of 2954 subjects were sampled with the purpose of achieving a recruitment rate of at least 85%, to obtain a minimum sample of 2500.
From three rural areas from different parts of Andhra Pradesh, 70 rural clusters were selected with the purpose of having a study sample representative of the socioeconomic distribution of the rural population of the state. These three rural areas were located in the West Godavari (well-off rural), Adilabad, and Mahabubnagar (poor rural) districts. For these three rural segments, a total of 8832 subjects were sampled of which 7771 eligible participants were interviewed by trained field investigators.
Dilated Ophthalmic Examination.
Anthropometric Measurements.
Smoking Status.
Cumulative Smoking Dose.
Body Mass Index.
Cataract.
AMD.
Blindness and Moderate Visual Impairment.
Data from this population-based study demonstrated the expected association between age and AMD. Cigar smoking, cortical cataract, and cataract surgery were also significantly associated with AMD, whereas light alcohol consumption was protective. Based on our results, cigar smoking and possibly hypertension were identified as modifiable risk factors, whereas age, cortical cataract, and cataract surgery were identified as nonmodifiable risk factors.
As reported in other populations worldwide, age was significantly associated with AMD.
7 34 35 37 38 39 When age was entered in the logistic regression model as a covariate, for each unit (a year) of increment of age, there was a 1.05 (95% CI, 1.03–1.07;
P < 0.0001) odds ratio of increment of AMD in this population. The odds of AMD were slightly higher in people of lower socioeconomic status; however, this was not statistically significant in a multivariate model that explored interactions among SES, smoking, and alcohol intake.
There are conflicting reports of an association of hypertension and AMD. We did not find hypertension to be associated with AMD in our sample.
3 8 40 41 42 43 44 45 46 However, we found higher odds of AMD in the hypertensive group. We do not, however, have any evidence that antihypertensive medications lower the risk of AMD. Our study results suggest that persons with moderate or severe hypertension may benefit from periodic retinal examinations, since they are at risk for development of AMD.
The prevalence of AMD was significantly higher in those with a history of
heavy cigar smoking compared with never smokers. Heavy cigar smoking attributed to 14% of the avoidable risk of AMD in this population
(Table 3) . We found higher, but not statistically significant, odds of AMD in cigarette smokers. It is possible that the difference between cigar and cigarette smokers may be associated with differences in the nicotine content and dose inhaled. It is also possible that the nicotine content of home-rolled cigars may be higher, as it uses crude unprocessed tobacco compared with cigarettes and may have more toxicity than the cigarettes. Also, cigars weigh 2 to 3 g each, whereas the cigarettes weigh approximately 0.82 g each. In addition, many cigarettes have filters, whereas the local cigars do not have any. Smoking is the most consistent risk factor associated with the prevalence of AMD.
10 14 17 There are other health benefits that may accrue from not smoking. We did not try to determine effects of passive smoking in this population.
Our results suggest that the presence of cortical cataract and prior cataract surgery was significantly associated with the increased risk of AMD. The finding of a higher prevalence of AMD in the presence of cortical cataract is not consistent with a previously published report.
47 The significant association of AMD with prior cataract surgery is also not consistent with some of the previously published reports.
5 6 48 49 50 51 Our cross-sectional study design does not allow us to assign causality and it is possible that some of the eyes with prior cataract surgery actually had AMD before the cataract surgery. As suggested earlier,
52 we emphasize that when cataract surgery is indicated in an eye with both early and moderate to severe AMD, the surgeon should discuss the possibility of progression of AMD with the subject. As India has a large cataract burden, this problem should receive great attention for the timely detection and appropriate management of AMD.
Consistent with the existing literature, we did not find an association between AMD and education or BMI.
17 36 42 53 54 55 Our study results showed an inverse relationship between light alcohol consumption and prevalence of AMD. Given the small sample, it is difficult to make a definite inference, but the finding is similar to that in a previously published report.
56
The PAR% for associated risk factors varied between 10% and 14%, which suggests that eliminating these factors as a public health intervention may not be priority. However, even if this PAR% is relatively low, there are other potential individual and public health benefits that may accrue from not smoking. Modification of these risk factors assumes greater importance if viewed within the context of greater health benefits not necessarily limited to AMD. Primary care physicians who are made aware of these risk factors may play an important role in referring their patients to an ophthalmologist.
