Does daily dietary intake affect diabetic retinopathy progression? 10-year results from the 45 and Up Study

Inter-Relations between Dietary Patterns and Glycemic Control-Related Biomarkers on Risk of Retinopathy in Type 2 Diabetes

Diabetic retinopathy (DR), which can cause vision loss, may progress faster with poor glycemic control and oxidative stress. This study aims to examine how dietary patterns and glycemic control biomarkers relate to retinopathy risk in type 2 diabetes patients. In this study, we enrolled diabetic patients with retinopathy (DR) (n = 136) and without retinopathy (no DR) (n = 466) from a cohort of participants in the "Blood Pressure Control to Reduce the Risk of Type 2 Diabetic Nephropathy Study". Hemoglobin A1c (HbA1c) and malondialdehyde were defined as elevated when their levels reached ≥8.5% and ≥2/3 (16.2 μm), respectively. Dietary data were collected by a food frequency questionnaire. Dietary patterns were identified by factor analysis. Elevated HbA1c was significantly correlated with increased risk of DR (OR: 2.12, 95% CI: 1.14-3.93, p = 0.017). In subjects with a high animal protein and processed food dietary pattern (≥highest tertile score) or a low vegetable intake pattern ( Collapse

Key Words

• diabetic retinopathy
• glycated hemoglobin A1c
• malondialdehyde

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MESH Headings

• Humans
• Diabetes Mellitus, Type 2/blood
• Diabetes Mellitus, Type 2/complications
• Male
• Diabetic Retinopathy/etiology
• Diabetic Retinopathy/epidemiology
• Diabetic Retinopathy/blood
• Female
• Middle Aged
• Biomarkers/blood
• Glycated Hemoglobin/analysis
• Glycated Hemoglobin/metabolism
• Diet/adverse effects
• Risk Factors
• Aged
• Glycemic Control
• Malondialdehyde/blood
• Blood Glucose/metabolism
• Feeding Behavior
• Dietary Patterns

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Grants

• 112-2320-B-037-018 National Science and Technology Council, Taiwan
• KMUH-108-8R78 Kaohsiung Medical University Hospital

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Affiliation(s)

Yu-Ju Wu Department of Nutrition and Dietetics, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807378, Taiwan; Graduate Institute of Medicine and Department of Public Health and Environmental Medicine, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807378, Taiwan;
Chih-Cheng Hsu Institute of Population Health Sciences, National Health Research Institutes, Miaoli County 350401, Taiwan; (C.-C.H.); (Y.-F.H.) Department of Health Services Administration, China Medical University, Taichung 4064040, Taiwan Department of Family Medicine, Min-Sheng General Hospital, Taoyuan 330056, Taiwan National Center for Geriatrics and Welfare Research, National Health Research Institutes, Yunlin 632007, Taiwan
Shang-Jyh Hwang Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807378, Taiwan; Division of Endocrinology and Metabolism, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807378, Taiwan;
Kun-Der Lin The Lin’s Clinics, Kaohsiung 807057, Taiwan;
Pi-Chen Lin Division of Endocrinology and Metabolism, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807378, Taiwan;
Ya-Fang Huang Institute of Population Health Sciences, National Health Research Institutes, Miaoli County 350401, Taiwan; (C.-C.H.); (Y.-F.H.)
Chien-Hung Lee Department of Public Health, College of Health Sciences, Kaohsiung Medical University, Kaohsiung 807378, Taiwan;
Chiao-I Chang Graduate Institute of Medicine and Department of Public Health and Environmental Medicine, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807378, Taiwan;
Meng-Chuan Huang Department of Nutrition and Dietetics, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807378, Taiwan; Graduate Institute of Medicine and Department of Public Health and Environmental Medicine, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807378, Taiwan;

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Effect of High-Sucrose Diet on the Occurrence and Progression of Diabetic Retinopathy and Dietary Modification Strategies

As the most serious of the many worse new pathological changes caused by diabetes, there are many risk factors for the occurrence and development of diabetic retinopathy (DR). They mainly include hyperglycemia, hypertension, hyperlipidemia and so on. Among them, hyperglycemia is the most critical cause, and plays a vital role in the pathological changes of DR. High-sucrose diets (HSDs) lead to elevated blood glucose levels in vivo, which, through oxidative stress, inflammation, the production of advanced glycation end products (AGEs) and vascular endothelial growth factor (VEGF), cause plenty of pathological damages to the retina and ultimately bring about loss of vision. The existing therapies for DR primarily target the terminal stage of the disease, when irreversible visual impairment has appeared. Therefore, early prevention is particularly critical. The early prevention of DR-related vision loss requires adjustments to dietary habits, mainly by reducing sugar intake. This article primarily discusses the risk factors, pathophysiological processes and molecular mechanisms associated with the development of DR caused by HSDs. It aims to raise awareness of the crucial role of diet in the occurrence and progression of DR, promote timely changes in dietary habits, prevent vision loss and improve the quality of life. The aim is to make people aware of the importance of diet in the occurrence and progression of DR. According to the dietary modification strategies that we give, patients can change their poor eating habits in a timely manner to avoid theoretically avoidable retinopathy and obtain an excellent prognosis.

