[Skip to Content]
Access to paid content on this site is currently suspended due to excessive activity being detected from your IP address 18.204.227.250. Please contact the publisher to request reinstatement.
[Skip to Content Landing]
Figure 1.
Age Distribution of Study Participants
Age Distribution of Study Participants
Figure 2.
Adjusted Prevalence of Unilateral and Bilateral Age-Related Macular Degeneration (AMD) by Age and Indigenous Status
Adjusted Prevalence of Unilateral and Bilateral Age-Related Macular Degeneration (AMD) by Age and Indigenous Status

Prevalence was adjusted for sex, ethnicity, educational attainment, language spoken at home, remoteness, history of cataract surgery, history of diabetes, and history of stroke.

Table 1.  
Weighted Prevalence of AMD by Severity, Indigenous Status, Age, and Sex
Weighted Prevalence of AMD by Severity, Indigenous Status, Age, and Sex
Table 2.  
Weighted Prevalence of Any Soft Drusen and Any Pigment Abnormalities by Indigenous Status, Age, and Sex
Weighted Prevalence of Any Soft Drusen and Any Pigment Abnormalities by Indigenous Status, Age, and Sex
Table 3.  
Sampling Weight-Adjusted Multivariable Multinomial Logistic Regression Examining Associations Between AMD Severity and Related Factors, Stratified by Indigenous Status
Sampling Weight-Adjusted Multivariable Multinomial Logistic Regression Examining Associations Between AMD Severity and Related Factors, Stratified by Indigenous Status
1.
VanNewkirk  MR, Weih  L, McCarty  CA, Taylor  HR.  Cause-specific prevalence of bilateral visual impairment in Victoria, Australia: the Visual Impairment Project.  Ophthalmology. 2001;108(5):960-967.PubMedGoogle ScholarCrossref
2.
Wang  JJ, Foran  S, Mitchell  P.  Age-specific prevalence and causes of bilateral and unilateral visual impairment in older Australians: the Blue Mountains Eye Study.  Clin Exp Ophthalmol. 2000;28(4):268-273.PubMedGoogle ScholarCrossref
3.
Congdon  N, O’Colmain  B, Klaver  CC,  et al; Eye Diseases Prevalence Research Group.  Causes and prevalence of visual impairment among adults in the United States.  Arch Ophthalmol. 2004;122(4):477-485.PubMedGoogle ScholarCrossref
4.
Pascolini  D, Mariotti  SP, Pokharel  GP,  et al.  2002 Global update of available data on visual impairment: a compilation of population-based prevalence studies.  Ophthalmic Epidemiol. 2004;11(2):67-115.PubMedGoogle ScholarCrossref
5.
Australian Government Department of Health.  Implementation Plan Under the National Framework for Action to Promote Eye Health and Prevent Avoidable Blindness and Vision Loss. Canberra, Australia: Communications Branch, Dept of Health; 2014.
6.
Cahill  MT, Banks  AD, Stinnett  SS, Toth  CA.  Vision-related quality of life in patients with bilateral severe age-related macular degeneration.  Ophthalmology. 2005;112(1):152-158.PubMedGoogle ScholarCrossref
7.
Hassell  JB, Lamoureux  EL, Keeffe  JE.  Impact of age related macular degeneration on quality of life.  Br J Ophthalmol. 2006;90(5):593-596.PubMedGoogle ScholarCrossref
8.
Mitchell  P.  Eyes on the Future: A Clear Outlook on Age-Related Macular Degeneration. Sydney, Australia: Deloitte Access Economics; 2011:1-146.
9.
Wong  WL, Su  X, Li  X,  et al.  Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: a systematic review and meta-analysis.  Lancet Glob Health. 2014;2(2):e106-e116.PubMedGoogle ScholarCrossref
10.
VanNewkirk  MR, Nanjan  MB, Wang  JJ, Mitchell  P, Taylor  HR, McCarty  CA.  The prevalence of age-related maculopathy: the visual impairment project.  Ophthalmology. 2000;107(8):1593-1600.PubMedGoogle ScholarCrossref
11.
Mitchell  P, Smith  W, Attebo  K, Wang  JJ.  Prevalence of age-related maculopathy in Australia: the Blue Mountains Eye Study.  Ophthalmology. 1995;102(10):1450-1460.PubMedGoogle ScholarCrossref
12.
Australian Bureau of Statistics. Australian Social Trends: Life-Expectancy Trends. http://www.ausstats.abs.gov.au/ausstats/subscriber.nsf/LookupAttach/4102.0Publication23.03.112/$File/41020_Lifeexpectancy_Mar2011.pdf2011. Accessed March 23, 2017.
13.
Landers  J, Henderson  T, Craig  J.  The prevalence and causes of visual impairment in indigenous Australians within central Australia: the Central Australian Ocular Health Study.  Br J Ophthalmol. 2010;94(9):1140-1144.PubMedGoogle ScholarCrossref
14.
Taylor  HR, Xie  J, Fox  S, Dunn  RA, Arnold  AL, Keeffe  JE.  The prevalence and causes of vision loss in Indigenous Australians: the National Indigenous Eye Health Survey.  Med J Aust. 2010;192(6):312-318.PubMedGoogle Scholar
15.
Australian Institute of Health and Welfare.  Vision Problems Among Older Australians. Canberra: Australian Institute of Health and Welfare; 2005.
16.
Foreman  J, Keel  S, Dunn  R, van Wijngaarden  P, Taylor  HR, Dirani  M.  Sampling methodology and site selection in the National Eye Health Survey: an Australian population-based prevalence study.  Clin Exp Ophthalmol. 2017;45(4):336-347.PubMedGoogle ScholarCrossref
17.
Foreman  J, Keel  S, van Wijngaarden  P, Taylor  HR, Dirani  M.  Recruitment and testing protocol in the National Eye Health Survey: a population-based eye study in Australia.  Ophthalmic Epidemiol. 2017:1-11.PubMedGoogle Scholar
18.