57 Unless we find preventable and/or modifiable risk factors, application of currently accepted clinical care, including laser treatment,
58 photodynamic therapy,
59 submacular surgery, and visual rehabilitation measures,
60 could help affected persons to live more independently until we discover a more effective therapy.
The strengths of this study are the representativeness of the sample population, the high response rate, and the standardized protocol, including photographic documentation. Limitations include the relatively few cases of AMD. This decreases the power of the study to identify all significant risk factors.
Supported by grants from the Christoffel-Blindenmission, Bensheim, Germany, and the Hyderabad Eye Research Foundation, Hyderabad, India.
Submitted for publication July 2, 2005; revised August 11, 2005; accepted October 5, 2005.
Disclosure:
S. Krishnaiah, None;
T. Das, None;
P.K. Nirmalan, None;
R. Nutheti, None;
B.R. Shamanna, None;
G.N. Rao, None;
R. Thomas, None
The publication costs of this article were defrayed in part by page charge payment. This article must therefore be marked “
advertisement” in accordance with 18 U.S.C. §1734 solely to indicate this fact.
Corresponding author: Sannapaneni Krishnaiah, L. V. Prasad Eye Institute, Banjara Hills, Hyderabad 500 034, India;
[email protected].
Table 1. Associations between Prevalence of AMD, Demographic Factors, and Vision Impairment in the Study Population
Table 1. Associations between Prevalence of AMD, Demographic Factors, and Vision Impairment in the Study Population
Characteristics | Total Population (N = 3723) | AMD n (%) | P |
Age | | | |
40–49 | 1424 | 13 (0.9) | <0.0001* |
50–59 | 1047 | 14 (1.3) | |
60–69 | 899 | 31 (3.4) | |
70+ | 353 | 13 (3.7) | |
Sex | | | |
Male | 1751 | 31 (1.8) | 0.632, † |
Female | 1972 | 40 (2.0) | |
Socioeconomic status, ‡ | | | |
Extreme lower | 417 | 4 (1.0) | 0.103* |
Lower | 1791 | 43 (2.4) | |
Middle | 1317 | 19 (1.4) | |
Upper | 145 | 2 (1.4) | |
Education | | | |
Illiterate | 2200 | 43 (2.0) | 0.903, † |
Literate | 1517 | 28 (1.8) | |
Place of residence | | | |
Urban | 934 | 19 (2.0) | 0.782, † |
Rural | 2789 | 52 (1.9) | |
Vision impairment | | | |
Normal | 2659 | 25 (0.9) | <0.0001* |
MVI | 818 | 36 (4.4) | |
Blind | 246 | 10 (4.1) | |
Table 2. Associations between Prevalence of AMD and Potential Risk Factors
Table 2. Associations between Prevalence of AMD and Potential Risk Factors
Characteristics | Total Population (N = 3723) | AMD n (%) | P |
High blood pressure | | | |
No | 1910 | 29 (1.5) | 0.150* |
Yes | 1813 | 41 (2.3) | |
Diabetes | | | |
No | 3528 | 70 (2.0) | 0.182* |
Yes | 194 | 1 (0.5) | |
Nuclear cataract | | | |
No | 2661 | 32 (1.2) | <0.0001* |
Yes | 895 | 29 (3.2) | |
Cortical cataract | | | |
No | 3022 | 39 (1.3) | <0.0001* |
Yes | 526 | 21 (4.0) | |
Posterior subcapsular cataract | | | |
No | 3002 | 46 (1.5) | 0.071* |
Yes | 548 | 15 (2.7) | |
Prior cataract surgery, † | | | |
No | 3447 | 50 (1.5) | <0.0001* |
Yes | 276 | 21 (7.6) | |
BMI | | | |
Normal | 1293 | 26 (2.0) | 0.078, ‡ |
Underweight | 1816 | 37 (2.0) | |
Overweight | 312 | — | |
Obese | 153 | 4 (2.6) | |
Cigarette smoking | | | |
Never a smoker | 3419 | 64 (1.9) | 0.866, ‡ |
Current smoker | 179 | 4 (2.2) | |
