Search

Summary Background Excessive use of digital smart devices, including smartphones and tablet computers, could be a risk factor for myopia. We aimed to review the literature on the association between digital smart device use and myopia. Methods In this systematic review and meta-analysis we searched MEDLINE and Embase, and manually searched reference lists for primary research articles investigating smart device (ie, smartphones and tablets) exposure and myopia in children and young adults (aged 3 months to 33 years) from database inception to June 2 (MEDLINE) and June 3 (Embase), 2020. We included studies that investigated myopia-related outcomes of prevalent or incident myopia, myopia progression rate, axial length, or spherical equivalent. Studies were excluded if they were reviews or case reports, did not investigate myopia-related outcomes, or did not investigate risk factors for myopia. Bias was assessed with the Joanna Briggs Institute Critical Appraisal Checklists for analytical cross-sectional and cohort studies. We categorised studies as follows: category one studies investigated smart device use independently; category two studies investigated smart device use in combination with computer use; and category three studies investigated smart device use with other near-vision tasks that were not screen-based. We extracted unadjusted and adjusted odds ratios (ORs), β coefficients, prevalence ratios, Spearman's correlation coefficients, and p values for associations between screen time and incident or prevalent myopia. We did a meta-analysis of the association between screen time and prevalent or incident myopia for category one articles alone and for category one and two articles combined. Random-effects models were used when study heterogeneity was high (I2>50%) and fixed-effects models were used when heterogeneity was low (I2≤50%). Findings 3325 articles were identified, of which 33 were included in the systematic review and 11 were included in the meta-analysis. Four (40%) of ten category one articles, eight (80%) of ten category two articles, and all 13 category three articles used objective measures to identify myopia (refraction), whereas the remaining studies used questionnaires to identify myopia. Screen exposure was measured by use of questionnaires in all studies, with one also measuring device-recorded network data consumption. Associations between screen exposure and prevalent or incident myopia, an increased myopic spherical equivalent, and longer axial length were reported in five (50%) category one and six (60%) category two articles. Smart device screen time alone (OR 1·26 [95% CI 1·00–1·60]; I2=77%) or in combination with computer use (1·77 [1·28–2·45]; I2=87%) was significantly associated with myopia. The most common sources of risk of bias were that all 33 studies did not include reliable measures of screen time, seven (21%) did not objectively measure myopia, and nine (27%) did not identify or adjust for confounders in the analysis. The high heterogeneity between studies included in the meta-analysis resulted from variability in sample size (range 155–19 934 participants), the mean age of participants (3–16 years), the standard error of the estimated odds of prevalent or incident myopia (0·02–2·21), and the use of continuous (six [55%] of 11) versus categorical (five [46%]) screen time variables Interpretation Smart device exposure might be associated with an increased risk of myopia. Research with objective measures of screen time and myopia-related outcomes that investigates smart device exposure as an independent risk factor is required. Funding None.

Clinical relevance: The malignant potential of choroidal melanocytic tumours detected incidentally in the community is thought to be low, but this has not been assessed using a validated screening tool. An accurate characterisation of the malignant potential of these lesions has implications for resource allocation, service provision, education, and training.Background: MOLES (Mushroom shape, Orange Pigment, Large size, Enlargement, and Subretinal fluid) categorises tumours as 'common naevus', 'low-risk naevus', 'high-risk naevus', and 'probable melanoma'. The MOLES system recommends that patients with common naevi (score = 0) undergo review by a community optometrist every two years, ideally with sequential colour photography. For the remaining patients (score ≥ 1), specialist imaging and assessment are recommended, with referral triaged as non-urgent for patients with low-risk (score = 1) or high-risk naevi (score = 2) and urgent for patients with probable melanoma (score > 2).Methods: Lesions flagged as choroidal melanocytic tumours on retinal photographs taken during the Australian National Eye Health Survey were retrospectively analysed by an ocular oncologist. Each lesion was assigned a MOLES score and categorised as common, low-risk, high-risk or probable melanoma.Results: Seventy-seven choroidal naevi were identified. Seventy-five (97%) of the choroidal naevi were categorised as common naevi, with a MOLES score of 0. Two (3%) choroidal naevi had a score of 1 and diagnosed as low-risk naevi due to their size. No naevi had a score of 2 or more.Conclusion: All choroidal naevi detected in this nationally representative population survey were innocuous. This suggests that the vast majority of choroidal melanocytic tumours that are incidentally detected in Australia can be managed in primary eye care settings without the need for specialist referral. MOLES provides a simple evidence-based method for choroidal naevi assessment in primary care.

AIM: To determine the prevalence and associations of non-retinopathy ocular conditions among older Australian adults with diabetes. METHODS: Multistage random-cluster sampling was used to select 3098 non-indigenous Australians aged 50y or older (46.4% male) and 1738 indigenous Australians aged 40y or older (41.1% male) from all levels of geographic remoteness in Australia. Participants underwent a standardised questionnaire to ascertain diabetes history, and a clinical examination to identify eye disease. We determined the prevalence of uncorrected refractive error, visually significant cataract, cataract surgery, age-related macular degeneration, glaucoma, ocular hypertension, retinal vein occlusion and epiretinal membrane among those with and without self-reported diabetes. RESULTS: Participants with self-reported diabetes had a higher prevalence of cataract surgery than those without diabetes (28.8% vs 16.9%, OR 1.78, 95%CI: 1.35-2.34 among non-indigenous Australians, and 11.3% vs 5.2%, OR 1.62, 95%CI: 1.22-2.14 among indigenous Australians). Diabetic retinopathy (DR) increased the odds of cataract surgery among self-reported diabetic indigenous and non-indigenous Australians (OR 1.89, P=0.004 and OR 2.33, P

IMPORTANCE: Projections of Australia's future burden of vision loss will inform eye health service delivery. BACKGROUND: This study aimed to forecast bilateral vision loss in Australia from 2020 to 2050. DESIGN: Population-based survey. PARTICIPANTS: Indigenous and non-indigenous Australians (n = 4253) aged ≥50 years from the National Eye Health Survey (NEHS, 2015-2016). METHODS: Using the age-and-sex-stratified prevalence of vision loss (better eye visual acuity

Objective To present the prevalence of self-reported diabetes in Indigenous and non-Indigenous participants in the National Eye Health Survey. Research Design and Methods 3098 non-Indigenous Australians aged 50–98 years and 1738 Indigenous Australians aged 40–92 years were examined in 30 randomly selected sites, stratified by remoteness. A history of diabetes was obtained using an interviewer-administered questionnaire. Results 13.91% (431/3098) of non-Indigenous Australians and 37.11% (645/1738) of Indigenous Australians had self-reported diabetes. The age-adjusted prevalence of self-reported diabetes for non-Indigenous and Indigenous Australians was 11.49% and 43.77%, respectively (p