World Medical Association.  World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects.  JAMA. 2013;310(20):2191-2194. doi:10.1001/jama.2013.281053PubMedGoogle ScholarCrossref
19.
Bird  AC, Bressler  NM, Bressler  SB,  et al; The International ARM Epidemiological Study Group.  An international classification and grading system for age-related maculopathy and age-related macular degeneration.  Surv Ophthalmol. 1995;39(5):367-374.PubMedGoogle ScholarCrossref
20.
Ferris  FL  III, Wilkinson  CP, Bird  A,  et al; Beckman Initiative for Macular Research Classification Committee.  Clinical classification of age-related macular degeneration.  Ophthalmology. 2013;120(4):844-851.PubMedGoogle ScholarCrossref
21.
Kawasaki  R, Wang  JJ, Aung  T,  et al; Singapore Malay Eye Study Group.  Prevalence of age-related macular degeneration in a Malay population: the Singapore Malay Eye Study.  Ophthalmology. 2008;115(10):1735-1741.PubMedGoogle ScholarCrossref
22.
Varma  R, Fraser-Bell  S, Tan  S, Klein  R, Azen  SP; Los Angeles Latino Eye Study Group.  Prevalence of age-related macular degeneration in Latinos: the Los Angeles Latino eye study.  Ophthalmology. 2004;111(7):1288-1297.PubMedGoogle ScholarCrossref
23.
Smith  W, Assink  J, Klein  R,  et al.  Risk factors for age-related macular degeneration: pooled findings from three continents.  Ophthalmology. 2001;108(4):697-704.PubMedGoogle ScholarCrossref
24.
Australian Institute of Health and Welfare.  2010 National Drug Strategy Household Survey: Survey Report. Canberra: Australian Institute of Health and Welfare; 2010.
25.
Jonasson  F, Arnarsson  A, Sasaki  H, Peto  T, Sasaki  K, Bird  AC.  The prevalence of age-related maculopathy in Iceland: Reykjavik eye study.  Arch Ophthalmol. 2003;121(3):379-385.PubMedGoogle ScholarCrossref
26.
Klein  R, Klein  BE, Linton  KL.  Prevalence of age-related maculopathy: the Beaver Dam Eye Study.  Ophthalmology. 1992;99(6):933-943.PubMedGoogle ScholarCrossref
27.
Vingerling  JR, Dielemans  I, Hofman  A,  et al.  The prevalence of age-related maculopathy in the Rotterdam Study.  Ophthalmology. 1995;102(2):205-210.PubMedGoogle ScholarCrossref
28.
Bressler  SB, Muñoz  B, Solomon  SD, West  SK; Salisbury Eye Evaluation (SEE) Study Team.  Racial differences in the prevalence of age-related macular degeneration: the Salisbury Eye Evaluation (SEE) Project.  Arch Ophthalmol. 2008;126(2):241-245.PubMedGoogle ScholarCrossref
29.
Klein  R, Klein  BE, Jensen  SC, Mares-Perlman  JA, Cruickshanks  KJ, Palta  M.  Age-related maculopathy in a multiracial United States population: the National Health and Nutrition Examination Survey III.  Ophthalmology. 1999;106(6):1056-1065.PubMedGoogle ScholarCrossref
30.
Klein  R, Klein  BE, Knudtson  MD,  et al.  Prevalence of age-related macular degeneration in 4 racial/ethnic groups in the multi-ethnic study of atherosclerosis.  Ophthalmology. 2006;113(3):373-380.PubMedGoogle ScholarCrossref
31.
Jampol  LM, Tielsch  J.  Race, macular degeneration, and the Macular Photocoagulation Study.  Arch Ophthalmol. 1992;110(12):1699-1700.PubMedGoogle ScholarCrossref
32.
Leveziel  N, Puche  N, Zerbib  J,  et al.  Genetic factors associated with age-related macular degeneration [in French].  Med Sci (Paris). 2010;26(5):509-515.PubMedGoogle ScholarCrossref
33.
Australian Institute of Health and Welfare.  Mortality and Life Expectancy of Indigenous Australians. Canberra: Australian Institute of Health and Welfare; 2014.
34.
Age-Related Eye Disease Study Research Group.  A randomized, placebo-controlled, clinical trial of high-dose supplementation with vitamins C and E, beta carotene, and zinc for age-related macular degeneration and vision loss: AREDS report no. 8.  Arch Ophthalmol. 2001;119(10):1417-1436.PubMedGoogle ScholarCrossref
35.
Avery  RL, Pieramici  DJ, Rabena  MD, Castellarin  AA, Nasir  MA, Giust  MJ.  Intravitreal bevacizumab (Avastin) for neovascular age-related macular degeneration.  Ophthalmology. 2006;113(3):363-372.e5.PubMedGoogle ScholarCrossref
36.
Ferrara  N, Damico  L, Shams  N, Lowman  H, Kim  R.  Development of ranibizumab, an anti-vascular endothelial growth factor antigen binding fragment, as therapy for neovascular age-related macular degeneration.  Retina. 2006;26(8):859-870.PubMedGoogle ScholarCrossref
37.
Regillo  CD, Busbee  BG, Ho  AC, Ding  B, Haskova  Z.  Baseline predictors of 12-month treatment response to ranibizumab in patients with wet age-related macular degeneration.  Am J Ophthalmol. 2015;160(5):1014-1023.e2.PubMedGoogle ScholarCrossref
38.
Gupta  OP, Brown  GC, Brown  MM.  Age-related macular degeneration: the costs to society and the patient.  Curr Opin Ophthalmol. 2007;18(3):201-205.PubMedGoogle ScholarCrossref
Original Investigation
November 2017

Prevalence of Age-Related Macular Degeneration in Australia: The Australian National Eye Health Survey

Author Affiliations
  • 1Centre for Eye Research Australia, Royal Victorian Eye & Ear Hospital, Melbourne, Australia
  • 2Department of Surgery, University of Melbourne, Melbourne, Australia
  • 3Indigenous Eye Health Unit, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
JAMA Ophthalmol. 2017;135(11):1242-1249. doi:10.1001/jamaophthalmol.2017.4182
Key Points

Question  What is the prevalence of age-related macular degeneration in Australian adults?