Prior smoker | 125 | 3 (2.4) | |
Cigar smoking | | | |
Never a smokers | 3224 | 53 (1.6) | 0.001, ‡ |
Current smoker | 362 | 10 (2.8) | |
Prior smoker | 137 | 8 (5.8) | |
Beedi smoking | | | |
Never a smoker | 3002 | 63 (2.1) | 0.214, ‡ |
Current smoker | 570 | 6 (1.1) | |
Prior smoker | 151 | 2 (1.3) | |
Hooka smoking | | | |
Never a smoker | 3720 | 71 (1.9) | 1.000* |
Prior smoker | 3 | — | |
More than one form of smoking | | | |
Never a smoker | 2347 | 42 (1.8) | 0.737, ‡ |
Only one type | 1259 | 26 (2.1) | |
More than one type | 117 | 3 (2.6) | |
Alcohol consumption, § | | | |
Never a drinker | 2658 | 61 (2.3) | 0.023, ‡ |
Light drinker | 805 | 8 (1.0) | |
Heavy drinker | 260 | 2 (0.8) | |
Table 3. Multivariable Logistic Regression Analyses for Associations between Potential Risk Factors and AMD (n = 3,723)
Table 3. Multivariable Logistic Regression Analyses for Associations between Potential Risk Factors and AMD (n = 3,723)
Characteristics | Total Population | AMD n (%) | Adjusted Odds Ratio (95% CI) | PAR* |
Age, † | | | | |
40–49 | 1424 | 13 (0.9) | 1.00 | |
50–59 | 1047 | 14 (1.3) | 2.04 (0.92–4.60) | — |
60–69 | 899 | 31 (3.4) | 4.38 (2.50–7.64) | — |
≥70 | 353 | 13 (3.7) | 3.29 (1.57–7.01) | — |
Vision impairment | | | | |
Normal | 2659 | 25 (0.9) | 1.00 | |
MVI | 818 | 36 (4.4) | 3.02 (1.68–5.41) | — |
Blind | 246 | 10 (4.1) | 2.89 (1.27–6.55) | — |
High blood pressure, † | | | | |
No | 1910 | 29 (1.5) | 1.00 | |
Yes | 1813 | 41 (2.3) | 1.25 (0.67–2.29) | 0.10 (0.0–0.31) |
Any cataract, ‡ | | | | |
No | 2271 | 22 (1.0) | 1.00 | |
Yes | 1442 | 49 (3.4) | 2.29 (1.24–4.29) | — |
Nuclear cataract, § | | | | |
No | 2661 | 32 (1.2) | 1.00 | |
Yes | 895 | 29 (3.2) | 1.58 (0.84–2.97) | — |
Cortical cataract, § | | | | |
No | 3022 | 39 (1.3) | 1.00 | |
Yes | 526 | 21 (4.0) | 2.87 (1.57–5.26) | — |
PSC cataract, § | | | | |
No | 3002 | 46 (1.5) | 1.00 | |
Yes | 548 | 15 (2.7) | 1.12 (0.58–2.19) | — |
Prior cataract surgery, ∥ | | | | |
No | 3447 | 50 (1.5) | 1.00 | |
Yes | 276 | 21 (7.6) | 3.79 (2.12–6.78) | — |
History of smoking | | | | |
Cigarette smoking | | | | |
Never a smoker | 3419 | 64 (1.9) | 1.00 | |
Current smoker | 179 | 4 (2.2) | 1.65 (0.55–5.01) | 0.03 (0.0–0.20) |
Prior smoker | 125 | 3 (2.4) | 1.17 (0.33–4.14) | 0.01 (0.0–0.12) |
Cumulative smoking dose, ¶ | | | | |
Light smoker | 58 | 2 (3.4) | 2.80 (0.59–13.26) | 0.03 (0.0–0.20) |
Heavy smoker | 246 | 5 (2.0) | 2.01 (0.54–5.01) | 0.06 (0.0–0.23) |
Cigar smoking | | | | |
Never a smoker | 3224 | 53 (1.6) | 1.00 | |
Current smoker | 362 | 10 (2.8) | 1.77 (0.84–3.74) | 0.07 (0.0–0.24) |
Prior smoker | 137 | 8 (5.8) | 3.29 (1.42–7.57) | 0.10 (0.01–0.24) |
Cumulative smoking dose, ¶ | | | | |
Light smoker | 83 | 2 (2.4) | 1.30 (0.29–5.77) | 0.01 (0.0–0.13) |
Heavy smoker | 416 | 16 (3.8) | 2.36 (1.17–4.71) | 0.14 (0.02–0.33) |
History of alcohol consumption, # | | | | |
Never a drinker | 2658 | 61 (2.3) | 1.00 | |
Light drinker | 805 | 8 (1.0) | 0.43 (0.21–0.92) | 0.14 (0.02–0.18) |
Heavy drinker | 260 | 2 (0.8) | 0.45 (0.11–1.81) | 0.04 (0.0–0.05) |
The authors thank all the APEDS team—in particular, Lalit and Rakhi Dandona and Catherine McCarty, who designed and conducted the detailed study; Vallam S. Rao for clinical inputs; and all the volunteers who participated.
