Association between body mass index and diabetic retinopathy in Asians: the Asian Eye Epidemiology Consortium (AEEC) study

The causal relationship between immune cells and diabetic retinopathy: a Mendelian randomization study

Purpose

This article explored the causal relationship between immune cells and diabetic retinopathy (DR) using single nucleotide polymorphisms (SNPs) as an instrumental variable and Mendelian randomization (MR).

Methods

Statistical data were collected from a publicly available genome-wide association study (GWAS), and SNPs that were significantly associated with immune cells were used as instrumental variables (IVs). Inverse variance weighted (IVW) and MR-Egger regression were used for MR analysis. A sensitivity analysis was used to test the heterogeneity, horizontal pleiotropy, and stability of the results.

Results

We investigated the causal relationship between 731 immune cells and DR risk. All the GWAS data were obtained from European populations and from men and women. The IVW analysis revealed that HLA DR on CD14+ CD16- monocytes, HLA DR on CD14+ monocytes, HLA DR on CD33-HLA DR+, HLA DR on CD33+ HLA DR+ CD14- on CD33+ HLA DR+ CD14dim, and HLA DR on myeloid dendritic cells may increase the risk of DR (P<0.05). HLA DR to CD14-CD16- cells, the monocytic myeloid-derived suppressor cell absolute count, the SSC-A count of CD4+ T cells, and terminally differentiated CD4+ T cells may be protective factors against DR (P<0.05). The sensitivity analysis indicated no heterogeneity or pleiotropy among the selected SNPs. Furthermore, gene annotation of the SNPs revealed significant associations with 10 genes related to the risk of developing PDR and potential connections with 12 other genes related to PDR.

Conclusion

Monocytes and T cells may serve as new biomarkers or therapeutic targets, leading to the development of new treatment options for managing DR.

Type 2 diabetes: is obesity for diabetic retinopathy good or bad? A cross-sectional study

BACKGROUND

The relationship between obesity and diabetic retinopathy (DR) remains controversial, and the relationship between sarcopenic obesity and DR is still unclear. The purpose of this study is to investigate the relationship between obesity, sarcopenic obesity, and DR in patients with type 2 diabetes mellitus (T2DM).

METHODS

A cross-sectional study was conducted on patients with T2DM. Obesity was assessed by body mass index (BMI), fat mass index (FMI), android fat mass, gynoid fat mass, and visceral adipose tissue (VAT) mass. Sarcopenia was defined according to the criteria of Consensus of the Asian Working Group for Sarcopenia (AWGS 2019). Sarcopenic obesity was defined as the coexistence of sarcopenia and obesity. The association between obesity, sarcopenic obesity, and DR was examined using univariable and multivariable logistic regression models.

RESULTS

A total of 367 patients with T2DM (mean age 58.3 years; 57.6% male) were involved in this study. The prevalence of DR was 28.3%. In total patients, significant adverse relationships between obesity and DR were observed when obesity was assessed by BMI (adjusted odds ratio [aOR] 0.54, 95% confidence interval [CI] 0.31 to 0.96, p = 0.036), FMI (aOR 0.49, 95% CI 0.28 to 0.85, p = 0.012), android fat mass (aOR 0.51, 95% CI 0.29 to 0.89, p = 0.019), gynoid fat mass (aOR 0.52, 95% CI 0.30 to 0.91, p = 0.021) or VAT mass (aOR 0.45, 95% CI 0.25 to 0.78, p = 0.005). In patients with T2DM and obesity, the prevalence of sarcopenic obesity was 14.8% (n = 23) when obesity was assessed by BMI, 30.6% (n = 56) when assessed by FMI, 27.9% (n = 51) when assessed by android fat mass, 28.4% (n = 52) when assessed by gynoid fat mass, and 30.6% (n = 56) when assessed by VAT mass. Sarcopenic obesity was associated with DR when obesity was assessed by BMI (aOR 2.61, 95% CI 1.07 to 6.37, p = 0.035), android fat mass (aOR 3.27, 95% CI 1.37 to 7.80, p = 0.007), or VAT mass (aOR 2.50, 95% CI 1.06 to 5.92, p = 0.037).

CONCLUSIONS

Patients with T2DM showed a substantial inverse relationship between DR and obesity, and sarcopenic obesity was considerably favorably associated with DR. Detection of sarcopenia in patients with T2DM, especially in obese T2DM, is essential to guide clinical intervention in DR.