AimTo estimate the prevalence of glaucoma in Australia.MethodsThis was a population-based study of 3098 non-Indigenous Australians (50–98 years) and 1738 Indigenous Australians (40–92 years) stratified by remoteness. Each participant underwent a standard examination that included visual field assessment, tonometry and non-mydriatic fundus photography. Two fellowship-trained glaucoma specialists independently assessed relevant case notes (past ocular history, best-corrected visual acuity, frequency doubling technology visual fields, Van Herick grade, intraocular pressure and optic disc-centred photographs) and assigned a diagnosis ranked on a scale of certainty: none, possible, probable or definite glaucoma.ResultsA total of 4792 (99.1%, 3062 non-Indigenous and 1730 Indigenous) participants had retinal photographs in at least one eye that were gradable for glaucoma. The weighted prevalence of glaucoma (definite) in non-Indigenous Australians and Indigenous Australians was 1.5% (95% CI 1.0 to 2.2) and 0.6% (95% CI 0.4 to 1.1), respectively. When definite and probable cases of glaucoma were combined, rates were 3.4% (95% CI 2.7 to 4.3) among non-Indigenous and 1.6% (95% CI 1.1 to 2.3) in Indigenous Australians. Only 52.4% of non-Indigenous Australians and 28.0% of Indigenous Australians with glaucoma self-reported a known history of glaucoma.ConclusionWe estimate that 198 923 non-Indigenous Australians aged 50 years and over and 2139 Indigenous Australians aged 40 years and over have glaucoma. Given the high rates of undiagnosed glaucoma coupled with a significant ageing of the Australian population, improvements in case detection and access to low vision rehabilitation services may be required to cope with the growing burden of glaucoma.

PURPOSE: To describe the prevalence and associations of presenting near vision impairment (NVI) in Indigenous and non-Indigenous Australians. METHODS: A sample of 3098 non-Indigenous Australians (aged 50–98 years) and 1738 Indigenous Australians (aged 40–92 years) living in 30 randomly selected Australian sites were examined as part of the population-based National Eye Health Survey (NEHS). Binocular presenting NVI was defined as near vision worse than N8 (20/50). RESULTS: In total, 4817 participants (99.6% of the total sample, comprising 3084 non-Indigenous Australians and 1733 Indigenous Australians) had complete data on near visual acuity. The overall weighted prevalence of presenting NVI was 21.6% (95% CI: 19.6, 23.8) in non-Indigenous Australians and 34.7% (95% CI: 29.2, 40.8) among Indigenous Australians. In the non-Indigenous population, higher odds of presenting NVI were associated with older age (OR=1.68 per 10 years, P

AimTo assess the visual outcomes of cataract surgery among a national sample of non-Indigenous and Indigenous Australians.MethodsThis was a population-based study of 3098 non-Indigenous Australians (50–98 years) and 1738 Indigenous Australians (40–92 years), stratified by remoteness. A poor postoperative outcome in an eye that had undergone cataract surgery was defined as presenting distance visual acuity (PVA) ResultsThe sampling weight adjusted cataract surgery prevalence was 19.8% (95% CI 17.9 to 22.0) in non-Indigenous Australians and 8.2% (95% CI 6.0 to 9.6) in Indigenous Australians. Among the non-Indigenous population, poor and very poor PVA outcomes were present in 18.1% and 1.9% of eyes, respectively. For Indigenous Australians, these values were 27.8% and 6.3%, respectively. The main causes of poor vision were refractive error (non-Indigenous=41.8%; Indigenous=41.9%) and coincident disease (non-Indigenous=43.3%; Indigenous=40.3%). The eCSC rates in the non-Indigenous and Indigenous populations were 88.5% (95% CI 85.2 to 91.2) and 51.6% (95% CI 42.4 to 60.7), respectively.ConclusionApproximately half of eyes with a poor visual outcome postcataract surgery could be readily avoided through the appropriate refractive correction. The finding of a lower eCSC rate among Indigenous Australians suggests that improvements in access and quality of cataract services may be warranted in order to reduce cataract-related vision loss in the Indigenous population.

Purpose: To conduct a nationwide survey on the prevalence and causes of vision impairment and blindness in Indigenous and non-Indigenous Australians. \ud Design: Nationwide, cross-sectional, population-based field survey. Participants: Indigenous Australians aged 40 years or older and non-Indigenous Australians aged 50 years or more randomly sampled from all levels of geographic remoteness in Australia. \ud Methods: Multistage random-cluster sampling was used to select 3098 non-Indigenous Australians and 1738 Indigenous Australians from 30 sites across 5 remoteness strata with a response rate of 71.5%. Sociodemographic and health data were collected using an interviewer-administered questionnaire. Trained examiners conducted standardized eye examinations, including visual acuity, perimetry, slit-lamp examination, intraocular pressure, and fundus photography. The prevalence and main causes of bilateral presenting vision loss (visual acuity worse than 6/12 in the better eye) were determined, and risk factor analysis was conducted. \ud Main Outcome Measures: The prevalence and main causes of vision impairment and blindness. \ud Results: The overall prevalence of vision loss in Australia was 6.6% (95% confidence interval [CI], 5.4e7.8). The prevalence of vision loss was 11.2% (95% CI, 9.5e13.1) in Indigenous Australians and 6.5% (95% CI, 5.3e7.9) in non-Indigenous Australians. Vision loss was 2.8 times more prevalent in Indigenous Australians than in non-Indigenous Australians after age and gender adjustment (17.7%, 95% CI, 14.5e21.0 vs. 6.4%, 95% CI, 5.2e7.6, P < 0.001). In non-Indigenous Australians, the leading causes of vision loss were uncorrected refractive error (61.3%), cataract (13.2%), and age-related macular degeneration (10.3%). In Indigenous Australians, the leading causes of vision loss were uncorrected refractive error (60.8%), cataract (20.1%), and diabetic retinopathy (5.2%). In non-Indigenous Australians, increasing age (odds ratio [OR], 1.72 per decade; 95% CI, 1.40e2.10) and having not had an eye examination within the past year (OR, 1.61; 95% CI, 1.06e2.42) were risk factors for vision loss. Risk factors in Indigenous Australians included older age (OR, 1.61 per decade; 95% CI, 1.34e1.95), remoteness (OR, 2.02; 95% CI, 1.23e3.31), gender (OR, 0.60 for men; 95% CI, 0.42e0.84), and diabetes in combination with never having had an eye examination (OR, 14.47; 95% CI, 5.65e37.05). \ud Conclusions: Vision loss is more prevalent in Indigenous Australians than in non-Indigenous Australians, highlighting that improvements in eye healthcare in Indigenous communities are required. The leading causes of vision loss were uncorrected refractive error and cataract, which are readily treatable. Other countries with Indigenous communities may benefit from conducting similar surveys of Indigenous and non-Indigenous populations.

