A prospective study was carried out from August 2010 to August 2014 in the community of Fengyutan (China). Six hundred and twenty two T2D subjects were collected. The incidence density of diabetic retinopathy (DR) was 1.81% person-year (95% confidence interval, CI: 1.21–2.43% person-year). After a Cox regression model analysis and adjusted confounding factors, independent predictors related to the incidence of DR including male gender (adjusted hazard ratios, aHR: 1.47, 95% CI: 1.21–1.62), with hypertension (aHR: 1.49, 95%: 1.12–1.73), duration of diabetes > 10 years (aHR: 2.28, 95%: 2.05–2.42), uncontrolled diabetes (aHR: 1.76, 95%: 1.41–2.01), total cholesterol ≥ 200 mg/dL (aHR: 1.54, 95%: 1.34–1.72) and HbA1c ≥ 7% (mmol/mol) (aHR: 2.12, 95%: 1.87–2.32). Duration of T2D revealed the significantly dose-response relationship to the onset of DR. The incidence density of DR in the Chinese community was relatively low in comparison with other studies. More attention should be paid to the T2D patients, especially of male gender, with hypertension, longer duration of diabetes, uncontrolled diabetes, total cholesterol ≥ 200mg/dL and HbA1c ≥ 7% (mmol/mol).
ObjectiveTo describe the telescreening model and assess the prevalence of ocular fundus pathology in patients with type 2 diabetes within a Chinese urban community.DesignCommunity-based cross-sectional study.SettingHealthcare centre of Fengyutan Community, Shenyang, China.ParticipantsA total 528 patients (287 females) with type 2 diabetes mellitus (DM) were randomly recruited using health files from the healthcare centre of Fengyutan community between 8 October and 20 November 2012.Main outcome measuresSigns of any diabetic retinopathy (DR), signs of glaucoma and signs of age-related macular degeneration (AMD).ResultsThe main ocular fundus pathologies were DR (75 patients, 14.20%), 65 (86.67%) cases of which were newly detected, AMD (57 patients, 10.79%) and glaucoma (63 patients, 11.93%). The risk factors for fundus pathology were long duration of diabetes (OR 2.31, 95% CI 1.87 to 2.56), and higher fasting plasma glucose (OR 3.64, 95% CI 1.81 to 5.21) and glycated haemoglobin (HbA1c) levels (OR 3.83, 95% CI 1.87 to 6.35).ConclusionsThere was a high prevalence of fundus pathology among patients with type 2 diabetes, and in most of the cases, this was newly detected. Community screening for fundus pathology among patients with a long duration of type 2 diabetes and high fasting plasma glucose and HbA1c levels using a telescreening model will provide an effective strategy for the prevention and treatment of fundus pathology.
ObjectiveTo investigate the relationship between metabolic syndrome (MS) and the prevalence of retinopathy.DesignA cross-sectional study was carried out from August 2013 to September 2014 in Fengyutan Sub-District.Primary and secondary outcome measuresA total of 1163 eligible participants attended. All the participants were subjected to stereo fundus photography to detect retinopathy. The discrepancy of prevalence of retinopathy in different participants was described.ResultsThe prevalence of retinopathy was 9.64% in patients with MS and 3.91% in patients without MS. A higher prevalence of retinopathy with proliferative diabetic retinopathy was found in patients with MS. In multiple logistic regression analysis, independent risk factors for any retinopathy in patients with MS were longer diabetes duration (OR 1.07; 95% CI 1.04 to 1.10, per year increase), higher systolic blood pressure (SBP) (OR 1.16; 95% CI 1.09 to 1.29, per 10 mm Hg increase), higher diastolic blood pressure (DBP) (OR 1.24; 95% CI 1.12 to 1.35, per 10 mm Hg increase), higher fasting plasma glucose (OR 1.07; 95% CI 1.02 to 1.11, per 10 mg/dL increase), higher 2 h postprandial plasma glucose (OR 1.17; 95% CI 1.12 to 1.21, per 10 mg/dL increase), and higher haemoglobin A1c (HbA1c) (OR 1.23; 95% CI 1.13 to 1.34, per % increase). Similar independent risk factors, except for DBP, were found for any retinopathy in patients without MS.ConclusionsThe presence of MS components, hyperglycaemia (fasting glucose and HbA1c) and hypertension (SBP and DBP), are significantly associated with the prevalence of retinopathy.
In order to induce the shift in consumer behavior necessary for the mitigation of diet-related diseases, front-of-package labels (FoPL) such as the Nutri-Score that support consumers in their efforts to identify nutritionally valuable products during grocery shopping have been found to be effective; however, they remain non-compulsory in most regions. Counter-intuitively, a similar stream of research on digital web-based FoPL does not yet exist, even though such digital labels hold several advantages over physical labels. Digital FoPL can provide scalable and personalized interventions, are easier to implement than physical labels, and are especially timely due to the recent increase in online grocery shopping. The goal of this study was to demonstrate the technical feasibility and intervention potential of novel, scalable, and passively triggered health behavior interventions distributed via easy-to-install web browser extensions designed to support healthy food choices via the inclusion of digital FoPL in online supermarkets. To that end, we developed a Chrome web browser extension for a real online supermarket and evaluated the effect of this digital food label intervention (i.e., display of the Nutri-Score next to visible products) on the nutritional quality of individuals’ weekly grocery shopping in a randomized controlled laboratory trial (N = 135). Compared to the control group, individuals exposed to the intervention chose products with a higher nutritional quality (e.g., 8% higher healthy trolley index (HETI), 3.3% less sugar, 7.5% less saturated fat). In particular, users with low food literacy seemed to benefit from the digital FoPL (e.g., 11% higher HETI, 10.5% less sugar, 5.5% less saturated fat). Furthermore, participants exposed to the food label advocated its introduction more strongly than the control group (p = 0.081). Consumers worldwide could easily install such applications to display digital food labels on their end devices, and would thus not have to wait for stakeholders in the food industry to eventually reach consensus on mandatory food label introduction.