Findings  In this population-based national sample of 3098 nonindigenous and 1738 indigenous Australian adults, the prevalence of late age-related macular degeneration was 0.96% in nonindigenous and 0.17% in indigenous Australians. Age-related macular degeneration was attributed as the main cause of vision loss in 11.1% of nonindigenous and 1.1% of indigenous Australians.

Meaning  Age-related macular degeneration remains a prominent cause of vision loss in the nonindigenous Australian population; an increased provision of low vision rehabilitation services may be required to cope with the projected increase in age-related macular degeneration in Australia.

Abstract

Importance  Age-related macular degeneration (AMD) is a leading cause of irreversible blindness among the elderly population globally. Currently, knowledge of the epidemiology of AMD in Australia remains scarce because of a paucity of recent population-based data.

Objective  To examine the prevalence of AMD in Australia.

Design, Setting, and Participants  In this population-based, cross-sectional survey performed from March 11, 2015, to April 18, 2016, a sample of 3098 nonindigenous Australians 50 years and older and 1738 indigenous Australians 40 years and older from 30 geographic areas across Australia were examined.

Main Outcomes and Measures  Any AMD, early AMD, intermediate AMD, and late AMD graded according to the Beckman clinical classification system.

Results  A total of 4836 individuals were examined, including 3098 nonindigenous Australian (64.1%; 58.9% female vs 41.1% male; age range, 40-92 years; mean [SD] age, 55.0 [10.0] years) and 1738 indigenous Australians (35.9%; 53.6% female vs 46.4% male; age range, 50-98 years; mean [SD] age, 66.6 [9.7] years). A total of 4589 (94.9%, 2946 nonindigenous and 1643 indigenous) participants had retinal photographs in at least 1 eye that were gradable for AMD. The weighted prevalence of early AMD was 14.8% (95% CI, 11.7%-18.6%) and of intermediate AMD was 10.5% (95% CI, 8.3%-13.1%) among nonindigenous Australians. In indigenous Australians, the weighted prevalence of early AMD was 13.8% (95% CI, 9.7%-19.3%) and of intermediate AMD was 5.7% (96% CI, 4.7%-7.0%). Late AMD was found in 0.96% (95% CI, 0.59%-1.55%) of nonindigenous participants (atrophic, 0.72%; neovascular, 0.24%). The prevalence of late AMD increased to 6.7% in participants 80 years or older and was higher in men (1.4% vs 0.61%, P = .02). Only 3 (0.17% [95% CI, 0.04%-0.63%]) indigenous participants had late (atrophic) AMD. Age-related macular degeneration was attributed as the main cause of vision loss (<6/12 in the better eye) in 23 of 208 nonindigenous Australians (11.1%) and 2 of 183 indigenous Australians (1.1%).

Conclusions and Relevance  In line with data from other white populations, AMD is a prominent cause of vision loss in the nonindigenous Australian population. An increased provision of low vision rehabilitation services may be required to cope with the projected increase in AMD in Australia.

Introduction

Age-related macular degeneration (AMD) is a leading cause of irreversible blindness among the elderly population in Australia1,2 and other Western nations.3,4 The incidence of AMD is projected to increase with the aging of the population.5 Studies have established that AMD severely affects quality of life6,7 and poses a significant financial burden, with estimated annual direct costs in Australia of $750 million.8 Despite this, knowledge of the epidemiology of AMD in Australia remains scarce because of a paucity of recent national population-based data. This information is vital for effective policy formulation and planning for eye health care delivery in Australia.

A recent meta-analysis9 of 39 population-based studies from around the world reported the pooled AMD prevalence (age range, 45-85 years) to be 0.37%. In Australia, 2 landmark, regional population-based cohort studies conducted in the early 1990s, the Melbourne Visual Impairment Project (VIP) (individuals ≥40 years of age)10 and the Blue Mountains Eye Study (BMES) (individuals ≥49 years of age),11 reported the prevalence of late AMD to be 0.68% (VIP) and 1.9% (BMES). Although these studies10,11 provided excellent insights into the burden of AMD in Australia, since their completion, there have been substantial demographic changes, including a marked increase in life expectancy and population growth.12 There has been no national estimate of AMD in indigenous Australians. However, the National indigenous Eye Health Survey and the Central Australian Ocular Health Study reported that AMD is an uncommon cause of low vision in indigenous adults 40 years or older.13,14 Age-related macular degeneration was attributed as the main cause of vision loss in only 2% of cases in the National indigenous Eye Health Survey, whereas it was not the main cause of vision loss in any study participant in the Central Australian Ocular Health Study. The purpose of the present study was to examine the prevalence of AMD among nonindigenous and indigenous Australian adults in the National Eye Health Survey (NEHS).