Background To determine the prevalence of vision loss due to ocular trauma in Australia. Methods The National Eye Health Survey (NEHS) is a population-based cross-sectional study that examined 3098 non-Indigenous Australians (aged 50–98 years) and 1738 Indigenous Australians (aged 40–92 years) living in 30 randomly selected sites, stratified by remoteness. An eye was considered to have vision loss due to trauma if the best-corrected visual acuity was worse than 6/12 and the main cause was attributed to ocular trauma. This determination was made by two independent ophthalmologists and any disagreements were adjudicated by a third senior ophthalmologist. Results The sampling weight adjusted prevalence of vision loss due to ocular trauma in non-Indigenous Australians aged 50 years and older and Indigenous Australians aged 40 years and over was 0.24% (95% CI: 0.10, 0.52) and 0.79% (95% CI: 0.56, 1.13), respectively. Trauma was attributed as an underlying cause of bilateral vision loss in one Indigenous participant, with all other cases being monocular. Males displayed a higher prevalence of vision loss from ocular trauma than females in both the non-Indigenous (0.47% vs. 1.25%, p = 0.03) and Indigenous populations (0.12% vs. 0.38%, p = 0.02). After multivariate adjustments, residing in Very Remote geographical areas was associated with higher odds of vision loss from ocular trauma. Conclusions We estimate that 2.4 per 1000 non-Indigenous and 7.9 per 1000 Indigenous Australian adults have monocular vision loss due to a previous severe ocular trauma. Our findings indicate that males, Indigenous Australians and those residing in Very Remote communities may benefit from targeted health promotion to improve awareness of trauma prevention strategies.

Importance National data on eye healthcare service utilisation will inform Australia's eye health policy. Background To investigate the utilisation of eye healthcare services by Australians. Design Cross-sectional survey Participants Indigenous Australians aged 40 years and older and non-Indigenous Australians aged 50 years and older. Methods 1738 Indigenous Australians and 3098 non-Indigenous Australians were recruited from 30 randomly-selected sites, stratified by remoteness. Sociodemographic, ocular history, and eye healthcare service utilisation data were collected, and an eye examination was conducted. Main outcome measures Recentness of eye examinations, types of providers used, and associated risk factors. Results 67.0% of Indigenous Australians and 82.5% of non-Indigenous Australians underwent an eye examination within the previous two years. Indigenous status (p

IMPORTANCE: In Australia, knowledge of the epidemiology of retinal vein occlusion remains scarce because of a paucity of recent population-based data. The National Eye Health Survey (2015-2016) provides an up-to-date estimate of the prevalence of retinal vein occlusion in non-Indigenous and Indigenous Australian adults. BACKGROUND: To determine the prevalence and associations of retinal vein occlusion in a national sample of Indigenous and non-Indigenous Australian adults. DESIGN: Population-based cross-sectional study. PARTICIPANTS: A total of 3098 non-Indigenous Australians (aged 50-98 years) and 1738 Indigenous Australians (aged 40-92 years) living in 30 randomly selected sites, stratified by remoteness. METHODS: Retinal vein occlusions were graded from retinal photographs using standardized protocols and recorded as central retinal vein occlusion or branch retinal vein occlusion. MAIN OUTCOME MEASURE: Prevalence of retinal vein occlusion. RESULTS: In the non-Indigenous population, the sampling weight adjusted prevalence of any retinal vein occlusion was 0.96% (95% confidence interval: 0.59, 1.6), with branch retinal vein occlusion observed in 0.72% (95% confidence interval: 0.41, 1.2) and central retinal vein occlusion in 0.24% (95% confidence interval: 0.13, 0.47). Any retinal vein occlusion was found in 0.91% (95% confidence interval: 0.47, 1.7) of Indigenous Australians aged 40 years and over, with branch retinal vein occlusion observed in 0.83% (95% confidence interval: 0.40, 1.7) and central retinal vein occlusion in 0.07% (95% confidence interval: 0.02, 0.32). Older age (odds ratio = 1.64 per 10 years, P = 0.006) and the presence of self-reported diabetes (odds ratio = 3.24, P = 0.006) were associated with any retinal vein occlusion after multivariable adjustments. Retinal vein occlusion was attributed as the cause of monocular vision loss (

Purpose To determine the prevalence of and factors associated with diabetic retinopathy (DR) among non-Indigenous and Indigenous Australian adults with self-reported diabetes. Design Population-based cross-sectional study. Participants Non-Indigenous Australians (50–98 years of age) and Indigenous Australians (40–92 years of age) with known diabetes. Methods Diabetes was determined based on self-report of previous diagnosis of the disease. Nonmydriatic fundus photographs were obtained of each eye and graded according to the modified Airlie House classification system. Main Outcome Measures Any DR, vision-threatening DR (VTDR), treatment coverage rates (proportion of participants with proliferative DR [PDR], clinically significant macular edema [CSME], or both who had evidence of retinal scatter and focal laser treatment). Results Four hundred thirty-one non-Indigenous Australians (13.9%) and 645 Indigenous Australians (37.1%) self-reported diabetes, of whom 93% (1004/1076) had retinal images that were gradable for DR. The sampling weight-adjusted prevalence of any DR and VTDR among non-Indigenous adults with self-reported diabetes was 28.5% (95% confidence interval [CI], 22.6–35.3) and 4.5% (95% CI, 2.6–7.9), respectively. Among adults 40 years of age and older, the sampling weight-adjusted prevalence of any DR and VTDR was 39.4% (95% CI, 33.1–46.1) and 9.5% (95% CI, 6.8–13.1), respectively. Longer diabetes duration was associated significantly with VTDR in the Indigenous Australian population (odds ratio [OR], 1.08 per 1-year increase; P = 0.005) and non-Indigenous Australian population (OR, 1.05 per 1-year increase; P = 0.03). The treatment coverage of PDR and CSME was 75% (56/75) in Indigenous Australians and 79% (15/19) in non-Indigenous Australians. Diabetic retinopathy was attributed as the main cause of vision loss ( Conclusions Three quarters of non-Indigenous and Indigenous Australian adults with PDR or CSME have received laser treatment. The prevalence of VTDR in Indigenous and non-Indigenous Australians in the present study was lower than that found in previous population-based reports, nevertheless, approximately 1 in 10 Indigenous adults with known diabetes experience VTDR. This highlights that intensified prevention strategies are required to delay or prevent avoidable vision loss resulting from DR in Indigenous Australian communities.

OBJECTIVE: To determine adherence to NHMRC eye examination guidelines for Indigenous and non-Indigenous Australian people with diabetes. DESIGN: Cross-sectional survey using multistage, random cluster sampling. SETTING: Thirty randomly selected geographic sites in the five mainland Australian states and the Northern Territory, stratified by remoteness. PARTICIPANTS: 1738 Indigenous Australians aged 40-92 years and 3098 non-Indigenous Australians aged 50-98 years were recruited and examined between March 2015 and April 2016 according to a standardised protocol that included a questionnaire (administered by an interviewer) and a series of standard eye tests. MAIN OUTCOME MEASURES: Adherence rates to NHMRC eye examination guidelines; factors influencing adherence. RESULTS: Adherence to screening recommendations was significantly greater among non-Indigenous Australians (biennial screening; 77.5%) than Indigenous Australians (annual screening; 52.7%; P

To present the recruitment and testing methodology of the National Eye Health Survey (NEHS), a population-based study that aimed to determine the prevalence and causes of vision impairment and blindness in Australia.Non-Indigenous Australians aged 50 years and older and Indigenous Australians aged 40 years and older were recruited using a door-to-door approach from 30 randomly selected geographical areas, stratified by remoteness. Participants underwent a vision examination, anterior segment assessment, intraocular pressure testing, perimetry, and fundus photography.In total, recruiters approached 23,235 residences, and 11,883 residents were successfully contacted (51.1%). Of these, 6760 (56.9%) were deemed eligible and 5764 agreed to participate (positive response rate = 85.3%). Of those who agreed, 4836 residents attended the examination (4836/6760 = 71.5%). This included 1738 Indigenous Australians (41.1% male) aged 40-92 years (mean ± standard deviation = 55.0 ± 10.0 years) and 3098 non-Indigenous Australians (46.4% male), aged 50-98 years (mean ± standard deviation = 66.6 ± 9.7 years).The NEHS achieved an excellent positive response rate, and the data collected from 4836 Australians will provide the first population-based national estimate of the prevalence of vision impairment and blindness. This data will guide future economic analysis, policy formulation, and eye health service delivery in Australia.