Investigating the causal association of generalized and abdominal obesity with microvascular complications in patients with type 2 diabetes: A community-based prospective study

AIM

The paradoxical protective association between overweight/obesity and diabetic microvascular complications (DMC), a phenomenon well-known as the obesity paradox, has been considered a non-causal association based on methodological influences. We aimed to investigate the association of generalized and abdominal obesity, as measured by body mass index (BMI) and waist circumference (WC), respectively, with DMC in patients with type 2 diabetes (T2D), using a causal inference approach.

MATERIALS AND METHODS

We enrolled 1436 patients with clinically diagnosed T2D but not DMC at baseline in a community-based prospective cohort in China between 2017 and 2019 and followed them annually until 2022 with new-onset DMC recorded. Marginal structural Cox models with inverse probability weighting were constructed to determine the causal association. Subgroup analyses were performed to identify potential effect modifiers.

RESULTS

We observed 360 incident DMC cases, including 109 cases of diabetic nephropathy (DN) and 277 cases of diabetic retinopathy (DR) during four follow-up visits. Multivariable-adjusted hazard ratios (95% confidence intervals) for overall DMC, DN and DR were 1.037 (1.005-1.071), 1.117 (1.062-1.175) and 1.018 (0.980-1.059) for 1 kg/m2 increase in BMI, and 1.005 (0.994-1.017), 1.034 (1.018-1.051) and 1.000 (0.987-1.014) for 1 cm increase in WC, respectively. Similar patterns were observed across the BMI and WC categories, while the positive association appeared to be more pronounced in women.

CONCLUSIONS

Generalized but not abdominal obesity was associated with an increased risk for the overall DMC, whereas both obesities were causally related to DN, albeit not DR, in T2D. Routine weight management should not be neglected in diabetes care, particularly in women.

Is Kidney Function Associated with Age-Related Macular Degeneration?: Findings from the Asian Eye Epidemiology Consortium

PURPOSE

Chronic kidney disease (CKD) may elevate susceptibility to age-related macular degeneration (AMD) because of shared risk factors, pathogenic mechanisms, and genetic polymorphisms. Given the inconclusive findings in prior studies, we investigated this association using extensive datasets in the Asian Eye Epidemiology Consortium.

DESIGN

Cross-sectional study.

PARTICIPANTS

Fifty-one thousand two hundred fifty-three participants from 10 distinct population-based Asian studies.

METHODS

Age-related macular degeneration was defined using the Wisconsin Age-Related Maculopathy Grading System, the International Age-Related Maculopathy Epidemiological Study Group Classification, or the Beckman Clinical Classification. Chronic kidney disease was defined as estimated glomerular filtration rate (eGFR) of less than 60 ml/min per 1.73 m2. A pooled analysis using individual-level participant data was performed to examine the associations between CKD and eGFR with AMD (early and late), adjusting for age, sex, hypertension, diabetes, body mass index, smoking status, total cholesterol, and study groups.

MAIN OUTCOME MEASURES

Odds ratio (OR) of early and late AMD.

RESULTS

Among 51 253 participants (mean age, 54.1 ± 14.5 years), 5079 had CKD (9.9%). The prevalence of early AMD was 9.0%, and that of late AMD was 0.71%. After adjusting for confounders, individuals with CKD were associated with higher odds of late AMD (OR, 1.46; 95% confidence interval [CI], 1.11-1.93; P = 0.008). Similarly, poorer kidney function (per 10-unit eGFR decrease) was associated with late AMD (OR, 1.12; 95% CI, 1.05-1.19; P = 0.001). Nevertheless, CKD and eGFR were not associated significantly with early AMD (all P ≥ 0.149).

CONCLUSIONS

Pooled analysis from 10 distinct Asian population-based studies revealed that CKD and compromised kidney function are associated significantly with late AMD. This finding further underscores the importance of ocular examinations in patients with CKD.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Transition probabilities of diabetic retinopathy and death in an Asian population with diabetes

PURPOSE

To evaluate the dynamic transitions in diabetic retinopathy (DR) severity over time and associated risk factors in an Asian population with diabetes.