Methods
Study Population

The NEHS is a nationwide, population-based survey conducted from March 11, 2015, to April 18, 2016, that investigated the prevalence and causes of vision impairment (<6/12 to ≥6/60 in the better eye) and blindness (<6/60 in the better eye) among nonindigenous Australians 50 years and older and indigenous Australians 40 years and older. The younger age criterion for indigenous participants was chosen because of the earlier onset and more rapid progression of common eye diseases and diabetes in indigenous Australians.15 The sampling and testing methods have been described in detail elsewhere.16,17 In brief, using multistage cluster sampling, we recruited participants door to door from 30 geographic areas across 5 Australian states and 1 territory, stratified by remoteness. Selection of sites used 2011 census data collected by the Australian Bureau of Statistics. High overall positive response rates (83.5%) and examination rates (71.5%) were achieved. Ethics approval was obtained from the Royal Victorian Eye and Ear Hospital Human Research Ethics Committee. Additional ethical approvals were obtained at the state level by the Aboriginal Health and Medical Research Council of New South Wales, the Menzies School of Health Research, the Aboriginal Health Council of Western Australia, and the Aboriginal Health Council of South Australia. Study procedures adhered to the tenets of the Declaration of Helsinki18 as revised in 2013, and participants provided written informed consent to participate.

Interview and Examination Procedures

An interviewer-administered questionnaire was used to collect information on sociodemographic factors, ocular and medical histories, and previous use of eye health services. Participants underwent presenting distance visual acuity assessment using the logMAR chart, and automated refraction was performed (Nidek ARK-30 Type-R handheld auto-refractor/keratometer, Nidek Co Ltd) on participants with vision loss of less than 6/12 that improved to 6/12 or greater with pinhole. Two standard, 45°, nonstereoscopic color retinal photographs were taken of each eye, one centered on the optic disc (field 1) and the other centered on the macula (field 2), using a Diabetic Retinopathy Screening nonmydriatic fundus camera (CenterVue SpA). Pupillary dilation was conducted when retinal images were of reduced quality because of small pupil size. A single experienced grader graded each image masked to the identity and clinical characteristics of study participants. Any uncertain cases were adjudicated by the study ophthalmologist.

Grading and Classification of AMD

Retinal images were deemed to be gradable for AMD if field 2 was present and two-thirds of the macular area was visible. A transparent grid was placed over field 2 of each eye and centered on the fovea.19 The grid included 3 concentric circles with radii of 500, 1500, and 3000 μm and had 4 radial lines that divided the retinal image into superior, inferior, nasal, and temporal quadrants. Any AMD lesions outside the margins of this grid were excluded from analysis. Age-related macular degeneration was graded according to the Beckman classification system as early, intermediate, or late AMD.20 In brief, early AMD was defined as the presence of medium drusen 63 to 125 μm in diameter. Intermediate AMD was characterized by large drusen greater than 125 μm in diameter and/or definite AMD pigmentary abnormalities, defined as any definite hyperpigmentary or hypopigmentary abnormalities associated with medium or large drusen but not associated with known disease entities. Late AMD was defined as neovascular AMD or atrophic AMD. Neovascular AMD consisted of retinal pigment epithelium detachment or intraretinal, subretinal, or sub–retinal pigment epithelium hemorrhages or subretinal fibrous scars. Atrophic AMD was defined as the presence of visible choroidal vessels and a central zone of retinal pigment epithelium atrophy 175 μm or larger in diameter. The AMD grade was assigned on the basis of the worse of the 2 eyes. If an eye was ungradable, the grade for the fellow eye was assigned. Two independent ophthalmologists reviewed relevant questionnaire and clinical data to determine the main cause of vision impairment or blindness. For cases in which a single primary cause was not identifiable, vision loss was attributed to combined mechanisms. Any disagreements were adjudicated by a third senior ophthalmologist.

Statistical Analysis

Data were weighted by calculating sample weights for all records using the probability of selection at each stage of sampling. The 95% CIs, taking into account the sampling design, were calculated for the prevalence of AMD.

Univariate and multivariable multinomial logistic regression models were used to examine the associations between AMD severity (no AMD, early AMD, intermediate AMD, and late AMD) and key explanatory variables. Lack of multicollinearity between the independent variables in the model was verified. Statistical interaction was tested for all predictors of AMD in the final model. A plot of the residuals compared with estimates was examined to determine whether the assumptions of linearity and homoscedasticity were met. NLCHECK (Stata module) was used to check linearity assumption after model estimation. Adjusted proportions were calculated by logistic regression models, taking into account covariates and the sampling weight.

All analyses were performed by incorporating the sampling weights and nonresponse rate to obtain unbiased estimates from the complex NEHS sampling design. Analyses were conducted with Stata, version 14.2.0 (StataCorp). A 2-tailed P < .05 was considered to be statistically significant.

Results

A total of 4836 individuals were examined in the NEHS, including 3098 nonindigenous Australians (64.1%; 58.9% female vs 41.1% male; age range, 40-92 years; mean [SD] age, 55.0 [10.0] years) and 1738 indigenous Australians (35.9%; 53.6% female vs 46.4% male; age range, 50-98 years; mean [SD] age, 66.6 [9.7] years). Of these, 4589 participants (94.9%, 2946 nonindigenous and 1643 indigenous) had retinal photographs in at least 1 eye that were gradable for AMD (396 gradable images in only 1 eye [8.6%]). Nonindigenous participants with missing or ungradable images were significantly older (mean [SD], 72.2 [9.9] years) than those with gradable images (mean [SD], 66.3 [9.6] years; P < .001). This was also the case for indigenous participants (mean [SD] age, 62.0 [11.6] years for those with ungradable images vs 54.6 [9.7] years for those with gradable images; P < .001). Of the total nonindigenous population with gradable retinal images for AMD, 1364 (46.3%) were male and 2121 (72.0%) identified as Oceanian. Of the indigenous participants with gradable retinal images for AMD, 274 (41.0%) were male. The age profiles of the nonindigenous and indigenous samples are presented in Figure 1.