A medication-wide association study to identify medications associated with incident clinically significant diabetic retinopathy

Background

Diabetic retinopathy, a common microvascular complication of diabetes mellitus, is one of the leading causes of vision loss worldwide. Although some oral drugs have been suggested to affect the risk of diabetic retinopathy, systematic evaluation about the associations between medications and diabetic retinopathy is still absent.

Objective

To comprehensively investigate associations of systemic medications with incident clinically significant diabetic retinopathy (CSDR).

Design

Population-based cohort study.

Methods

From 2006 to 2009, more than 26 000 participants residing in New South Wales were enrolled in the 45 and Up study. Diabetic participants with self-reported physician diagnosis or records of anti-diabetic medication prescriptions were finally included in the current analysis. CSDR was defined as diabetic retinopathy cases requiring retinal photocoagulation recorded in the Medicare Benefits Schedule database from 2006 to 2016. Prescriptions of systemic medication from 5 years to 30 days prior to CSDR were retrieved from the Pharmaceutical Benefits Scheme. The study participants were equally split into training and testing datasets. Logistic regression analyses were performed for the association between each of systemic medication and CSDR in the training dataset. After controlling the false discovery rate (FDR), significant associations were further validated in the testing dataset.

Results

The 10-year incidence of CSDR was 3.9% (n = 404). A total of 26 systemic medications were found to be positively associated with CSDR, among which 15 were validated by the testing dataset. Additional adjustments for pertinent comorbidities suggested that isosorbide mononitrate (ISMN) (OR: 1.87, 95%CI: 1.00-3.48), calcitriol (OR: 4.08, 95% CI: 2.02-8.24), three insulins and analogues (e.g., intermediate-acting human insulin, OR: 4.28, 95% CI: 1.69-10.8), five anti-hypertensive medications (e.g., furosemide, OR: 2.53, 95% CI: 1.77-3.61), fenofibrate (OR: 1.96, 95% CI: 1.36-2.82) and clopidogrel (OR: 1.72, 95% CI: 1.15-2.58) were independently associated with CSDR.

Conclusion

This study investigated the association of a full spectrum of systemic medications with incident CSDR. ISMN, calcitriol, clopidogrel, a few subtypes of insulin, anti-hypertensive and cholesterol-lowering medications were found to be associated with incident CSDR.

Dietary Intake and Diabetic Retinopathy: A Systematic Review of the Literature

Diabetic retinopathy (DR) is a common microvascular complication of diabetes mellitus. The evidence connecting dietary intake and DR is emerging, but uncertain. We conducted a systematic review to comprehensively summarize the current understanding of the associations between dietary consumption, DR and diabetic macular edema (DME). We systematically searched PubMed, Embase, Medline, and the Cochrane Central Register of Controlled Trials between January 1967 to May 2022 for all studies investigating the effect of diet on DR and DME. Of the 4962 articles initially identified, 54 relevant articles were retained. Our review found that higher intakes of fruits, vegetables, dietary fibers, fish, a Mediterranean diet, oleic acid, and tea were found to have a protective effect against DR. Conversely, high intakes of diet soda, caloric intake, rice, and choline were associated with a higher risk of DR. No association was seen between vitamin C, riboflavin, vitamin D, and milk and DR. Only one study in our review assessed dietary intake and DME and found a risk of high sodium intake for DME progression. Therefore, the general recommendation for nutritional counseling to manage diabetes may be beneficial to prevent DR risk, but prospective studies in diverse diabetic populations are needed to confirm our findings and expand clinical guidelines for DR management.

Association between Usual Dietary Intake of Food Groups and DNA Methylation and Effect Modification by Metabotype in the KORA FF4 Cohort

Associations between diet and DNA methylation may vary among subjects with different metabolic states, which can be captured by clustering populations in metabolically homogenous subgroups, called metabotypes. Our aim was to examine the relationship between habitual consumption of various food groups and DNA methylation as well as to test for effect modification by metabotype. A cross-sectional analysis of participants (median age 58 years) of the population-based prospective KORA FF4 study, habitual dietary intake was modeled based on repeated 24-h diet recalls and a food frequency questionnaire. DNA methylation was measured using the Infinium MethylationEPIC BeadChip providing data on >850,000 sites in this epigenome-wide association study (EWAS). Three metabotype clusters were identified using four standard clinical parameters and BMI. Regression models were used to associate diet and DNA methylation, and to test for effect modification. Few significant signals were identified in the basic analysis while many significant signals were observed in models including food group-metabotype interaction terms. Most findings refer to interactions of food intake with metabotype 3, which is the metabotype with the most unfavorable metabolic profile. This research highlights the importance of the metabolic characteristics of subjects when identifying associations between diet and white blood cell DNA methylation in EWAS.