Background To present the sampling methodology and selected testing sites of the National Eye Health Survey (NEHS); a cross-sectional population-based survey that aimed to determine the prevalence of vision impairment and blindness in Australia. Design Indigenous Australians aged 40 years and older and non-Indigenous Australians aged 50 years and older residing in all levels of geographic remoteness in Australia. Methods Using multi-stage, random-cluster sampling, 30 geographic areas were selected to provide a sample of 3000 non-Indigenous Australians and 1400 Indigenous Australians. Site selection involved; 1) Selecting Statistical Area-Level 2 (SA2) sites, stratified by remoteness; 2) Selecting Statistical Area-Level 1 (SA1) sites within SA2 sites to provide targeted samples; 3) Grouping of target SA1 sites with contiguous SA1s or replacing SA1s to provide sufficient samples. Participants were recruited using a door-to-door approach. Main outcome measures Sites selected and participants sampled in the National Eye Health Survey. Results Thirty sites were generated, including; 12 Major City, 6 Inner Regional, 6 Outer Regional, 4 Remote, and 2 Very Remote sites within 5 States and one Territory. 3098 non-Indigenous participants and 1738 Indigenous participants were recruited. Selection of SA1s overestimated the number of eligible residents in all sites. 20% (6/30) of SA1s were situated in non-residential bushland, while 26.67% (8/30) of SA1 populations had low eligibility or accessibility, requiring replacement with contiguous SA1s. Conclusions Representative samples of Indigenous and non-Indigenous Australians were selected, recruited and tested, providing the first national data on the prevalence of vision impairment and blindness in Australia.

As the myopia epidemic gathers pace, with 5 billion people expected to be myopic and 1 billion predicted to have sight-threatening high myopia by 2050, there is an urgent need to identify targets for early intervention to mitigate the onset and progression of myopia among children.1 Research has suggested that insufficient time spent outdoors in childhood is one of myopia’s major modifiable risk factors,2 and public health interventions that increase time spent outdoors may therefore be the most scalable and efficacious preventative strategies. However, much of the time children spend outdoors consists of moderate-to-vigorous physical activity, and studies on the effect of time spent outdoors have typically not accounted for potentially confounding protective effects of physical activity against myopia.3 There is a noteworthy lack of research on and understanding of the independent association between myopia and physical activity, which might be measured independently of time spent outdoors by objectively studying physical activity in exclusively indoor environments or including ambient light sensors in studies on physical activity. This knowledge gap may impede the optimisation of behavioural interventions for myopia prevention. Physical activity exerts myriad positive effects on paediatric health and may protect against other eye diseases including glaucoma,4 and there are compelling reasons to expect that it may also attenuate axial elongation independently of time spent outdoors, perhaps through promotion of choroidal perfusion and thickening,5 although this has been disputed.6 A 2017 systematic review by Suhr Thykjaer and colleagues attempted to clarify the relationship between physical activity and myopia, but the authors were unable to draw strong conclusions owing …

Interest in reliable biomarkers of Alzheimer's disease, the leading cause of dementia, has been fuelled by challenges in diagnosing the disease and monitoring disease progression as well as the response to therapy. A range of ocular manifestations of Alzheimer's disease, including retinal and lens amyloid-beta accumulation, retinal nerve fibre layer loss and retinal vascular changes, have been proposed as potential biomarkers of the disease. Herein we examine the evidence regarding the potential value of these ocular biomarkers of Alzheimer's disease.

Background Given the rising public health burden of myopia, population-based data on the level of awareness about myopia amongst parents in Singapore are required for planning future awareness campaigns and public health interventions. This study aimed to evaluate the level of awareness of myopia amongst a group of parents residing in Singapore. Methods This study was a cross-sectional survey. A sample of 326 participants aged 19 to 69 years with at least 1 child were recruited at The Kidz Academy (TKA) 2018 exhibition in Singapore. Socio-demographic characteristics, smart device use and awareness of myopia (prevalence and mitigation strategies) were collected via an interviewer-administered online questionnaire. Results 56.7% (185/326) of survey respondents were aware of the high prevalence of myopia amongst secondary school-going Singaporean children. 18.1% (59/326) of the respondents reported that an eye-to-screen distance of less than 30 cm was acceptable and 27.0% (88/326) were unaware of the importance of regular eye examinations among children. Less than half of the respondents [46.6% (152/326)] correctly identified that Singaporean children spend at least 6.5 hours a day on digital screens. 87.7% (286/326) were aware of the importance of outdoor activity as an intervention to slow the progression of myopia, with female respondents significantly more likely to be aware of its importance [odds ratio (OR) = 2.12, 95% confidence interval = 1.09 – 4.13, χ2 = 4.86, P = .03]. Conclusion Survey respondents demonstrated a good level of awareness of the high prevalence of myopia in Singapore and the protective role of outdoor activity in its development and progression. Awareness campaigns may be beneficial for promoting regular eye examinations amongst children and educating the public on the risk of excessive time spent on smart devices.

Studies of rodent models of Alzheimer’s disease (AD) and of human tissues suggest that the retinal changes that occur in AD, including the accumulation of amyloid beta (Aβ), may serve as surrogate markers of brain Aβ levels. As Aβ has a wavelength-dependent effect on light scatter, we investigate the potential for in vivo retinal hyperspectral imaging to serve as a biomarker of brain Aβ. Significant differences in the retinal reflectance spectra are found between individuals with high Aβ burden on brain PET imaging and mild cognitive impairment (n = 15), and age-matched PET-negative controls (n = 20). Retinal imaging scores are correlated with brain Aβ loads. The findings are validated in an independent cohort, using a second hyperspectral camera. A similar spectral difference is found between control and 5xFAD transgenic mice that accumulate Aβ in the brain and retina. These findings indicate that retinal hyperspectral imaging may predict brain Aβ load., The use of PET for detection of Aβ in the brain in AD has limitations; studies also indicate that retinal changes, including Aβ deposition, occur in AD. Here the authors demonstrate the potential to use in vivo retinal hyperspectral imaging as a surrogate for brain accumulation of Aβ.