CastenRJ, RovnerBW, TasmanW. Age-related macular degeneration and depression: a review of recent research. Curr Opin Ophthalmol. 2004;15:181–183.
[CrossRef] [PubMed]BresslerNM. Early detection and treatment of neovascular age-related macular degeneration. J Am Board Fam Pract. 2002;15:142–152.
[PubMed]NirmalanPK, KatzJ, RobinAL, et al. Prevalence of vitreoretinal disorders in a rural population of Southern India: The Aravind Comprehensive Eye Study. Arch Ophthalmol. 2004;122:581–586.
[CrossRef] [PubMed]HymanL, NeborskyR. Risk factors for age-related macular degeneration. Curr Opin Ophthalmol. 2003;13:171–175.
KleinR, KleinBE, WongTY, TomanySC, CruickshanksKJ. The association of cataract and cataract surgery with the long-term incidence of age-related maculopathy: The Beaver Dam Eye Study. Arch Ophthalmol. 2002;120:1551–1558.
[CrossRef] [PubMed]WangJJ, KleinR, SmithW, KleinBE, TomanyS, MitchellP. Cataract surgery and the 5-year incidence of late-stage age-related maculopathy: pooled findings from the Beaver Dam and Blue Mountains eye studies. Ophthalmology. 2003;110:1960–1967.
[CrossRef] [PubMed]DelcourtC, MichelF, ColvezA,for the POLA Study Groupet al. Associations of cardiovascular disease and its risk factors with age-related macular degeneration; the POLA study. Ophthalmic Epidemiol. 2001;8:237–249.
[CrossRef] [PubMed]SperdutoRD, HillerR. Systemic hypertension and age-related maculopathy in the Framingham Study. Arch Ophthalmol. 1986;104:216–219.
[CrossRef] [PubMed]KaunistoRMV, TerasirtaME, UusitupaMIJ, NiskanenLK. Age-related macular degeneration in newly diagnosed type 2 diabetic patients and control subjects: a 10-year follow-up on evaluation, risk factors, and prognostic significance. Diabetes Care. 2000;23:1672–1678.
[CrossRef] [PubMed]TomanySC, WangJJ, van LeeuwenR, et al. Risk factors for incident age-related macular degeneration: pooled findings from three continents. Ophthalmology. 2004;111:1280–1287.
[CrossRef] [PubMed]DelcourtC, DiazJL, Ponton-SanchezA, PapoL. Smoking and age-related macular degeneration. The POLA Study. [in French]Arch Ophthalmol. 1998;116:1031–1035.
[CrossRef] [PubMed]SmithW, MitechellP, LeedewrSR. Smoking and age-related maculopathy; the Blue Mountain Eye Study. Arch Ophthalmol. 1996;114:1518–1523.
[CrossRef] [PubMed]SeddonJM, WilletteWC, SpeizerFE, HankinsonSE. A prospective study of cigarette smoking and age-related macular degeneration in women. JAMA. 1996;276:1141–1146.
[CrossRef] [PubMed]Age Related Eye Disease Study Research Group. Risk factors associated with age-related macular degeneration: a case-control study in the Age-related Eye Disease Study Report Number 3. Ophthalmology. 2000;107:2224–2232.
[CrossRef] [PubMed]NorthridgeME. Annotation: public health methods: attributable risk as a link between causality and public health action. Am J Publ Health. 1995;85:1202–1204.
[CrossRef] RockhillB, NewmanB, WeinbergC. Use and misuse of population attributable fractions. Am J Publ Health. 1998;88:15–19.
[CrossRef] McCartyCA, MukeshBN, FuCL, et al. Risk factors for age-related maculopathy: the Visual Impairment Project. Arch Ophthalmol. 2001;119:1455–1462.
[CrossRef] [PubMed]DandonaL, DandonaR, SrinivasM, et al. Blindness in the Indian State of Andhra Pradesh. Invest Ophthalmol Vis Sci. 2001;42:908–916.