Prevalence of AMD by Indigenous Status

The weighted prevalence among nonindigenous Australians 50 years and older was 14.8% (95% CI, 11.7%-18.6%) for early AMD and 10.5% (95% CI, 8.3%-13.1%) for intermediate AMD (Table 1). The prevalence of individual AMD lesions, including soft drusen and pigment abnormalities, is given in Table 2. Late AMD was found in 0.96% (95% CI, 0.59%-1.55%) of nonindigenous Australian adults, with atrophic AMD observed in 0.72% (95% CI, 0.41%-1.24%) and neovascular AMD in 0.24% (95% CI, 0.13%-0.47%). The weighted prevalence of late AMD increased with age in nonindigenous participants, with the following age-specific prevalences: 0.13% among those 69 years or older, 0.83% among those aged 70 to 79 years, and 6.7% among those 80 years or older (P < .001). Among nonindigenous Australians 50 years and older, the prevalence of late AMD was 1.4% for men and 0.61% for women (P = .02).

Among indigenous Australians 40 years and older, the weighted prevalence was 13.8% (95% CI, 9.7%-19.3%) for early AMD and 5.7% (95% CI, 4.7%-7.0%) for intermediate AMD. The prevalence of intermediate AMD was 4.4% among those 50 through 59 years of age, 9.4% among those 60 through 69 years of age, and 16.7% among those 70 years or older (P = .001). Late AMD was present in only 3 individuals (0.17%; 95% CI, 0.04%-0.63%), with all cases being atrophic AMD. To allow for more robust comparisons with the nonindigenous population, the weighted prevalence of AMD in the indigenous population was recalculated after excluding all participants younger than 50 years. In indigenous Australians 50 years or older, the prevalence was 15.9% (95% CI, 11.4%-21.8%) for early AMD, 7.6% (95% CI, 6.0%-9.5%) for intermediate AMD, and 0.26% (95% CI, 0.07%-1.0%) for late AMD.

Associations of Early, Intermediate, and Late AMD

Logistic regression analysis that examined associations between known and potential risk factors of AMD was stratified by indigenous status (Table 3). In the nonindigenous population, univariate multinominal logistic regression analysis revealed that older age (relative risk ratio [RRR], 9.03 per 10 years [95% CI, 5.16-15.79 per 10 years]; P < .001), male sex (RRR, 2.21 [95% CI, 1.18-4.16]; P = .02), European ethnicity (RRR, 1.78 [95% CI, 1.48-2.14]; P < .001), and residing in very remote geographic areas (RRR, 1.80 [95% CI, 1.17-2.73]; P = .01) were associated with the presence of AMD. After known and potential covariates were adjusted for, the weighted prevalence of early, intermediate, and late AMD remained related to age. Furthermore, European ethnicity remained a risk factor for early AMD, and an ethnicity other than Oceanian or European remained associated with intermediate AMD.

Logistic regression analysis was restricted to early and intermediate AMD for the indigenous population. In univariate analysis, older age (RRR, 2.17 per 10 years [95% CI, 1.63-2.87 per 10 years]; P ≤ .001), male sex (RRR, 1.79 [95% CI, 1.14-2.83]; P = .01), lower educational attainment (RRR, 0.28 [95% CI, 0.12-0.63]; P = .004), and self-reported stroke (RRR, 3.93 [95% CI, 2.61-5.92]; P ≤ .001) were associated with the presence of AMD. After adjustments, self-reported stroke remained a risk factor for intermediate AMD and the weighted prevalence of early and intermediate AMD remained associated with age.

Vision Loss and AMD

In the nonindigenous population, AMD was attributed as the main cause of vision impairment (<6/12 to ≥6/60 in the better eye) in 18 of 201 individuals (9%) and was the leading cause of blindness (<6/60 in the better eye) (5 of 7 individuals [71.4%]). In the indigenous population, AMD was attributed as the main cause of vision impairment in only 2 of 183 individuals (1.1%) and was not the main cause of blindness in any indigenous participant.

Bilaterality of AMD

Bilateral AMD signs were found in 489 of 1141 individuals with AMD (42.9%). Among these individuals, bilateral early AMD was found in 203 of 698 (29.5%) and bilateral intermediate AMD in 254 of 416 (61.1%). Of the 36 individuals with late AMD, 17 had bilateral late AMD, 15 had early or intermediate AMD in the fellow eye, and the remaining 4 had no signs of AMD in the other eye. The prevalence of bilateral AMD increased with age in the nonindigenous and indigenous participants (Figure 2).

Utilization of Eye Care Services in Participants With AMD

Among nonindigenous participants with AMD, 274 of 474 (57.8%) of those with early AMD, 218 of 319 (68.3%) of those with intermediate AMD, and 24 of 33 (72.7%) of those with late AMD had accessed an optometry or ophthalmology service in the past 12 months (self-report). Among the indigenous population with AMD, 105 of 215 (48.8%) with early AMD, 47 of 97 (48.5%) with intermediate AMD, and 1 of 3 (33.3%) with late AMD had consulted with an optometrist or ophthalmologist in the previous 12 months (self-report).

Discussion

This article presents the age-specific prevalence of early, intermediate, and late AMD in indigenous and nonindigenous Australian adults. We report the prevalence of late AMD among nonindigenous Australians (age range, 50-98 years) to be 0.96% and among indigenous Australians (age range, 40-92 years) to be 0.17%. Of importance, AMD was attributed as the main cause of bilateral blindness in approximately 70% of cases in the nonindigenous population.

