Introduction: More than half of diabetes mellitus (DM) and pre-diabetes (pre-DM) cases remain undiagnosed, while existing risk assessment models are limited by focusing on diabetes mellitus only (omitting pre-DM) and often lack lifestyle factors such as sleep. This study aimed to develop a non-laboratory risk assessment model to detect undiagnosed diabetes mellitus and pre-diabetes mellitus in Chinese adults.
Methods: Based on a population-representative dataset, 1,857 participants aged 18-84 years without self-reported diabetes mellitus, pre-diabetes mellitus, and other major chronic diseases were included. The outcome was defined as a newly detected diabetes mellitus or pre-diabetes by a blood test. The risk models were developed using logistic regression (LR) and interpretable machine learning (ML) methods. Models were validated using area under the receiver-operating characteristic curve (AUC-ROC), precision-recall curve (AUC-PR), and calibration plots. Two existing diabetes mellitus risk models were included for comparison.
Results: The prevalence of newly diagnosed diabetes mellitus and pre-diabetes mellitus was 15.08%. In addition to known risk factors (age, BMI, WHR, SBP, waist circumference, and smoking status), we found that sleep duration, and vigorous recreational activity time were also significant risk factors of diabetes mellitus and pre-diabetes mellitus. Both LR (AUC-ROC = 0.812, AUC-PR = 0.448) and ML models (AUC-ROC = 0.822, AUC-PR = 0.496) performed well in the validation sample with the ML model showing better discrimination and calibration. The performance of the models was better than the two existing models.
Conclusions: Sleep duration and vigorous recreational activity time are modifiable risk factors of diabetes mellitus and pre-diabetes in Chinese adults. Non-laboratory-based risk assessment models that incorporate these lifestyle factors can enhance case detection of diabetes mellitus and pre-diabetes.
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http://dx.doi.org/10.1111/jdi.13790 | DOI Listing |
Front Clin Diabetes Healthc
January 2025
Department of Endocrinology and Diabetes, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, United Kingdom.
Background: The UK National Paediatric Diabetes Audit (NPDA) data reports disparities in Haemoglobin A1c (HbA1c) levels among children and young people (CYP) with Type 1 Diabetes (T1D), with higher levels in those of Black ethnic background and lower socioeconomic status who have less access to technology. We investigate HbA1c differences in a T1D cohort with higher than national average technology uptake where > 60% come from an ethnic minority and/or socioeconomically deprived population.
Design & Methods: Retrospective cross-sectional study investigating the influence of demographic factors, technology use, and socioeconomic status (SES) on glycaemic outcomes.
PeerJ
January 2025
Department of Nephrology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China.
Dysregulated specificity proteins (SPs), members of the C2H2 zinc-finger family, are crucial transcription factors (TFs) with implications for renal physiology and diseases. This comprehensive review focuses on the role of SP family members, particularly SP1 and SP3, in renal physiology and pathology. A detailed analysis of their expression and cellular localization in the healthy human kidney is presented, highlighting their involvement in fatty acid metabolism, electrolyte regulation, and the synthesis of important molecules.
View Article and Find Full Text PDFFront Neurol
January 2025
Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Objective: To investigate the altered characteristics of cortical morphology and individual-based morphological brain networks in type 2 diabetes mellitus (T2DM), as well as the neural network mechanisms underlying cognitive impairment in T2DM.
Methods: A total of 150 T2DM patients and 130 healthy controls (HCs) were recruited in this study. The study used voxel- and surface-based morphometric analyses to investigate morphological alterations (including gray matter volume, cortical thickness, cortical surface area, and localized gyrus index) in the brains of T2DM patients.
J Tradit Complement Med
November 2024
Chitkara College of Pharmacy, Chitkara University, Rajpura, 140401, Punjab, India.
Diabetes mellitus and its debilitating microvascular complications, including diabetic neuropathy and nephropathy, represent a growing global health burden. Despite advances in conventional therapies, their suboptimal efficacy and adverse effects necessitate exploring complementary and alternative medicine approaches. , a coniferous tree species native to eastern North America, has gained significant attention for its potential therapeutic applications in various disorders, attributed to its rich phytochemical composition.
View Article and Find Full Text PDFJ Diabetes Res
January 2025
Renal Research Laboratory, Kolling Institute of Medical Research, Royal North Shore Hospital & The University of Sydney, Sydney, Australia.
Emerging evidence suggests cell exfoliation could be operating under the control of cell metabolism. It is unclear if there are associations between the concentration of exfoliated kidney proximal tubule cells (PTCs) in urine with glycemic control and complications. Our study is aimed at exploring this.
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