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Background: Body mass index (BMI) and fasting plasma glucose (FPG) are known risk factors for type 2 diabetes mellitus (T2DM), but data on the prospective association of the combination of BMI and FPG with T2DM are limited. This study sought to characterize the association of the combination of BMI and FPG (ByG) with T2DM.
Methods: The current study used the NAGALA database. We categorized participants by tertiles of ByG. The association of ByG with T2DM was expressed with hazard ratios (HRs) with 95% confidence intervals (CIs) after adjustment for potential risk factors.
Results: During a median follow-up of 6.19 years in the normoglycemia cohort and 5.58 years in the prediabetes cohort, the incidence of T2DM was 0.75% and 7.79%, respectively. Following multivariable adjustments, there were stepwise increases in T2DM with increasing tertiles of ByG. After a similar multivariable adjustment, the risk of T2DM was 2.57 (95% CI 2.26 - 2.92), 1.97 (95% CI 1.53 - 2.54) and 1.50 (95% CI 1.30 - 1.74) for a per-SD change in ByG in all populations, the normoglycemia cohort and the prediabetes cohort, respectively.
Conclusion: ByG was associated with an increased risk of T2DM in Japan. The result reinforced the importance of the combination of BMI and FPG in assessing T2DM risk.
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http://dx.doi.org/10.3389/fendo.2024.1355180 | DOI Listing |
Geroscience
September 2025
Department of Emergency and Internal Medicine, Skåne University Hospital, Malmö, Sweden.
To evaluate a simplified version of the Clinical Frailty Scale (SCFS) among older adults presenting to the emergency department (ED) with acute dyspnea. In this retrospective single-center cohort study, we included patients from the Acute Dyspnea Study (ADYS) cohort. Severity of illness was assessed using the Medical Emergency Triage and Treatment System (METTS).
View Article and Find Full Text PDFBariatric surgery is an effective treatment for morbid obesity, but patient outcomes differ greatly because of a variety of phenotypes, comorbidities, and postoperative adherence. In bariatric care, artificial intelligence (AI) and machine learning (ML) are becoming revolutionary tools because traditional predictive models based on BMI and demographic variables are unable to account for these complexities. To put it simply, AI is a branch of computer science that enables machines to perform tasks that typically require human intelligence.
View Article and Find Full Text PDFBiol Psychiatry Cogn Neurosci Neuroimaging
September 2025
Developmental Imaging and Psychopathology Laboratory, University of Geneva School of medicine, Geneva, Switzerland; Department of Genetic Medicine and Development, University of Geneva School of Medicine, Geneva, Switzerland.
Background: Recent epidemiological evidence links early-life obesity and metabolic dysregulation to adult psychosis vulnerability, though a causal relationship remains unclear. Establishing causality in highly heritable psychotic disorders requires: 1) demonstrating that early-life metabolic factors mediate between genetic vulnerability and psychosis trajectory, 2) dissecting mechanisms leading to early-life obesity in genetically vulnerable individuals, and 3) clarifying downstream neurodevelopmental pathways linking early-life obesity to psychosis symptoms.
Methods: Here we investigated bidirectional pathways linking behavioral, BMI, and neurodevelopment trajectories in a unique longitudinal cohort of 184 individuals at high genetic risk for psychosis, due to 22q11.
J Affect Disord
September 2025
School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, China. Electronic address:
Background: While associations between psychiatric disorders and hypothyroidism have been observed, the underlying causal relationships remain unclear. Exploring the causal relationships among them can provide new insights into the underlying mechanisms.
Methods: Two-sample Mendelian randomization (MR) was conducted to assess the causal effects of seven psychiatric disorders on hypothyroidism.
JMIR Pediatr Parent
September 2025
Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China.
Background: Adolescence is a critical transitional period between childhood and adulthood, marked by dramatic changes in physical and psychosocial health. Adolescents are vulnerable to both depression and adiposity, but how these conditions evolve over time from adolescence to early adulthood and whether sex differences exist remains unclear.
Objective: This study aims to first identify the population heterogeneity in the joint trajectories of depressive symptoms and BMI from adolescence to early adulthood and then explore the sex differences in the joint trajectories.