A Comprehensive Systematic Review of Data Linkage Publications on Diabetes in Australia

Aims

Our study aimed to identify the common themes, knowledge gaps and to evaluate the quality of data linkage research on diabetes in Australia.

Methods

This systematic review was developed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (the PRISMA Statement). Six biomedical databases and the Australian Population Health Research Network (PHRN) website were searched. A narrative synthesis was conducted to comprehensively identify the common themes and knowledge gaps. The guidelines for studies involving data linkage were used to appraise methodological quality of included studies.

Results

After screening and hand-searching, 118 studies were included in the final analysis. Data linkage publications confirmed negative health outcomes in people with diabetes, reported risk factors for diabetes and its complications, and found an inverse association between primary care use and hospitalization. Linked data were used to validate data sources and diabetes instruments. There were limited publications investigating healthcare expenditure and adverse drug reactions (ADRs) in people with diabetes. Regarding methodological assessment, important information about the linkage performed was under-reported in included studies.

Conclusions

In the future, more up to date data linkage research addressing costs of diabetes and its complications in a contemporary Australian setting, as well as research assessing ADRs of recently approved antidiabetic medications, are required.

Dietary associations with diabetic retinopathy-A cohort study

Purpose

To assess the role of dietary factors in the development of diabetic retinopathy (DR) in diabetics.

Methods

This prospective study was carried out on patients attending the outpatient department of ophthalmology for a period of 1 year. An interview-based 24-hour diet recall was used to document average daily dietary nutrient intakes. Each patient was subjected to a comprehensive ocular examination to look for DR.

Results

A total of 261 patients attending the outpatient department of ophthalmology were the participants for this study. The mean (±SD) age of the participants was 57.73 ± 11.29 years, and 67% were men. One hundred and six participants had DR. Univariate analysis revealed sex, duration, fish (times/week), egg (yes/no), rice lunch (yes/no), rice dinner, rice (boiled/white), and total calorie intake to be associated with DR (P < 0.05). Logistic regression multivariable analysis revealed males (OR: 3.20, 95% CI: 1.65-6.19), longer duration of diabetes (OR:1.05,95% CI:1.01-1.11), antioxidant intake (OR: 3.42, 95% CI: 1.65-7.05), and consumption of rice (OR: 3.19, 95% CI: 1.17-8.69) to have significant association with DR (P < 0.05), with the odds of developing DR increasing three times in these patients. The odds of developing DR were lesser with more frequent (>2 times/week) fish consumption (OR: 0.42, 95% CI: 0.18-0.94) and in patients on pharmacological treatment for diabetes mellitus (OR: 0.16, 95% CI: 0.04-0.58). Binary logistic regression revealed chapathi consumption (OR: 9.37, 95% CI: 1.64-53.68) to be associated with severe forms and fish consumption (OR: 0.06, 95% CI: 0.01-1.06) (P < 0.05) to be associated with less severe forms of DR.

Conclusion

Males, longer duration of diabetes, antioxidant intake, fish consumption, and consumption of rice were associated with the occurrence of DR. Participants with diabetes who consumed fish more frequently and those who were on pharmacological treatment for diabetes mellitus had a significantly lower risk of DR and frequent fish consumption could reduce the risk of DR progression.

Predicting the 10-year risk of cataract surgery using machine learning techniques on questionnaire data: findings from the 45 and Up Study

Background/aims

To investigate the feasibility and accuracy of using machine learning (ML) techniques on self-reported questionnaire data to predict the 10-year risk of cataract surgery, and to identify meaningful predictors of cataract surgery in middle-aged and older Australians.

Methods

Baseline information regarding demographic, socioeconomic, medical history and family history, lifestyle, dietary and self-rated health status were collected as risk factors. Cataract surgery events were confirmed by the Medicare Benefits Schedule Claims dataset. Three ML algorithms (random forests [RF], gradient boosting machine and deep learning) and one traditional regression algorithm (logistic model) were compared on the accuracy of their predictions for the risk of cataract surgery. The performance was assessed using 10-fold cross-validation. The main outcome measures were areas under the receiver operating characteristic curves (AUCs).

Results

In total, 207 573 participants, aged 45 years and above without a history of cataract surgery at baseline, were recruited from the 45 and Up Study. The performance of gradient boosting machine (AUC 0.790, 95% CI 0.785 to 0.795), RF (AUC 0.785, 95% CI 0.780 to 0.790) and deep learning (AUC 0.781, 95% CI 0.775 to 61 0.786) were robust and outperformed the traditional logistic regression method (AUC 0.767, 95% CI 0.762 to 0.773, all p<0.05). Age, self-rated eye vision and health insurance were consistently identified as important predictors in all models.

Conclusions

The study demonstrated that ML modelling was able to reasonably accurately predict the 10-year risk of cataract surgery based on questionnaire data alone and was marginally superior to the conventional logistic model.