DESIGN

Longitudinal cohort study METHODS: We analyzed data from 9481 adults in the Singapore Integrated Diabetic Retinopathy Screening Program (2010-2015) with linkage to death registry. A multistate Markov model adjusted for age, sex, systolic blood pressure (SBP), diabetes duration, HbA1c, and body mass index (BMI) was applied to estimate annual transition probabilities between four DR states (no, mild, moderate, and severe/proliferative) and death, and the mean sojourn time in each state.

RESULTS

The median assessment interval was 12 months, with most patients having 3 assessments. Annual probabilities for DR progression (no-to-mild, mild-to-moderate and moderate-to-severe/proliferative) were 6.1 %, 7.0 % and 19.3 %, respectively; and for regression (mild-to-no, moderate-to-mild and severe-to-moderate) were 55.4 %, 17.3 % and 4.4 %, respectively. Annual mortality rates from each DR state were 1.2 %, 2.0 %, 18.7 %, and 30.0 %. The sojourn time in each state were 8.2, 0.8, 0.8 and 2.2 years. Higher HbA1c and SBP levels were associated with progression of no-mild and mild-moderate DR, and diabetes duration with no-to-mild and moderate-to-severe/proliferative DR. Lower HbA1c levels were associated with regression from mild-to-no and moderate-to-mild, and higher BMI with mild-to-no DR.

CONCLUSIONS

Our results suggest a prolonged duration (∼8 years) in developing mild DR, with faster transitions (within a year) from mild or moderate states. Moderate/above DR greatly increases the probability of progression and death as compared to mild DR/below. HbA1c was associated with both progression as well as regression.

Association of Visceral Obesity Indices With Incident Diabetic Retinopathy in Patients With Diabetes: Prospective Cohort Study

BACKGROUND

Visceral adipose tissue plays an active role in the pathogenesis of type 2 diabetes and vascular dysfunction. The lipid accumulation product (LAP), visceral adiposity index (VAI), and Chinese VAI (CVAI) have been proposed as simple and validated surrogate indices for measuring visceral adipose tissue. However, the evidence from prospective studies on the associations between these novel indices of visceral obesity and diabetic retinopathy (DR) remains scant.

OBJECTIVE

This study aimed to investigate the longitudinal associations of LAP, VAI, and CVAI with incident DR in Chinese patients with diabetes.

METHODS

This was a prospective cohort study conducted in Guangzhou in southern China. We collected baseline data between November 2017 and July 2020, while on-site follow-up visits were conducted annually until January 2022. The study participants consisted of 1403 patients with a clinical diagnosis of diabetes, referred from primary care, who were free of DR at baseline. The LAP, VAI, and CVAI levels were calculated by sex-specific equations based on anthropometric and biochemical parameters. DR was assessed using 7-field color stereoscopic fundus photographs and graded according to the modified Airlie House Classification scheme. Time-dependent Cox proportional hazard models were constructed to estimate the hazard ratios with 95% CIs. Restricted cubic spline curves were fitted to examine the dose-response relationship between the 3 indices of visceral obesity and new-onset DR. Subgroup analyses were performed to investigate the potential effect modifiers.

RESULTS

The mean age of study participants was 64.5 (SD 7.6) years, and over half (816/1403, 58.2%) were female. During a median follow-up of 2.13 years, 406 DR events were observed. A 1-SD increment in LAP, VAI, or CVAI was consistently associated with increased risk for new-onset DR, with a multivariable‑adjusted hazard ratio of 1.24 (95% CI 1.09-1.41; P=.001), 1.22 (95% CI 1.09-1.36; P<.001), and 1.48 (95% CI 1.19-1.85; P=.001), respectively. Similar patterns were observed across tertiles in LAP (P for trend=.001), VAI (P for trend<.001), and CVAI (P for trend=.009). Patients in the highest tertile of LAP, VAI, and CVAI had an 84%, 86%, and 82% higher hazard of DR, respectively, compared to those in the lowest tertile. A nonlinear dose-response relationship with incident DR was noted for LAP and VAI (both P for nonlinearity<.05), but not for CVAI (P for nonlinearity=.51). We did not detect the presence of effect modification by age, sex, duration of diabetes, BMI, or comorbidity (all P for interaction>.10).

CONCLUSIONS

Visceral obesity, as measured by LAP, VAI, or CVAI, is independently associated with increased risk for new-onset DR in Chinese patients with diabetes. Our findings may suggest the necessity of incorporating regular monitoring of visceral obesity indices into routine clinical practice to enhance population-based prevention for DR.