The overall prevalence of late AMD among nonindigenous participants was 0.96%, increasing 8-fold from 0.83% among those 70 to 79 years of age to 6.7% among those 80 years or older. A comparison of age-specific rates revealed that the prevalence of late AMD among nonindigenous participants was marginally higher than that reported in a recent global meta-analysis9 of 39 population-based studies in the age category of 80 to 85 years (4.0% in the NEHS vs 3.3% globally). In the Australian setting, we were able to compare the age-standardized prevalence of late AMD in our study with that reported in the Melbourne VIP. After age standardization, the prevalence of late AMD among nonindigenous participants in the present study (1.2%) was comparable to that reported in the Melbourne VIP (1.5%). Unlike the Melbourne VIP and BMES, a higher prevalence of late AMD was observed among male individuals. This finding is consistent with the Singapore Malay Eye Study21 and the Los Angeles Latino Eye Study.22 Given the well-recognized association between AMD and smoking,23 this finding may reflect the higher smoking prevalence among men than women in Australia.24

The ratio of atrophic to neovascular AMD is important to eye health service delivery because current therapy is available for only the neovascular form. Of interest, similar to findings from the Reykjavik Eye Study,25 we report the ratio for atrophic vs neovascular AMD to be approximately 3:1. This finding is not consistent with findings from the Beaver Dam Eye Study,26 the Rotterdam Eye Study,27 and the BMES,11 which reported that the ratio of neovascular type vs atrophic AMD was approximately 2:1. Additional studies are needed to elucidate this finding because of the small number of nonindigenous Australians with late AMD (n = 33) in the present study.

To enable more direct comparisons with the Melbourne VIP, the prevalence of early AMD was recalculated according to a synchronized definition in which early AMD included medium (63- to 125-μm) or large (>125-μm) drusen and/or associated hyperpigmentary or hypopigmentary abnormalities. After age standardization, we noted a higher prevalence of early AMD than in the Melbourne VIP participants among individuals 50 years and older (19.3% in VIP vs 26.1% in the NEHS). Extrapolating these findings to the current Australian population using 2011 census data, we estimated the number of nonindigenous Australian citizens 50 years and older to be 1.4 million with early AMD and 53 960 with late AMD.

This is the first population-based study, to our knowledge, to report the national prevalence of AMD among indigenous Australians. The finding of a low rate of late AMD among indigenous participants (0.17%) is consistent with previous Australian studies13,14 that have reported that AMD is an uncommon cause of vision loss in indigenous adults. This finding is also consistent with earlier studies28-30 from the United States that report low frequencies of AMD among African American and Latino individuals. It has been hypothesized that individuals with higher levels of retinal pigmentation may be at a lower risk of end-stage disease because of the protective effects of melanin from oxidative damage.31 Furthermore, genetic factors32 and the lower life expectancy of indigenous Australians (on average, indigenous persons live 10 years less than nonindigenous persons)33 are also likely to contribute to the low prevalence of late AMD in this cohort.

Nearly all late AMD cases (32 of 36 [88.9%]) were bilateral, and when compared with the Melbourne VIP, AMD was attributed as the main cause of bilateral vision loss (<6/12 in the better eye) in a similar proportion of nonindigenous participants (10% in VIP vs 11% in the NEHS). Even with the advancements in therapies for AMD during the past 2 decades,34-36 AMD remains a prominent cause of significant vision loss in the elderly Australian population. Because AMD lesions associated with intermediate AMD indicate an increased risk of developing vision-threatening late-stage disease,20 our finding that 30% of nonindigenous and 50% of indigenous Australians with intermediate AMD had not accessed an optometry or ophthalmology service in the past 12 months is noteworthy. This finding may highlight that increased public education on the importance of having regular eye examinations is warranted, because presenting visual acuity is a strong predictor of outcome for anti–vascular endothelial growth factor treatment in neovascular AMD37 and particularly if new preventive treatments that target intermediate disease become available.38

Strengths and Limitations

The strengths of this study include its study and sampling design, large sample size, and stratification by indigenous status. A number of limitations must also be considered. First, there was a relatively small representation of the oldest age group in the sample, which may have resulted in an unstable estimate of late AMD. Second, several known and potential risk factors for AMD were not assessed, including family history, smoking history, blood pressure, alcohol consumption, and dietary intake, which limited our ability to conduct comprehensive risk factor analysis for AMD. Third, the use of nonstereoscopic images and the exclusion of optical coherence tomography in the study protocol may have resulted in a reduced sensitivity of AMD detection. Fourth, those with missing or ungradable images were on average older than study participants with gradable images, which may have led to an underestimation of the true prevalence of AMD among Australian adults.

Conclusions

The NEHS provides age- and indigenous-specific prevalence estimates of early, intermediate, and late AMD in a national population-based sample of Australian adults. The prevalence of late AMD in indigenous Australians was low (0.17%), with potential explanations, including genetic factors and a lower life expectancy. However, in line with data from other white populations, AMD is a prominent cause of blindness in the nonindigenous Australian population. With a significant aging of the Australian population and an increase in life expectancy, improved access to low vision rehabilitation services may be required to cope with the burden of AMD.

Back to top
Article Information

Corresponding Author: Stuart Keel, PhD, Centre for Eye Research Australia, Royal Victorian Eye & Ear Hospital, 32 Gisborne St, East Melbourne, Victoria, Australia 3002 (stuart.keel@unimelb.edu.au).

Accepted for Publication: August 26, 2017.

Published Online: October 12, 2017. doi:10.1001/jamaophthalmol.2017.4182

Author Contributions: Drs Keel and Dirani had full access to the data in the study and take responsibility for the integrity of the data and accuracy of data analysis.

Study concept and design: Keel, Foreman, van Wijngaarden, Taylor, Dirani.

Acquisition, analysis, or interpretation of data: Keel, Xie, Foreman, Dirani.

Drafting of the manuscript: Keel.