PURPOSE: To describe the prevalence of visually significant cataract in Indigenous and non-Indigenous Australians. METHODS: A total of 3098 non-Indigenous Australians aged 50 years and over and 1738 Indigenous Australians aged 40 years and over, residing in 30 randomly selected Australian sites, were examined as part of the population-based National Eye Health Survey (NEHS). For those with visual acuity worse than 6/12, photos of the anterior and posterior segment were taken with a nonmydriatic fundus camera and assessed for cataract. Visually significant cataract was assigned in eyes with best-corrected visual acuity worse than 6/12 and cataract that was determined to be the primary cause of vision loss in that eye. RESULTS: In total, 99.2% (4797/4836) participants had complete data for visual acuity and cataract assessment. The overall weighted prevalence of visually significant cataract was 2.7% (95% CI: 2.0, 3.5) in non-Indigenous Australians and 4.3% (95% CI: 3.1, 5.9) among Indigenous Australians. After adjusting for age and gender, the odds of visually significant cataract were almost three times higher among Indigenous participants compared to non-Indigenous participants (adjusted odds ratio (OR) 2.95, 95% CI: 2.03, 4.29). Only 54.8% of non-Indigenous Australians and 38.9% of Indigenous Australians with visually significant cataract self-reported a known history of cataract. CONCLUSIONS: Our results suggest that continued efforts are required to build sustainable cataract surgery services within Indigenous communities. Furthermore, given the significant ageing of the Australian population, maintaining high cataract surgery rates amongst the non-Indigenous population is critical to reduce cataract-related vision loss.

Importance In Australia, nationally representative data of the burden and associations of severe uncorrected refractive error are scarce. Background To report the prevalence and characteristics of severe uncorrected refractive error in Indigenous and non-Indigenous Australians. Design Population-based cross-sectional study. Participants A total of 3098 non-Indigenous Australians aged 50 to 98 and 1738 Indigenous Australians aged 40 to 92 living in 30 randomly selected Australian sites were examined. Methods Severe uncorrected refractive error was defined as an improvement of ≥2 lines on the logMAR chart in one or both eyes in participants with a presenting visual acuity Main outcome measure Severe uncorrected refractive error RESULTS: Prevalence of severe uncorrected refractive error was 11.0% (95% confidence interval 9.3-13.0) in non-Indigenous and 14.5% (12.5-16.7) in Indigenous Australians. Eighty-two percent of non-Indigenous and 77% of Indigenous participants had a spherical equivalent refraction between -2.00D and +2.00D. Indigenous Australians who were older (odds ratio [OR] for 70-79 years vs 40-49 years = 3.59), resided in outer regional areas (OR = 1.78) and did not have an eye examination in the previous 2-years (OR = 1.50) were associated with higher odds of severe uncorrected refractive error. Geographical remoteness (OR = .68 for inner regional), male gender (OR = 1.30), older age (OR for 70-79 years vs 50-59 years = 1.51) and failure to have an eye examination in the previous 2-years (OR = 2.06) were associated with severe uncorrected refractive error among non-Indigenous participants. Conclusions and relevance Increased public awareness of the importance of regular optometric examinations may be required in groups at high risk of severe uncorrected refractive error.

Purpose We report a rare case of unilateral progressive adult-onset myopia in a healthy 27 year old female patient. Observations The patient presented to our clinic in 2014 with gradual decrease in vision in the right eye since one and a half years. Her uncorrected visual acuity (UCVA) in the right eye was 0.05, improving to 1.0 with −2.25 Diopter Sphere (DS). The left eye uncorrected visual acuity was 1.0 partial improving to 1.0 with −0.50 Diopter Cylinder (DC) at 10°. The myopia in her right eye continued to increase steadily until her last detailed ophthalmic examination in November 2018, at the age of 31 years, showed a refractive error of −6.75 Diopter Sphere with −0.5 Diopter Cylinder at 170°. Ocular biometry readings showed an axial length (AL) of 25.79mm in the right eye compared to 25.05mm in 2015. The ocular examination of both eyes including clinical examination of anterior and posterior segment, corneal topography, lens densitometry, ultrasound B scan all were within normal limits. Over the last two years she has gradually developed moderate constant esotropia in the right eye, currently +30 Prism Diopters. A short visit to the clinic in December 2019, showed a refraction of −6.75DS with −0.5DC at 170° in the right eye and −0.50DC at 10° in the left eye. Conclusions and importance The abrupt onset of myopia in one eye in a healthy individual in this case, the degree of myopia, the nature and rate of progression, absence of risk factors, and otherwise normal ocular examination except for progressive increase in axial length is unusual. Our case brings us to conjecture the role of powerful local factors in the intrinsic regulation of eyeball growth going askew. We believe more and more reporting of myopia cases deviating from natural history and their study might provide clues in a new direction about myopia pathogenesis and our understanding and tackling of one of the oldest eye disease with an ever increasing prevalence.

Background To describe the clinical characteristics of non–English speaking patients from the Diabetes Management Project (NEDMP), and compare their diabetes management and severity of diabetic retinopathy (DR) with the English-speaking DMP sample (EDMP). Design A prospective study was conducted on non-English speaking adults with diabetes who attended the Royal Victorian Eye and Ear Hospital. Participants 136 (90.1%) non-English speaking adults were assessed, with a mean age of 72.2 years (range: 50-88 years); 74 (54.4%) were male. Methods Participants completed interviewer-administered questionnaires and underwent visual acuity, fundus photography, optical coherence tomography, biochemistry and anthropometric measurements. The EDMP assessed 609 patients in 2009 using a similar protocol. Main Outcome Measures Type and duration of diabetes, diabetes control and diabetic retinopathy. Results A total of 127 (93.4%) and 8 (5.9%) participants reported having type 2 and type 1 diabetes, respectively, with a median (IQR) duration of 17 (14) years. The proportion of patients with poor diabetes control (HbA1c ≥ 7%) in the NEDMP was similar to the EDMP (64.0% and 68.2%, respectively; P = 0.411). A significantly higher proportion of patients with DR in the NEDMP were found to have poor diabetes control (HbA1c ≥ 7%) compared to those without DR (80.9% vs. 50.0%, P = 0.003). Almost two-thirds of NEDMP patients (74/118) had DR and 23% (27/115) had diabetic macular edema. The prevalence of DR was similar between the NEDMP and EDMP studies, ranging from 25-30% and 28-29%. Conclusions The clinical characteristics, diabetes control, and DR severity of English and non-English-speaking patients were similar. The high proportion of poor diabetes management in non-English speaking patients with DR suggests educational and behavioural interventions to improve glycaemic control are warranted.