Machine Learning-Based Diagnosis and Ranking of Risk Factors for Diabetic Retinopathy in Population-Based Studies from South India

This paper discusses the importance of investigating DR using machine learning and a computational method to rank DR risk factors by importance using different machine learning models. The dataset was collected from four large population-based studies conducted in India between 2001 and 2010 on the prevalence of DR and its risk factors. We deployed different machine learning models on the dataset to rank the importance of the variables (risk factors). The study uses a t-test and Shapely additive explanations (SHAP) to rank the risk factors. Then, it uses five machine learning models (K-Nearest Neighbor, Decision Tree, Support Vector Machines, Logistic Regression, and Naive Bayes) to identify the unimportant risk factors based on the area under the curve criterion to predict DR. To determine the overall significance of risk variables, a weighted average of each classifier's importance is used. The ranking of risk variables is provided to machine learning models. To construct a model for DR prediction, the combination of risk factors with the highest AUC is chosen. The results show that the risk factors glycosylated hemoglobin and systolic blood pressure were present in the top three risk factors for DR in all five machine learning models when the t-test was used for ranking. Furthermore, the risk factors, namely, systolic blood pressure and history of hypertension, were present in the top five risk factors for DR in all the machine learning models when SHAP was used for ranking. Finally, when an ensemble of the five machine learning models was employed, independently with both the t-test and SHAP, systolic blood pressure and diabetes mellitus duration were present in the top four risk factors for diabetic retinopathy. Decision Tree and K-Nearest Neighbor resulted in the highest AUCs of 0.79 (t-test) and 0.77 (SHAP). Moreover, K-Nearest Neighbor predicted DR with 82.6% (t-test) and 78.3% (SHAP) accuracy.

Application of big data in ophthalmology

The advents of information technologies have led to the creation of ever-larger datasets. Also known as big data, these large datasets are characterized by its volume, variety, velocity, veracity, and value. More importantly, big data has the potential to expand traditional research capabilities, inform clinical practice based on real-world data, and improve the health system and service delivery. This review first identified the different sources of big data in ophthalmology, including electronic medical records, data registries, research consortia, administrative databases, and biobanks. Then, we provided an in-depth look at how big data analytics have been applied in ophthalmology for disease surveillance, and evaluation on disease associations, detection, management, and prognostication. Finally, we discussed the challenges involved in big data analytics, such as data suitability and quality, data security, and analytical methodologies.

Neutrophil–lymphocyte ratio as a reliable marker to predict pre-clinical retinopathy among type 2 diabetic patients

Background

Diabetic retinopathy is now recognized as a neurovascular in lieu of a microvascular complication. Visual evoked potentials (VEPs) are greatly valuable in detecting early diabetic retinal functional changes before the occurrence of structural damage. Low-grade inflammation plays a fundamental part in the development and progression of retinopathy in diabetics. Detecting diabetic patients with early retinopathy before the occurrence of clinical symptoms provides a window of opportunity to ensure the best prognosis for these eyes. Neutrophil–lymphocyte ratio (NLR) has recently been introduced as a novel marker of inflammation in various diseases. Indeed, the presence of a cheap, available, and reliable marker of inflammation that is capable to detect pre-clinical diabetic retinopathy (P-DR) is crucial for early intervention to retard the progression of ocular damage. As far as we know no previous studies investigated the role of NLR in the detection of P-DR. The aim of this study was to investigate the quality of prediction of NLR in detecting pre-clinical retinopathy in type 2 diabetic patients.

Results

In this case–control study, VEPs results showed a significant delay in P100 latencies of the patients’ group compared to the control group. According to the VEPs results, the patient group was further subdivided into two: diabetic with VEPs changes (a group with P-DR) and diabetic without VEPs changes. NLR was significantly elevated in patients with P-DR (p < 0.001). NLR cut-off point ≥ 1.97 is able to predict P-DR with 89.29% sensitivity and 84.37% specificity. Linear regression model revealed that NLR is the only independent factor that predicts P-DR. (odds ratio 3.312; 95% confidence interval 1.262–8.696, p = 0.015*.