[PubMed]DandonaR, DandonaL, NaduvilathTJ, et al. Design of a population study of visually impairment in India: the Andhra Pradesh Eye Disease Study. Indian J Ophthalmol. 1997;45:251–257.
[PubMed]DandonaL, DandonaR, NaduvilathTJ, et al. Is eye-care-policy focus almost exclusively on cataract adequate to deal with blindness in India?. Lancet. 1998;2l:1312–1316.
FerrisFL, KassoffA, BresnickGH, et al. New visual acuity charts for clinical research. Am J Ophthalmol. 1982;94:91–96.
[CrossRef] [PubMed]ScheiHG. Width and pigmentation of the angle of the anterior chamber: a system of grading by gonioscopy. Arch Ophthalmol. 1957;58:510–512.
[CrossRef] Van HerickW, ShafferRN, SchwartzA. Estimation of width of angle of anterior chamber: incidence and significance of the narrow angle. Am J Ophthalmol. 1969;68:626–629.
[CrossRef] [PubMed]ChylackLT, WolfeJK, SingerDM, et al. The lens opacities classification system III. Arch Ophthalmol. 1993;111:831–836.
[CrossRef] [PubMed]TaylorHR, WestSK. A simple system for the clinical grading of lens opacities. Lens Res. 1988;5:175–181.
BirdAC, BresslerNM, BresslerSB, et al. An international classification and grading system for age-related maculopathy and age-related macular degeneration. The International ARM Epidemiological Study Group. Surv Ophthalmol. 1995;39:367–374.
[CrossRef] [PubMed]MaguireMG. Natural history of age-related macular degeneration.BergerJW FineSL MaguireMG eds. Age-Related Macular Degeneration. 1999;17–30.Mosby St. Louis.
HafronJ, MitraN, DalbagniG, et al. Does body mass index affect survival of patients undergoing radical or partial cystectomy for bladder cancer?. J Urol. 2005;173:1513–1517.
[CrossRef] [PubMed]NirmalanPK, KrishnadasR, RamakrishnanR, et al. Lens opacities in a rural population of southern India: The Aravind Comprehensive Eye Study. Invest Ophthalmol Vis Sci. 2003;44:4639–4643.
[CrossRef] [PubMed]DandonaR, DandonaL, SrinivasM, et al. Moderate visual impairment in India: the Andhra Pradesh Eye Disease Study. Br J Ophthalmol. 2002;86:373–377.
[CrossRef] [PubMed]RosnerB. Fundamentals of Biostatistics. 1986; 2nd ed. 84–92.PWS Publishers Boston.404–408
BennetS, WoodsT, LiyanageWM, et al. A simplified general method for cluster-sample surveys of health in developing countries. World Health Stat Q. 1991;44:98–106.
[PubMed]PearceN. Analytical implications of epidemiological concepts of interaction. Int J Epidemiol. 1989;18:976–980.
[CrossRef] [PubMed]VingerlingJR, DielemansI, HofmanA, et al. The prevalence of age-related maculopathy in the Rotterdam Study. Ophthalmology. 1995;102:205–210.
[CrossRef] [PubMed]MitchellP, SmithW, AtteboK, WangJJ. Prevalence of age-related maculopathy in Australia. The Blue Mountains Eye Study. Ophthalmology. 1995;102:1450–1460.
[CrossRef] [PubMed]KleinR, KleinBE, LintonKL. Prevalence of age-related maculopathy. The Beaver Dam Eye Study. Ophthalmology. 1992;99:933–943.
[CrossRef] [PubMed]BresslerNM, BresslerSB, WestSK, et al. The grading and prevalence of macular degeneration in Chesapeake Bay watermen. Arch Ophthalmol. 1989;107:847–852.
[CrossRef] [PubMed]LeibowitzHM, KruegerDE, MaunderLR, et al. The Framingham Eye Study monograph. Surv Ophthalmol. 1980;24:335–610.
[CrossRef] [PubMed]BellSF, DonofrioJ, WuJ, et al. Sociodemographic factors and age-related macular degeneration in Latinos: The Los Angeles Latino Eye Study. Am J Ophthalmol. 2005;139:30–38.
[CrossRef] [PubMed]FriedmanE. The role of the atherosclerotic process in the pathogenesis of age-related macular degeneration. Am J Ophthalmol. 2000;130:658–663.