Recent studies have demonstrated the potential of OCTA retinal imaging for the discovery of biomarkers of vascular disease of the eye and other organs. Furthermore, advances in deep learning have made it possible to train algorithms for the automated detection of such biomarkers. However, two key limitations of this approach are the need for large numbers of labeled images to train the algorithms, which are often not met by the typical single-centre prospective studies in the literature, and the lack of interpretability of the features learned during training. In the current study, we developed a network analysis framework to characterise retinal vasculature where geometric and topological information are exploited to increase the performance of classifiers trained on tens of OCTA images. We demonstrate our approach in two different diseases with a retinal vascular footprint: diabetic retinopathy (DR) and chronic kidney disease (CKD). Our approach enables the discovery of previously unreported retinal vascular morphological differences in DR and CKD, and demonstrate the potential of OCTA for automated disease assessment.
Objective To obtain more precise and rich information from the measurements for schizotypal personality disorder (SPD), a cutting‐edge psychometric theory called diagnostic classification models (DCMs) was first employed in the present study to develop a diagnostic classification version of the Schizotypal Personality Questionnaire (DC‐SPQ) based on the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. Methods Under the framework of DCMs, 980 college students were recruited to calibrate item parameters of the Schizotypal Personality Questionnaire. Items that fit the psychometric characteristic would be selected to compose the DC‐SPQ, prior to an analysis of its indexes. Results Results showed that the DC‐SPQ had high reliability and validity in both the classical test theory and DCMs, in addition to showing a sensitivity of 0.921 and a specificity of 0.841 with area under receiver operating characteristic curve = 0.936. Meanwhile, the four‐factor model proposed adequately fits with the data. More importantly, the DC‐SPQ provides not only the general‐level information similar to traditional questionnaires but also the symptom‐level information with the posterior probability, which provides an insight into delivering the individual‐specific intervention that is tailor made to schizotypal personality disorder. Conclusions This study demonstrates that the DC‐SPQ is very valuable for psychometric detection in that it can clarify the symptom being measured and provide more reasonable estimates.
The aim of this research was to identify the prevalence and distribution of vitreoretinal interface abnormalities (VIAs) among urban community population in Shenyang, China. According to the WHO criteria, a cross-sectional study was carried out among 304 Type 2 diabetes (T2D) patients and 304 people without diabetes as control over 45 years old. The presence of VIAs was determined by standardized grading of macular optical coherence tomography (Optovue OCT; Optovue, Inc., Fremont, CA) scans and two-field fundus photographs in at least one eye. For both men and women, high prevalence of VIAs (70.79%) was observed among over 65-years-old T2D patients. Prevalence of VIAs was observed to be high among T2D patients in all age groups compared to normal subjects. Prevalence of VIAs increased with age in all subjects. Prevalence of components of VIAs was epiretinal membrane (ERM) 11.43%, posterior vitreous detachment (PVD) 17.76%, vitreomacular traction syndrome (VMT) 5.67%, macular cysts/macular edema (MC/ME) 4.61%, full-thickness macular hole (FTMH) 0.82%, and partial thickness macular hole (PTMH) 0.74% in any eye, respectively. ERM and MC/ME were more prevalent in T2D in both males and females. The results highlight the need for early detection using OCT and approaches for the prevention of VIAs of diabetes in urban community.
In light of the globally increasing prevalence of diet-related chronic diseases, new scalable and non-invasive dietary monitoring techniques are urgently needed. Automatically collected digital receipts from loyalty cards hereby promise to serve as an objective and automatically traceable digital marker for individual food choice behavior and do not require users to manually log individual meal items. With the introduction of the General Data Privacy Regulation in the European Union, millions of consumers gained the right to access their shopping data in a machine-readable form, representing a historic chance to leverage shopping data for scalable monitoring of food choices. Multiple quantitative indicators for evaluating the nutritional quality of food shopping have been suggested, but so far, no comparison has validated the potential of these alternative indicators within a comparative setting. This manuscript thus represents the first study to compare the calibration capacity and to validate the discrimination potential of previously suggested food shopping quality indicators for the nutritional quality of shopped groceries, including the Food Standards Agency Nutrient Profiling System Dietary Index (FSA-NPS DI), Grocery Purchase Quality Index-2016 (GPQI), Healthy Eating Index-2015 (HEI-2015), Healthy Trolley Index (HETI) and Healthy Purchase Index (HPI), checking if any of them performs differently from the others. The hypothesis is that some food shopping quality indicators outperform the others in calibrating and discriminating individual actual dietary intake. To assess the indicators’ potentials, 89 eligible participants completed a validated food frequency questionnaire (FFQ) and donated their digital receipts from the loyalty card programs of the two leading Swiss grocery retailers, which represent 70% of the national grocery market. Compared to absolute food and nutrient intake, correlations between density-based relative food and nutrient intake and food shopping data are stronger. The FSA-NPS DI has the best calibration and discrimination performance in classifying participants’ consumption of nutrients and food groups, and seems to be a superior indicator to estimate nutritional quality of a user’s diet based on digital receipts from grocery shopping in Switzerland.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.