Conclusions

Visual evoked potentials have an important role to evaluate the visual pathway in diabetics and to diagnose pre-clinical diabetic retinopathy before the occurrence of structural damage. Neutrophil–lymphocyte ratio is a reliable marker for the detection of pre-clinical diabetic retinopathy with good sensitivity (89.29%) and specificity (84.37%). Finding a reliable available laboratory test to predict P-DR could be of help to save diabetic patients from serious ocular complications.

Association of anthropometric parameters as a risk factor for development of diabetic retinopathy in patients with diabetes mellitus

OBJECTIVE

To study the relationship of body fat distribution in patients with diabetes mellitus (DM), and its long-term complications like diabetic retinopathy (DR), in Indian population.

METHODS

This was a prospective, cross-sectional observational study involving 1773 subjects diagnosed with DM and 1778 age and gender-matched individuals. The patients with DM were assessed for the presence and severity of DR. Severe non-proliferative DR and proliferative DR were categorised as sight threatening DR (STDR). Anthropometric parameters, i.e., neck circumference (NC); mid-upper arm circumference (MAC); waist circumference (WC); hip circumference (HC); mid-thigh circumference (MTC) and body mass index (BMI) were measured using standardised technique.

RESULTS

The mean age was 59.33 ± 9.32 for DM group, and 66.03 ± 11.04 for non-DM group. DM group showed significantly greater NC, WC, and MTC and significantly reduced MAC and weight. HC and BMI were comparable between the groups. There was a significant positive correlation of MAC and WC (with any level of DR) and MAC, WC, and weight (for STDR); and a significant negative correlation of HC and MTC (with any level of DR) and NC, HC, MTC, and BMI (for STDR). Multiple logistic regression analysis confirmed that WC was the single most important predictor for any level of DR and STDR.

CONCLUSIONS

Association of body fat distribution with DM and DR appears multifactorial. However, central obesity signified by waist circumference appears to be the significant risk related to the development of DR and STDR in Indian population.

Association of Obesity Indices with Diabetic Kidney Disease and Diabetic Retinopathy in Type 2 Diabetes: A Real-World Study

Background

Diabetic microvascular complications mainly include diabetic kidney disease (DKD) and diabetic retinopathy (DR). Obesity was recognized as a risk factor for DKD, while the reported relationship between obesity and DR was inconsistent. Moreover, whether the associations can be attributed to C-peptide levels is unknown.

Methods

Data from 1142 sequential inpatients with T2DM at Xiangyang Central Hospital between June 2019 and March 2022 were extracted retrospectively from the electronic medical record system. The associations between four obesity indices (body mass index (BMI), waist-hip circumference ratio (WHR), visceral fat tissue area (VFA), and subcutaneous fat tissue area (SFA)) and DKD and DR were evaluated. Whether the associations can be attributed to C-peptide levels was also explored.

Results

Obesity was a risk factor for DKD after adjusting for sex, HbA1c, TG, TC, HDL, LDL, smoking history, education, duration of diabetes, and insulin use (obesity indices: BMI (OR 1.050: 95% CI: 1.008-1.094; P = 0.020); WHR (OR 10.97; 95% CI: 1.250-92.267; P = 0.031); VFA (OR 1.005; 95% CI: 1.001-1.008; P = 0.008)), but it became insignificant after further adjusting for fasting C-peptide. The associations between BMI, WHR, VFA, and DKD might be U-shaped. Obesity and FCP tended to protect against DR; however, they became insignificant after adjusting for multiple potential confounders. C2/C0 (the ratio of the postprandial serum C-peptide to fasting C-peptide) was a protective factor for both DKD (OR 0.894, 95% CI: 0.833-0.959, P < 0.05) and DR (OR 0.851, 95% CI: 0.787-0.919; P < 0.05).

Conclusions

Obesity was a risk factor for DKD, and the effect may be attributable to C-peptide, which represents insulin resistance. The protective effect of obesity or C-peptide on DR was not independent and could be confounded by multiple factors. Higher C2/C0 was associated with both decreased DKD and DR.

Impact of Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) GFR Estimating Equations on CKD Prevalence and Classification Among Asians

Background

In 2021, the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) validated a new equation for estimated glomerular filtration rate (eGFR). However, this new equation is not ethnic-specific, and prevalence of CKD in Asians is known to differ from other ethnicities. This study evaluates the impact of the 2009 and 2021 creatinine-based eGFR equations on the prevalence of CKD in multiple Asian cohorts.