Objectives: The purpose of this study were (i) to assess the knowledge, attitudes and practice (KAP) and impact of socioeconomic factors upon the prevalence of pre-diabetes and diabetes (ii) compute a diabetes risk score and (iii) estimate the undiagnosed prevalence of hypertension amongst a large adult population in rural Bangladesh. Methods/design: A sample of 3104 adults aged ?30 years were interviewed from a cluster sample of 18 villages in the Banshgram Union of the Narail District, Bangladesh. Each participant was interviewed using a semi-structured questionnaire that assessed participant knowledge, attitudes and practice (KAP) regarding diabetes, its risk factors, complications and management. Data on demographic details, education, socioeconomic status, medical history, dietary and lifestyle behavior was obtained. Fasting capillary glucose, blood pressure, presenting vision and anthropometric parameters were measured. Participants were stratified into those without diabetes, pre-diabetes, and diagnosed diabetes (known and newly diagnosed). The association of KAP components and other risk factors with diabetes status was assessed. Logistic regression analysis allowed for the development of a non-invasive risk-stratification tool to be developed and implemented for the rural Bangladeshi community. Multinomial logistic regression was applied to report the associations of risk factors with the severity of hypertension. Results and discussion: In Banshgram, over 95% people had not undergone any previous diabetes screening. Baseline demographics estimated the prevalence of diabetes in the sample was 3.2% (n=99). 47% of participants had no formal education. Whilst there is literature on the prevalence of diabetes in urban and semi-urban Bangladesh there is a paucity of evidence examining the impact of KAP of diabetes amongst the general community. We believe that the BPDES has developed a methodology to provide new evidence to guide health policy and targeted population-based interventions in these rural areas.Bangladesh Journal of Medical Science Vol.14(4) 2015 p.367-375

Importance Studies have documented a higher disease burden in indigenous compared with nonindigenous populations, but no global data on the epidemiology of visual loss in indigenous peoples are available. A systematic review of literature on visual loss in the world’s indigenous populations could identify major gaps and inform interventions to reduce their burden of visual loss. Objective To conduct a systematic review on the prevalence and causes of visual loss among the world’s indigenous populations. Evidence Review A search of databases and alternative sources identified literature on the prevalence and causes of visual loss (visual impairment and blindness) and eye diseases in indigenous populations. Studies from January 1, 1990, through August 1, 2017, that included clinical eye examinations of indigenous participants and, where possible, compared findings with those of nonindigenous populations were included. Methodologic quality of studies was evaluated to reveal gaps in the literature. Findings Limited data were available worldwide. A total of 85 articles described 64 unique studies from 24 countries that examined 79 598 unique indigenous participants. Nineteen studies reported comparator data on 42 085 nonindigenous individuals. The prevalence of visual loss was reported in 13 countries, with visual impairment ranging from 0.6% in indigenous Australian children to 48.5% in native Tibetans 50 years or older. Uncorrected refractive error was the main cause of visual impairment (21.0%-65.1%) in 5 of 6 studies that measured presenting visual acuity. Cataract was the main cause of visual impairment in all 6 studies measuring best-corrected acuity (25.4%-72.2%). Cataract was the leading cause of blindness in 13 studies (32.0%-79.2%), followed by uncorrected refractive error in 2 studies (33.0% and 35.8%). Conclusions and Relevance Most countries with indigenous peoples do not have data on the burden of visual loss in these populations. Although existing studies vary in methodologic quality and reliability, they suggest that most visual loss in indigenous populations is avoidable. Improvements in quality and frequency of research into the eye health of indigenous communities appear to be required, and coordinated eye care programs should be implemented to specifically target the indigenous peoples of the world.

Review objective/question:The objectives of this review are:To examine the burden of vision loss in Indigenous peoples worldwide by:Assessing the prevalence of vision loss in Indigenous peoples of the world.Assessing what eye diseases or conditions are responsible for vision loss in Indigenous peopl

Choroidal nevi are a common incidental finding on fundus examination. The National Eye Health Survey (NEHS, 2015-2016) provides an up-to-date estimate of the prevalence of choroidal nevi in non-Indigenous and Indigenous Australian adults.To describe the prevalence and characteristics of choroidal nevi among non-Indigenous and Indigenous Australian adults.Population-based cross-sectional study.This study included 3098 non-Indigenous Australians (aged 50-98 years) and 1738 Indigenous Australians (aged 40-92 years) living in 30 randomly selected sites, stratified by remoteness.Choroidal nevi were graded from retinal photographs using standard protocols.Prevalence of choroidal nevi.In the non-Indigenous population aged 50 years and over, the weighted prevalence of choroidal nevi was 2.1% (95% CI: 1.4, 3.3). Among Indigenous Australians aged 40 years and over, the weighted prevalence of choroidal nevi was 0.68% (95% CI: 0.4, 1.3). The average maximum diameter, surface area and distance from the disc of the choroidal nevi was 1730 μm, 2 766 800 μmChoroidal nevi were relatively infrequent among NEHS participants, however non-Indigenous Australians had a significantly higher prevalence than Indigenous Australians. Choroidal nevi did not affect visual acuity and the majority were small.

We assessed the validity and reliability of self-report of eye disease in participants with unilateral vision loss (presenting visual acuity worse than 6/12 in the worse eye and equal to or better than 6/12 in the better eye) or bilateral vision loss (presenting visual acuity worse than 6/12 in the better eye) in Australia’s National Eye Health Survey. In total, 1738 Indigenous Australians and 3098 non-Indigenous Australians were sampled from 30 sites. Participants underwent a questionnaire and self-reported their eye disease histories. A clinical examination identified whether participants had cataract, age-related macular degeneration, diabetic retinopathy and glaucoma. For those identified as having unilateral or bilateral vision loss (438 Indigenous Australians and 709 non-Indigenous Australians), self-reports were compared with examination results using validity and reliability measures. Reliability was poor for all four diseases (Kappa 0.06 to 0.37). Measures of validity of self-report were variable, with generally high specificities (93.7% to 99.2%) in all diseases except for cataract (63.9 to 73.1%) and low sensitivities for all diseases (7.6% in Indigenous Australians with diabetic retinopathy to 44.1% of non-Indigenous Australians with cataract). This study suggests that self-report is an unreliable population-based research tool for identifying eye disease in those with vision loss.

In Australia, knowledge of the epidemiology of retinal vein occlusion remains scarce because of a paucity of recent population-based data. The National Eye Health Survey (2015-2016) provides an up-to-date estimate of the prevalence of retinal vein occlusion in non-Indigenous and Indigenous Australian adults.To determine the prevalence and associations of retinal vein occlusion in a national sample of Indigenous and non-Indigenous Australian adults.Population-based cross-sectional study.A total of 3098 non-Indigenous Australians (aged 50-98 years) and 1738 Indigenous Australians (aged 40-92 years) living in 30 randomly selected sites, stratified by remoteness.Retinal vein occlusions were graded from retinal photographs using standardized protocols and recorded as central retinal vein occlusion or branch retinal vein occlusion.Prevalence of retinal vein occlusion.In the non-Indigenous population, the sampling weight adjusted prevalence of any retinal vein occlusion was 0.96% (95% confidence interval: 0.59, 1.6), with branch retinal vein occlusion observed in 0.72% (95% confidence interval: 0.41, 1.2) and central retinal vein occlusion in 0.24% (95% confidence interval: 0.13, 0.47). Any retinal vein occlusion was found in 0.91% (95% confidence interval: 0.47, 1.7) of Indigenous Australians aged 40 years and over, with branch retinal vein occlusion observed in 0.83% (95% confidence interval: 0.40, 1.7) and central retinal vein occlusion in 0.07% (95% confidence interval: 0.02, 0.32). Older age (odds ratio = 1.64 per 10 years, P = 0.006) and the presence of self-reported diabetes (odds ratio = 3.24, P = 0.006) were associated with any retinal vein occlusion after multivariable adjustments. Retinal vein occlusion was attributed as the cause of monocular vision loss (6/12) in seven (0.25%) non-Indigenous and six (0.36%) Indigenous participants.These data suggest that retinal vein occlusion is relatively uncommon in the non-Indigenous Australians aged 50 years and over and Indigenous Australians aged 40 years and over. Similar to previous Australian and international reports, the prevalence of retinal vein occlusion rose sharply with age.