Critical revision of the manuscript for important intellectual content: Foreman, van Wijngaarden, Taylor, Dirani.

Statistical analysis: Keel, Xie.

Obtained funding: Dirani.

Administrative, technical, or material support: Keel, Foreman, Dirani.

Study supervision: Taylor, Dirani.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.

Funding/Support: The National Eye Health Survey was funded by the Department of Health of the Australian Government and also received financial contributions from the Peggy and Leslie Cranbourne Foundation and Novartis Australia. In-kind support was received from industry and sector partners, OPSM, Carl Zeiss, Designs for Vision, the Royal Flying Doctor Service, Optometry Australia, and the Brien Holden Vision Institute. Dr Dirani is supported by National Health and Medical Research Council Career Development Fellowship 1090466. Mr Foreman is supported by an Australian Postgraduate Award scholarship.

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and the decision to submit the manuscript for publication.

Additional Contributions: We acknowledge OPSM, who kindly donated sunglasses valued at $130 for each study participant. The Centre for Eye Research Australia (CERA) receives operational infrastructure support from the Victorian government. CERA and Vision 2020 Australia wish to recognize the contributions of all the National Eye Health Survey project steering committee members. Furthermore, we acknowledge the overwhelming support from all collaborating indigenous organizations that assisted with the implementation of the survey and the indigenous health workers and volunteers at each survey site who contributed to the field work.