Methods

Eight population-based studies from China, India, Russia (Asian), Singapore and South Korea provided individual-level data (n = 67,233). GFR was estimated using both the 2009 CKD-EPI equation developed using creatinine, age, sex, and race (eGFRcr [2009, ASR]) and the 2021 CKD-EPI equation developed without race (eGFRcr [2021, AS]). CKD was defined as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73m2 (G3-G5). Prevalence of eGFR categories was compared within each study and within subgroups of age, sex, body mass index (BMI), diabetes, and hypertension status. The extent of reclassification was examined using net reclassification improvement (NRI).

Findings

Of 67,233 adults, CKD prevalence was 8.6% (n = 5800/67,233) using eGFRcr (2009, ASR) and 6.4% (n = 4307/67,233) using eGFRcr (2021, AS). With the latter, CKD prevalence was reduced across all eight studies, ranging from −7.0% (95% CI −8.5% to −5.4%) to −0.4% (−1.3% to 0.5%), and across all subgroups except those in the BMI < 18.5% subgroup. Net reclassification index (NRI) was significant at −2.33% (p < 0.001). No individuals were reclassified as a higher (more severe) eGFR category, while 1.7%−4.2% of individuals with CKD were reclassified as one eGFR category lower when eGFRcr (2021, AS) rather than eGFRcr (2009, ASR) was used.

Interpretation

eGFRcr (2021, AS) consistently provided reduced CKD prevalence and higher estimation of GFR among Asian cohorts than eGFRcr (2009, ASR). Based on current risk-stratified approaches to CKD management, more patients reclassified to lower-risk GFR categories could help reduce inappropriate care and its associated adverse effects among Asian renal patients. Comparison of both equations to predict progression to renal failure or adverse outcomes using prospective studies are warranted.

Funding

National Medical Research Council, Singapore.

Geriatric nutritional risk index is associated with retinopathy in patients with type 2 diabetes

The geriatric nutritional risk index (GNRI) is a nutrition-related risk assessment tool and has been used in various clinical settings. The relationship between body mass index (BMI) and the associated risk of diabetic retinopathy (DR) remains inconclusive. We aimed to evaluate the association between GNRI and DR in patients with type 2 diabetes. We included a total of 1359 patients with type 2 diabetes who followed up in our diabetes clinic and underwent fundus photographic examinations from August 2006 to February 2014. DR was assessed by retinal ophthalmologists using comprehensive ophthalmologic examinations. Patients were divided into tertiles according to their GNRI category. Patients in a lower GNRI tertile tended to have a higher proportion of nonproliferative DR (NPDR) and proliferative DR (PDR) compared with those in the other tertiles. The risk of PDR was higher in patients included in GNRI tertile 1 (Odds ratio (OR) 2.252, 95% Confidence Interval (CI) 1.080–4.823, P = 0.033) and GNRI tertile 2 (OR 2.602, 95% CI 1.323–5.336, P = 0.007) compared with those in GNRI tertile 3. In patients with lower GNRIs, the prevalence of DR was higher than in those with higher GNRIs. When GNRI was compared with BMI using the area under the curve, overall accuracy was high in GNRI. The risk of PDR was high in patients with low GNRI and there is an inverse association between GNRI scores and prevalence of DR. GNRI might be a useful tool to predict DR in patients with type 2 diabetes.

Retinal Nerve Fiber Layer Thickness and Rim Area Profiles in Asians: Pooled Analysis from the Asian Eye Epidemiology Consortium

PURPOSE

To evaluate ethnic variations, ocular and systemic determinants of retinal nerve fibre layer (RNFL) thickness and neuroretinal rim area among Asians, using a large consortium of population-based eye studies.

DESIGN

Cross-sectional pooled-analysis.

PARTICIPANTS

22436 participants (22436 eyes) from 10 population-based studies (China, Hong Kong, India, Japan, Russia and Singapore) of the Asian Eye Epidemiology Consortium.

METHODS

Participants aged ≥40 years without glaucoma were included. All participants underwent spectral domain optical coherence tomography (OCT) imaging, systemic and ocular examinations. Data were pooled from each study. Multivariable regression analysis was performed to evaluate inter-ethnic, inter-machine variations, ocular and systemic factors associated with RNFL thickness and rim area, adjusting for age, gender, diabetes, intraocular pressure (IOP), spherical equivalent (SE), ethnicity, OCT model, and study group. When evaluating body mass index, smoking, and hypertension as exposures, these factors were additionally adjusted in the model.