Australia is the only developed country to still have pockets of endemic trachoma. The research provides up-to-date, population-based prevalence data of later complications of trachoma amongst a national sample of Indigenous adults.To report the prevalence of trachomatous trichiasis (TT) in Indigenous Australians aged 40 years and older.Population-based cross-sectional study.A total of 1738 (41% male) Indigenous Australians aged 40 years or older, living amongst 30 randomly selected Australian sites, stratified by remoteness.Anterior segment examination was performed and trachoma grading for the presence of TT and corneal opacification (CO) was conducted using the WHO (WHO) simplified grading system.Prevalence of TT.A total of three (0.17%) participants had TT, and there were no confirmed cases of trachomatous CO in the NEHS. All three participants with TT were female and aged 40 years or older. Although they had likely spent their childhoods in more remote areas, two of the three confirmed cases resided in an urban and outer regional area at the time of their examinations.Our data are in line with ongoing national trachoma surveillance reports that suggest the prevalence of late sequences of trachoma appear to be decreasing in Australia.

To conduct a nationwide survey on the prevalence and causes of vision loss in Indigenous and non-Indigenous Australians.Nationwide, cross-sectional, population-based survey.Indigenous Australians aged 40 years or older and non-Indigenous Australians aged 50 years and older.Multistage random-cluster sampling was used to select 3098 non-Indigenous Australians and 1738 Indigenous Australians from 30 sites across 5 remoteness strata (response rate of 71.5%). Sociodemographic and health data were collected using an interviewer-administered questionnaire. Trained examiners conducted standardized eye examinations, including visual acuity, perimetry, slit-lamp examination, intraocular pressure, and fundus photography. The prevalence and main causes of bilateral presenting vision loss (visual acuity6/12 in the better eye) were determined, and risk factors were identified.Prevalence and main causes of vision loss.The overall prevalence of vision loss in Australia was 6.6% (95% confidence interval [CI], 5.4-7.8). The prevalence of vision loss was 11.2% (95% CI, 9.5-13.1) in Indigenous Australians and 6.5% (95% CI, 5.3-7.9) in non-Indigenous Australians. Vision loss was 2.8 times more prevalent in Indigenous Australians than in non-Indigenous Australians after age and gender adjustment (17.7%, 95% CI, 14.5-21.0 vs. 6.4%, 95% CI, 5.2-7.6, P0.001). In non-Indigenous Australians, the leading causes of vision loss were uncorrected refractive error (61.3%), cataract (13.2%), and age-related macular degeneration (10.3%). In Indigenous Australians, the leading causes of vision loss were uncorrected refractive error (60.8%), cataract (20.1%), and diabetic retinopathy (5.2%). In non-Indigenous Australians, increasing age (odds ratio [OR], 1.72 per decade) and having not had an eye examination within the past year (OR, 1.61) were risk factors for vision loss. Risk factors in Indigenous Australians included older age (OR, 1.61 per decade), remoteness (OR, 2.02), gender (OR, 0.60 for men), and diabetes in combination with never having had an eye examination (OR, 14.47).Vision loss is more prevalent in Indigenous Australians than in non-Indigenous Australians, highlighting that improvements in eye healthcare in Indigenous communities are required. The leading causes of vision loss were uncorrected refractive error and cataract, which are readily treatable. Other countries with Indigenous communities may benefit from conducting similar surveys of Indigenous and non-Indigenous populations.

National data on eye health-care service utilization will inform Australia's eye health policy.To investigate the utilization of eye health-care services by Australians.Cross-sectional survey.Indigenous Australians aged 40 years and older and non-Indigenous Australians aged 50 years and older.One thousand seven hundred thirty-eight Indigenous Australians and 3098 non-Indigenous Australians were recruited from 30 randomly selected sites, stratified by remoteness. Sociodemographic, ocular history and eye health-care service utilization data were collected, and an eye examination was conducted.Recentness of eye examinations, types of providers used and associated risk factors.Approximately 67.0% of Indigenous Australians and 82.5% of non-Indigenous Australians underwent an eye examination within the previous 2 years. Indigenous status (P 0.001), male gender (P 0.001), Outer Regional (P 0.001) and Very Remote (P 0.001) residence were associated with less recent examinations. Participants withself-reported eye disease or diabetes were most likely to have been examined within the past year (P 0.001). For Indigenous Australians, older age was associated with recent eye testing (P = 0.001). Those with retinal disease and cataract were more likely to see an ophthalmologist (P 0.001), and those with refractive error were more likely to see an optometrist (P 0.001). In Regional Australia, non-Indigenouspeople were more likely to see optometrists (P 0.001), and Indigenous Australians were more likely to utilize other, non-specialistservices (P 0.001).Eye examination frequency has improved in Indigenous and non-Indigenous Australians compared with previous population-based research. Further improvements are required in risk groups including Indigenous Australians and those living in Regional and Remote areas.

OBJECTIVE: To determine cataract surgery coverage rates for Indigenous and non-Indigenous Australians. DESIGN: National cross-sectional population-based survey. SETTING: Thirty randomly selected Australian geographic sites, stratified by remoteness. PARTICIPANTS: 3098 non-Indigenous Australians aged 50 years or more and 1738 Indigenous Australians aged 40 years or more, recruited and examined in the National Eye Health Survey (NEHS) between March 2015 and April 2016. METHODS: Participants underwent an interviewer-administered questionnaire that collected socio-demographic information and past ocular care history, including cataract surgery. For those with visual acuity worse than 6/12, anterior segment photography and slit lamp examinations were conducted. MAIN OUTCOME MEASURES: Cataract surgery coverage rates according to WHO and NEHS definitions; associated risk factors. RESULTS: Cataract surgery coverage rates calculated with the NEHS definition 1 of vision impairment (visual acuity worse than 6/12) were lower for Indigenous than non-Indigenous participants (58.5% v 88.0%; odds ratio [OR], 0.32; P < 0.001). According to the World Health Organization definition (eligibility criterion: best-corrected visual acuity worse than 6/18), coverage rates were 92.5% and 98.9% for Indigenous and non-Indigenous Australians respectively. Greater age was significantly associated with higher cataract surgery coverage in Indigenous (OR, 1.41 per 10 years; P = 0.048) and non-Indigenous Australians (OR, 1.58 per 10 years; P = 0.004). CONCLUSIONS: The cataract surgery coverage rate was higher for non-Indigenous than Indigenous Australians, indicating the need to improve cataract surgery services for Indigenous Australians. The WHO definition of the coverage rate may overestimate the cataract surgery coverage rate in developed nations and should be applied with caution.