[CrossRef] [PubMed]PauleikhoffD, ChenJC, ChisholmIH, BirdAC. Choroidal perfusion abnormality with age-related Bruch’s membrane change. Am J Ophthalmol. 1990;109:211–217.
[CrossRef] [PubMed]KahnHS, LeibowitzHM, GanleyJP, et al. The Framingham Eye Study, II: association of ophthalmic pathology with single variables previously measured in the Framingham Heart Study. Am J Epidemiol. 1997;106:33–41.
DelaneyWV, Jr, OatesRP. Senile macular degeneration: a preliminary study. Ann Ophthalmol. 1982;14:21–24.
[PubMed]KornzweigAL. Changes in the choriocapillaris associated with senile macular degeneration. Ann Ophthalmol. 1977;9:753–756.
[PubMed]KleinR, KleinBE, TomanySC, CruickshanksKJ. The association of cardiovascular disease with the long-term incidence of age-related maculopathy: The Beaver Dam Eye study. Ophthalmology. 2003;110:1273–1280.
[CrossRef] [PubMed]KleinR, KleinBE, FrankeT. The relationship of cardiovascular disease and its risk factors to age-related maculopathy: The Beaver Dam Eye study. Ophthalmology. 1993;100:406–414.
[CrossRef] [PubMed]KleinR, KleinBEK, JensenSC, CruickshanksKJ. The relationship of ocular factors to the incidence and progression of age-related maculopathy. Arch Ophthalmol. 1998;116:506–513.
[CrossRef] [PubMed]KleinR, KleinBEK, WangQ, et al. Is age-related maculopathy associated with cataracts?. Arch Ophthalmol. 1994;112:191–196.
[CrossRef] [PubMed]SperdutoRD, HillerR, SeigelD. Lens opacities and senile maculopathy. Arch Ophthalmol. 1981;99:1004–1008.
[CrossRef] [PubMed]ChaineG, HulloA, SahelJ, et al. Case-control study of the risk factors for age-related macular degeneration. Br J Ophthalmol. 1998;82:996–1002.
[CrossRef] [PubMed]WangJJ, MitchellPG, CummingRG, LimR. Cataract and age-related maculopathy: the Blue Mountains Eye Study. Ophthalmic Epidemiol. 1999;6:317–326.
[CrossRef] [PubMed]KleinR, PetoT, BirdA, VannewkirkMR. The Epidemiology of age-related macular degeneration. Am J Ophthalmol. 2004;137:486–495.
[CrossRef] [PubMed]HymanLG, LilienfeldAM, FerrisFL, 3rd, FineSL. Senile macular degeneration: a case-control study. Am J Epidemiol. 1983;118:213–227.
[PubMed]KleinR. Epidemiology.BergerJW FineSL MaguireMG eds. Age-Related Macular Degeneration. 1998;31–55.Mosby St. Louis.
KleinR, KleinBEK, JensenSC, et al. Age-related maculopathy in a multiracial United States population. The National Health and Nutrition Examination Survey. Ophthalmology. 1999;106:1056–1065.
[CrossRef] [PubMed]ObisesanTO, HirschR, KosokoO, CarlsonL, ParrottM. Moderate wine consumption is associated with decreased odds of developing age-related macular degeneration in NHANES-1. J Am Geriatr Soc. 1998;46:1–7.
[CrossRef] [PubMed]BresslerNM. Early detection and treatment of neovascular age-related macular degeneration. J Am Board Fam Pract. 2002;15:142–152.
[PubMed]Macular Photocoagulation. Study Group. Argon laser photocoagulation for neovascular maculopathy: five year results from randomized clinical trails. Arch Ophthalmol. 1991;109:1109–1114.
[CrossRef] [PubMed]Treatment of Age-Related Macular Degeneration with Photodynamic Therapy (TAP) Study group. Photodynamic Therapy of choroidal neovascularization in age-related macular degeneration with verteporfin: one year results of two randomized clinical trials. TAP report 1. Arch Ophthalmol. 1999;117:1329–1345.
[CrossRef] [PubMed]KhanSAK, DasT, KumarSM, NuthetiR. Low vision rehabilitation in patients with age-related macular degeneration at a tertiary eye care center in southern India. Clin Exp Ophthalmol. 2002;30:404–410.
[CrossRef]