MAIN OUTCOME MEASURE

Average RNFL thickness (μm) and rim area (mm²) RESULTS: Indian and Japanese eyes showed thinner RNFL, compared to other Asian ethnicities (β values ranging 7.31-12.76μm, P<0.001 for all pair-wise comparisons). Compared to measurements by Cirrus HD-OCT, RNFL was on average 7.29μm thicker when measured by Spectralis, 12.85μm thicker by Nidek, and 17.48μm thicker by Optovue (all P<0.001). Additionally, older age (per decade, β=-2.70; 95% confidence interval [CI], -2.85 to -2.55), diabetes (β=-0.72; 95%CI, -1.20 to -0.24), ), higher IOP (per mmHg, β=-0.07; 95% CI, -0.10 to -0.04), more myopic SE (per dioptre, β=-1.13; 95% CI, -1.19 to -1.07), cardiovascular disease (CVD, β=-0.94; 95% CI, -1.49 to -0.40), and hypertension (β=-0.68; 95% CI, -1.04 to -0.32), were associated with thinner RNFL (all P≤0.003). Similarly, older age (β=-0.019; 95% CI, -0.028 to -0.009), higher IOP (β=-0.010; 95% CI, -0.013 to -0.008) and more myopic SE (β=-0.025; 95% CI, -0.029 to -0.021) were associated with smaller rim area (all P<0.001).

CONCLUSIONS

In this large pooled-analysis of multiple Asian population studies, Indian and Japanese eyes were observed to have thinner RNFL profiles. In addition to previously known determinants, hypertension and CVD were associated with thinner RNFL. These findings further suggest the need of ethnic-specific normative database to improve glaucoma detection.

Prevalence and Associated Factors of Diabetic Retinopathy in a Russian Population. The Ural Eye and Medical Study

AIM

To assess prevalence and associated factors of diabetic retinopathy (DR) in a Russian population.

METHODS

Out of 7328 eligible individuals, the population-based cross-sectional Ural Eye and Medical Study included 5899 (80.5%) individuals aged 40+ years, who underwent a detailed medical and ophthalmological examination. Using ocular fundus photographs and optical coherence tomographic images, we assessed prevalence and degree of DR in 5105 participants.

RESULTS

DR was present in 99/5105 individuals (1.9%; 95% confidence interval [CI]: 1.6, 2.3). Its prevalence increased from 6/657 (1.0%; 95% CI: 0.2, 1.6) in the age group of 45-50 years to 24/680 (3.5%; 95% CI: 2.1, 4.9) in the age group of 65-70 years, and decreased to 3/153 (2.0%; 95% CI: 0.00, 4.2) in the age group of 80+ years. DR prevalence within the 577 (11.4%; 95% CI: 10.5, 12.2) individuals with diabetes was 99/577 (17.2%; 95% CI: 14.1, 20.2). DR was the cause for moderate-to-severe vision impairment (best corrected visual acuity <6/18 but ≥3/60) in four individuals (4/5105; 0.07%). In multivariable analysis, higher DR prevalence was associated with higher serum glucose concentration (odds ratio [OR]: 1.30; 95% CI: 1.20, 141), longer diabetes duration (OR: 1.06; 95% CI: 1.02, 1.09), type of diabetes therapy (nil/diet/oral/insulin) (OR:4.19;95% CI:3.08, 5.70), lower educational level (OR:0.81;95% CI:0.67, 0.98), lower manual dynamometric force (OR: 0.96; 95% CI: 0.94, 0.99), shorter ocular axial length (OR: 0.73; 95% CI: 0.56, 0.96), and higher diastolic blood pressure (OR: 1.04; 95% CI: 1.01, 1.06), or alternatively, higher estimated cerebrospinal fluid pressure (OR: 1.09; 95% CI: 1.01, 1.18).

CONCLUSION

In this urban and rural Russian population aged 40+ years, DR prevalence was relatively low (1.9%; 95% CI: 1.6, 2.3), showed an inverted U-shaped association with age, and in a cross-sectional study design it was associated with shorter axial length and higher estimated cerebrospinal fluid pressure.