Purpose: to describe the methodology and present the retinal grading findings of an older sample of australians with well-defined indices of neurocognitive function in the Personality and total Health (PatH) through life project. Design: a cross-sectional study. Methods: three hundred twenty-six individuals from the PatH through life project were invited to participate. Participants completed a general questionnaire and 2-field, 45-degree nonmydriatic color digital retinal photography. Photographs were graded for retinal pathology according to established protocols. Results: two hundred fifty-four (77.9%) subjects, aged 72 to 78 years, agreed to participate in the eye substudy. gradable images of at least 1 eye were acquired in 211 of 254 subjects (83.1%). retinal photographic screening identified 1 or more signs of pathology in 130 of the 174 subjects (74.7%) with gradable images of both eyes. a total of 45 participants (17.7%) had self-reported diabetes and diabetic retinopathy was observed in 22 (48.9%) of these participants. Conclusions: this well-defined sample of older australians provides a unique opportunity to interrogate associations between retinal findings, including retinal vascular geometric parameters, and indices of neurocognitive function.

To determine the prevalence of and factors associated with diabetic retinopathy (DR) among non-Indigenous and Indigenous Australian adults with self-reported diabetes.Population-based cross-sectional study.Non-Indigenous Australians (50-98 years of age) and Indigenous Australians (40-92 years of age) with known diabetes.Diabetes was determined based on self-report of previous diagnosis of the disease. Nonmydriatic fundus photographs were obtained of each eye and graded according to the modified Airlie House classification system.Any DR, vision-threatening DR (VTDR), treatment coverage rates (proportion of participants with proliferative DR [PDR], clinically significant macular edema [CSME], or both who had evidence of retinal scatter and focal laser treatment).Four hundred thirty-one non-Indigenous Australians (13.9%) and 645 Indigenous Australians (37.1%) self-reported diabetes, of whom 93% (1004/1076) had retinal images that were gradable for DR. The sampling weight-adjusted prevalence of any DR and VTDR among non-Indigenous adults with self-reported diabetes was 28.5% (95% confidence interval [CI], 22.6-35.3) and 4.5% (95% CI, 2.6-7.9), respectively. Among adults 40 years of age and older, the sampling weight-adjusted prevalence of any DR and VTDR was 39.4% (95% CI, 33.1-46.1) and 9.5% (95% CI, 6.8-13.1), respectively. Longer diabetes duration was associated significantly with VTDR in the Indigenous Australian population (odds ratio [OR], 1.08 per 1-year increase; P = 0.005) and non-Indigenous Australian population (OR, 1.05 per 1-year increase; P = 0.03). The treatment coverage of PDR and CSME was 75% (56/75) in Indigenous Australians and 79% (15/19) in non-Indigenous Australians. Diabetic retinopathy was attributed as the main cause of vision loss (6/12 in the better eye) in 9% and 19% of non-Indigenous and Indigenous Australian adults with known diabetes, respectively.Three quarters of non-Indigenous and Indigenous Australian adults with PDR or CSME have received laser treatment. The prevalence of VTDR in Indigenous and non-Indigenous Australians in the present study was lower than that found in previous population-based reports, nevertheless, approximately 1 in 10 Indigenous adults with known diabetes experience VTDR. This highlights that intensified prevention strategies are required to delay or prevent avoidable vision loss resulting from DR in Indigenous Australian communities.

The number of people with myopia is expected to rise from 1.950 billion in 2010 to 4.758 billion by 2050.1 In Asia, the prevalence of myopia in teenagers has been reported to be as high as 96.5%.2 One study demonstrated that 11% of Singaporean preschoolers were already myopic, placing them at a significantly higher risk of developing high myopia and myopic macular degeneration.3 This myopia ‘epidemic’ has become a profound public health concern. In Singapore, the direct cost of managing myopia was estimated at US$755 million annually, and globally at US$328 billion per year.4 It is now thought that because of the rapid increase in the prevalence of myopia in under one generation, environmental factors perhaps play a greater role in its development than our genes. Environmental risk factors include urbanisation, higher educational attainment, higher IQ, but more important has been two consistent risk factors: increased near-work activity and reduced outdoor activity.5 Studies often quantify near-work activity by the number of books …

The study aimed to determine the prevalence of and risk factors for self-reported stroke in Indigenous and non-Indigenous Australians.In this national eye study, 1738 Indigenous Australians (41.1% male) aged 40-92 years and 3098 non-Indigenous Australians (46.4% male) aged 50-98 years from 30 randomly selected sites, stratified by remoteness, were recruited and examined. Sociodemographic information and a history of stroke, diabetes, and ocular health were obtained using an interviewer-administered questionnaire.The crude prevalence of self-reported stroke was 5.04% (156 of 3098, 95% confidence interval: 4.29%-5.87%) for non-Indigenous Australians and 8.75% (152 of 1738, 95% confidence interval: 7.46%-10.17%) for Indigenous Australians (P .0001). The age-adjusted prevalence of self-reported stroke for non-Indigenous and Indigenous Australians was 4.23% and 12.72%, respectively. The prevalence of stroke increased significantly with age for both Indigenous (odds ratio = 1.06 per year, P ≤ .001) and non-Indigenous Australians (odds ratio = 1.04 per year, P ≤ .001), with the Indigenous prevalence being higher than that of the non-Indigenous group at every age.The prevalence of self-reported stroke was 3 times higher in Indigenous Australians than in non-Indigenous Australians. This disparity is consistent with previous reports, highlighting the need for intensified prevention and support services to reduce the burden of stroke on Indigenous Australians.

This paper presents the sampling methodology of the National Eye Health Survey that aimed to determine the prevalence of vision impairment and blindness in Australia.The National Eye Health Survey is a cross-sectional population-based survey.Indigenous Australians aged 40 years and older and non-Indigenous Australians aged 50 years and older residing in all levels of geographic remoteness in Australia.Using multistage, random-cluster sampling, 30 geographic areas were selected to provide samples of 3000 non-Indigenous Australians and 1400 Indigenous Australians. Sampling involved (i) selecting Statistical Area- Level 2 sites, stratified by remoteness; (ii) selecting Statistical Area- Level 1 sites within Statistical Area- Level 2 sites to provide targeted samples; and (iii) grouping of contiguous Statistical Area- Level 1 sites or replacing Statistical Area- Level 1 sites to provide sufficient samples.The main outcome measures involved Sites sites selected and participants sampled in the survey.Thirty sites were generated, including 12 Major City sites, 6 Inner Regional sites, 6 Outer Regional sites, 4 Remote sites and 2 Very Remote sites. Three thousand ninety-eight non-Indigenous participants and 1738 Indigenous participants were recruited. Selection of Statistical Area- Level 1 site overestimated the number of eligible residents in all sites. About 20% (6/30) of Statistical Area- Level 1 sites were situated in non-residential bushland, and 26.67% (8/30) of Statistical Area- Level 1 populations had low eligibility or accessibility, requiring replacement.Representative samples of Indigenous and non-Indigenous Australians were selected, recruited and tested, providing the first national data on the prevalence of vision impairment and blindness in Australia.