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PLoS One
January 2025
Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Background: Previous studies reported that focusing on healthy lifestyle, especially high diet quality is necessary for preventing type 2 diabetes (T2D). This study investigated the association between the innovative index, the Global Diet Quality Score (GDQS), and the risk of Type 2 Diabetes incidence.
Methods: In this secondary analysis, we included elective adult participants (n = 5948) from the third and fourth survey of the Tehran Lipid and Glucose Study.
Tunis Med
January 2025
Department of Endocrinology and Internal Medicine, Fattouma Bourguiba Hospital, Monastir. Tunisia.
Unlabelled: Introduction-Aim: Type 2 diabetes (T2D) is a major public health problem. To succeed its management and prevent its complications, good therapeutic adherence must be ensured. The objectives of our work were to estimate the prevalence of poor therapeutic adherence in our patients and to identify its associated factors.
View Article and Find Full Text PDFJ Agric Food Chem
January 2025
College of Food Science and Engineering, Northwest A&F University, Yangling, 712100 Shaanxi, China.
Pumpkin extract has been shown to alleviate hyperglycemic symptoms by improving glucose metabolism disorders. However, the specific active components responsible for its hypoglycemic effects and the underlying molecular mechanisms remain unclear. In this study, db/db mice underwent a 4-week dietary intervention with two pumpkin flours (PF1 and PF2), total dietary fiber (TDF), soluble dietary fiber (SDF), and insoluble dietary fiber (IDF), with acarbose serving as a positive control.
View Article and Find Full Text PDFDiabetes Metab Res Rev
January 2025
Division of Research, Kaiser Permanente Northern California, Pleasanton, California, USA.
Aims: Gestational diabetes mellitus (GDM) poses a significant risk for developing type 2 diabetes mellitus (T2D) and exhibits heterogeneity. However, understanding the link between different types of post-GDM individuals without diabetes and their progression to T2D is crucial to advance personalised medicine approaches.
Materials And Methods: We employed a discovery-based unsupervised machine learning clustering method to generate clustering models for analysing metabolomics, clinical, and biochemical datasets.
J Diabetes Sci Technol
January 2025
Madras Diabetes Research Foundation, Chennai, India.
Introduction: mHealth technology has the potential to deliver personalized health care; however, data on cardiometabolic risk factors are limited. This study aims to assess the effectiveness of mobile health applications (apps) on cardiometabolic risk factor reduction in adults aged 25 to 60 years in urban and rural India.
Methods: The study design was a pilot randomized controlled trial conducted in Tamil Nadu, India.
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