References
1.
VanNewkirk  MR, Weih  L, McCarty  CA, Taylor  HR.  Cause-specific prevalence of bilateral visual impairment in Victoria, Australia: the Visual Impairment Project.  Ophthalmology. 2001;108(5):960-967.PubMedGoogle ScholarCrossref
2.
Wang  JJ, Foran  S, Mitchell  P.  Age-specific prevalence and causes of bilateral and unilateral visual impairment in older Australians: the Blue Mountains Eye Study.  Clin Exp Ophthalmol. 2000;28(4):268-273.PubMedGoogle ScholarCrossref
3.
Congdon  N, O’Colmain  B, Klaver  CC,  et al; Eye Diseases Prevalence Research Group.  Causes and prevalence of visual impairment among adults in the United States.  Arch Ophthalmol. 2004;122(4):477-485.PubMedGoogle ScholarCrossref
4.
Pascolini  D, Mariotti  SP, Pokharel  GP,  et al.  2002 Global update of available data on visual impairment: a compilation of population-based prevalence studies.  Ophthalmic Epidemiol. 2004;11(2):67-115.PubMedGoogle ScholarCrossref
5.
Australian Government Department of Health.  Implementation Plan Under the National Framework for Action to Promote Eye Health and Prevent Avoidable Blindness and Vision Loss. Canberra, Australia: Communications Branch, Dept of Health; 2014.
6.
Cahill  MT, Banks  AD, Stinnett  SS, Toth  CA.  Vision-related quality of life in patients with bilateral severe age-related macular degeneration.  Ophthalmology. 2005;112(1):152-158.PubMedGoogle ScholarCrossref
7.
Hassell  JB, Lamoureux  EL, Keeffe  JE.  Impact of age related macular degeneration on quality of life.  Br J Ophthalmol. 2006;90(5):593-596.PubMedGoogle ScholarCrossref
8.
Mitchell  P.  Eyes on the Future: A Clear Outlook on Age-Related Macular Degeneration. Sydney, Australia: Deloitte Access Economics; 2011:1-146.
9.
Wong  WL, Su  X, Li  X,  et al.  Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: a systematic review and meta-analysis.  Lancet Glob Health. 2014;2(2):e106-e116.PubMedGoogle ScholarCrossref
10.
VanNewkirk  MR, Nanjan  MB, Wang  JJ, Mitchell  P, Taylor  HR, McCarty  CA.  The prevalence of age-related maculopathy: the visual impairment project.  Ophthalmology. 2000;107(8):1593-1600.PubMedGoogle ScholarCrossref
11.
Mitchell  P, Smith  W, Attebo  K, Wang  JJ.  Prevalence of age-related maculopathy in Australia: the Blue Mountains Eye Study.  Ophthalmology. 1995;102(10):1450-1460.PubMedGoogle ScholarCrossref
12.
Australian Bureau of Statistics. Australian Social Trends: Life-Expectancy Trends. http://www.ausstats.abs.gov.au/ausstats/subscriber.nsf/LookupAttach/4102.0Publication23.03.112/$File/41020_Lifeexpectancy_Mar2011.pdf2011. Accessed March 23, 2017.
13.
Landers  J, Henderson  T, Craig  J.  The prevalence and causes of visual impairment in indigenous Australians within central Australia: the Central Australian Ocular Health Study.  Br J Ophthalmol. 2010;94(9):1140-1144.PubMedGoogle ScholarCrossref
14.
Taylor  HR, Xie  J, Fox  S, Dunn  RA, Arnold  AL, Keeffe  JE.  The prevalence and causes of vision loss in Indigenous Australians: the National Indigenous Eye Health Survey.  Med J Aust. 2010;192(6):312-318.PubMedGoogle Scholar
15.
Australian Institute of Health and Welfare.  Vision Problems Among Older Australians. Canberra: Australian Institute of Health and Welfare; 2005.
16.
Foreman  J, Keel  S, Dunn  R, van Wijngaarden  P, Taylor  HR, Dirani  M.  Sampling methodology and site selection in the National Eye Health Survey: an Australian population-based prevalence study.  Clin Exp Ophthalmol. 2017;45(4):336-347.PubMedGoogle ScholarCrossref
17.
Foreman  J, Keel  S, van Wijngaarden  P, Taylor  HR, Dirani  M.  Recruitment and testing protocol in the National Eye Health Survey: a population-based eye study in Australia.  Ophthalmic Epidemiol. 2017:1-11.PubMedGoogle Scholar
18.
World Medical Association.  World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects.  JAMA. 2013;310(20):2191-2194. doi:10.1001/jama.2013.281053PubMedGoogle ScholarCrossref
19.
Bird  AC, Bressler  NM, Bressler  SB,  et al; The International ARM Epidemiological Study Group.  An international classification and grading system for age-related maculopathy and age-related macular degeneration.  Surv Ophthalmol. 1995;39(5):367-374.PubMedGoogle ScholarCrossref
20.
Ferris  FL  III, Wilkinson  CP, Bird  A,  et al; Beckman Initiative for Macular Research Classification Committee.  Clinical classification of age-related macular degeneration.  Ophthalmology. 2013;120(4):844-851.PubMedGoogle ScholarCrossref
21.
Kawasaki  R, Wang  JJ, Aung  T,  et al; Singapore Malay Eye Study Group.  Prevalence of age-related macular degeneration in a Malay population: the Singapore Malay Eye Study.  Ophthalmology. 2008;115(10):1735-1741.PubMedGoogle ScholarCrossref
22.
Varma  R, Fraser-Bell  S, Tan  S, Klein  R, Azen  SP; Los Angeles Latino Eye Study Group.  Prevalence of age-related macular degeneration in Latinos: the Los Angeles Latino eye study.  Ophthalmology. 2004;111(7):1288-1297.PubMedGoogle ScholarCrossref
23.
Smith  W, Assink  J, Klein  R,  et al.  Risk factors for age-related macular degeneration: pooled findings from three continents.  Ophthalmology. 2001;108(4):697-704.PubMedGoogle ScholarCrossref
24.
Australian Institute of Health and Welfare.  2010 National Drug Strategy Household Survey: Survey Report. Canberra: Australian Institute of Health and Welfare; 2010.
25.
Jonasson  F, Arnarsson  A, Sasaki  H, Peto  T, Sasaki  K, Bird  AC.  The prevalence of age-related maculopathy in Iceland: Reykjavik eye study.  Arch Ophthalmol. 2003;121(3):379-385.PubMedGoogle ScholarCrossref
26.
Klein  R, Klein  BE, Linton  KL.  Prevalence of age-related maculopathy: the Beaver Dam Eye Study.  Ophthalmology. 1992;99(6):933-943.PubMedGoogle ScholarCrossref
27.
Vingerling  JR, Dielemans  I, Hofman  A,  et al.  The prevalence of age-related maculopathy in the Rotterdam Study.  Ophthalmology. 1995;102(2):205-210.PubMedGoogle ScholarCrossref
28.
Bressler  SB, Muñoz  B, Solomon  SD, West  SK; Salisbury Eye Evaluation (SEE) Study Team.  Racial differences in the prevalence of age-related macular degeneration: the Salisbury Eye Evaluation (SEE) Project.  Arch Ophthalmol. 2008;126(2):241-245.PubMedGoogle ScholarCrossref
29.
Klein  R, Klein  BE, Jensen  SC, Mares-Perlman  JA, Cruickshanks  KJ, Palta  M.  Age-related maculopathy in a multiracial United States population: the National Health and Nutrition Examination Survey III.  Ophthalmology. 1999;106(6):1056-1065.PubMedGoogle ScholarCrossref
30.
Klein  R, Klein  BE, Knudtson  MD,  et al.  Prevalence of age-related macular degeneration in 4 racial/ethnic groups in the multi-ethnic study of atherosclerosis.  Ophthalmology. 2006;113(3):373-380.PubMedGoogle ScholarCrossref
31.
Jampol  LM, Tielsch  J.  Race, macular degeneration, and the Macular Photocoagulation Study.  Arch Ophthalmol. 1992;110(12):1699-1700.PubMedGoogle ScholarCrossref
32.
Leveziel  N, Puche  N, Zerbib  J,  et al.  Genetic factors associated with age-related macular degeneration [in French].  Med Sci (Paris). 2010;26(5):509-515.PubMedGoogle ScholarCrossref
33.
Australian Institute of Health and Welfare.  Mortality and Life Expectancy of Indigenous Australians. Canberra: Australian Institute of Health and Welfare; 2014.
34.
Age-Related Eye Disease Study Research Group.  A randomized, placebo-controlled, clinical trial of high-dose supplementation with vitamins C and E, beta carotene, and zinc for age-related macular degeneration and vision loss: AREDS report no. 8.  Arch Ophthalmol. 2001;119(10):1417-1436.PubMedGoogle ScholarCrossref
35.
Avery  RL, Pieramici  DJ, Rabena  MD, Castellarin  AA, Nasir  MA, Giust  MJ.  Intravitreal bevacizumab (Avastin) for neovascular age-related macular degeneration.  Ophthalmology. 2006;113(3):363-372.e5.PubMedGoogle ScholarCrossref
36.
Ferrara  N, Damico  L, Shams  N, Lowman  H, Kim  R.  Development of ranibizumab, an anti-vascular endothelial growth factor antigen binding fragment, as therapy for neovascular age-related macular degeneration.  Retina. 2006;26(8):859-870.PubMedGoogle ScholarCrossref
37.
Regillo  CD, Busbee  BG, Ho  AC, Ding  B, Haskova  Z.  Baseline predictors of 12-month treatment response to ranibizumab in patients with wet age-related macular degeneration.  Am J Ophthalmol. 2015;160(5):1014-1023.e2.PubMedGoogle ScholarCrossref
38.
Gupta  OP, Brown  GC, Brown  MM.  Age-related macular degeneration: the costs to society and the patient.  Curr Opin Ophthalmol. 2007;18(3):201-205.PubMedGoogle ScholarCrossref
×