High amount of visceral fat mass is associated with multiple metabolic changes in offspring of type 2 diabetic patients

2005 ◽  
Vol 29 (12) ◽  
pp. 1464-1470 ◽  
Author(s):  
U Salmenniemi ◽  
E Ruotsalainen ◽  
M Vänttinen ◽  
I Vauhkonen ◽  
J Pihlajamäki ◽  
...  
Keyword(s):  
Fat Mass ◽  
Visceral Fat ◽  
Metabolic Changes ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Type 2 Diabetic

scholarly journals Effects of Metformin on the Cerebral Metabolic Changes in Type 2 Diabetic Patients

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Yung-Cheng Huang ◽  
Chien-Chin Hsu ◽  
Wei-Che Lin ◽  
Tang-Kai Yin ◽  
Chi-Wei Huang ◽  
...  
Keyword(s):  
White Matter ◽  
Cerebral Metabolism ◽  
Statistical Parametric Mapping ◽  
Metabolic Changes ◽  
Parahippocampal Gyrus ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Fdg Uptake ◽  
Type 2 Diabetic

Metformin, a widely used antidiabetic drug, has numerous effects on human metabolism. Based on emerging cellular, animal, and epidemiological studies, we hypothesized that metformin leads to cerebral metabolic changes in diabetic patients. To explore metabolism-influenced foci of brain, we used 2-deoxy-2-[18F]fluoro-D-glucose (FDG) positron emission tomography for type 2 diabetic patients taking metformin (MET,n=18), withdrawing from metformin (wdMET,n=13), and not taking metformin (noMET,n=9). Compared with the noMET group, statistical parametric mapping showed that the MET group had clusters with significantly higher metabolism in right temporal, right frontal, and left occipital lobe white matter and lower metabolism in the left parahippocampal gyrus, left fusiform gyrus, and ventromedial prefrontal cortex. In volume of interest (VOI-) based group comparisons, the normalized FDG uptake values of both hypermetabolic and hypometabolic clusters were significantly different between groups. The VOI-based correlation analysis across the MET and wdMET groups showed a significant negative correlation between normalized FDG uptake values of hypermetabolic clusters and metformin withdrawal durations and a positive but nonsignificant correlation in the turn of hypometabolic clusters. Conclusively, metformin affects cerebral metabolism in some white matter and semantic memory related sites in patients with type 2 diabetes.

scholarly journals Systemic arteriosclerosis and eating behavior in Japanese type 2 diabetic patients with visceral fat accumulation

2015 ◽  
Vol 14 (1) ◽  
pp. 8 ◽  
Author(s):  
Shiro Fukuda ◽  
Ayumu Hirata ◽  
Hitoshi Nishizawa ◽  
Hirofumi Nagao ◽  
Susumu Kashine ◽  
...  
Keyword(s):  
Eating Behavior ◽  
Visceral Fat ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Fat Accumulation ◽  
Visceral Fat Accumulation ◽  
Type 2 Diabetic

scholarly journals Association of two novel adiposity indicators with visceral fat area in type 2 diabetic patients

Medicine ◽  
2020 ◽  
Vol 99 (19) ◽  
pp. e20046
Author(s):  
Junru Liu ◽  
Dongmei Fan ◽  
Xing Wang ◽  
Fuzai Yin
Keyword(s):  
Visceral Fat ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Visceral Fat Area ◽  
Type 2 Diabetic

scholarly journals Relative Fat Mass, a new tool for measuring obesity, could predict the complications of type 2 diabetes

2021 ◽  
Vol 5 (3) ◽  
pp. 01-08
Author(s):  
Isabelle Jambart
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Diabetic Neuropathy ◽  
Fat Mass ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Type 2 Diabetic

Aim/background: Obesity is a chronic disease contributing to many metabolic illnesses, in particular type 2 diabetes. The Relative Fat Mass (RFM) is a tool recently introduced for obesity which better predicts the level of visceral fat than the Body Mass Index (BMI). The aim of this study is to determine whether RFM is a better predictor of the cardiometabolic risk factors and the complications of type 2 diabetes than BMI. Materials and methods: This is a cross sectional study. A list of information was collected from endocrinologists treating type 2 diabetic patients in a primary healthcare clinic and a tertiary hospital in Beirut. This list allowed us to evaluate the micro and macro vascular complications of type 2 diabetic patients, to assess their risk factors and to calculate their RFM and BMI. Results: We analyzed the data of 359 patients. Higher RFM was associated with higher systolic blood pressure (p < 0.05), and both RFM and BMI were significantly correlated to higher CRP, triglyceride levels and liver enzymes. However, the BMI was better associated with other cardiometabolic risk factors such as the total cholesterol (p = 0,003), LDL cholesterol (p = 0,002) and HbA1c (p = 0,01) than RFM. Both RFM and BMI were correlated with higher microalbuminuria (p < 0.001) but unlike BMI, higher RFM was associated with higher creatinine level (p = 0.317 versus 0.047 respectively) and therefore better linked to diabetic nephropathy than BMI. More importantly, we observed an unprecedented result, associating RFM to diabetic neuropathy: a normal RFM excludes diabetic neuropathy with a high probability of 82.5%. Furthermore, a RFM cutoff value of 30.76 in men and 43.31 in women showed an increased risk of developing diabetic neuropathy by 2.464. No association was observed between RFM and diabetic retinopathy. Conclusion: The RFM better predicts microvascular complications of diabetes than BMI except for retinopathy. It is also associated with a worse profile of metabolic syndrome. This study is unique in its discovery of the potential role of RFM as a tool which could rule out neuropathy in diabetic patients.

scholarly journals Relative Fat Mass, a new tool for measuring obesity, could predict the complications of type 2 diabetes

2021 ◽  
Vol 5 (3) ◽  
pp. 01-08
Author(s):  
Isabelle Jambart
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Diabetic Neuropathy ◽  
Fat Mass ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Type 2 Diabetic

Aim/background: Obesity is a chronic disease contributing to many metabolic illnesses, in particular type 2 diabetes. The Relative Fat Mass (RFM) is a tool recently introduced for obesity which better predicts the level of visceral fat than the Body Mass Index (BMI). The aim of this study is to determine whether RFM is a better predictor of the cardiometabolic risk factors and the complications of type 2 diabetes than BMI. Materials and methods: This is a cross sectional study. A list of information was collected from endocrinologists treating type 2 diabetic patients in a primary healthcare clinic and a tertiary hospital in Beirut. This list allowed us to evaluate the micro and macro vascular complications of type 2 diabetic patients, to assess their risk factors and to calculate their RFM and BMI. Results: We analyzed the data of 359 patients. Higher RFM was associated with higher systolic blood pressure (p < 0.05), and both RFM and BMI were significantly correlated to higher CRP, triglyceride levels and liver enzymes. However, the BMI was better associated with other cardiometabolic risk factors such as the total cholesterol (p = 0,003), LDL cholesterol (p = 0,002) and HbA1c (p = 0,01) than RFM. Both RFM and BMI were correlated with higher microalbuminuria (p < 0.001) but unlike BMI, higher RFM was associated with higher creatinine level (p = 0.317 versus 0.047 respectively) and therefore better linked to diabetic nephropathy than BMI. More importantly, we observed an unprecedented result, associating RFM to diabetic neuropathy: a normal RFM excludes diabetic neuropathy with a high probability of 82.5%. Furthermore, a RFM cutoff value of 30.76 in men and 43.31 in women showed an increased risk of developing diabetic neuropathy by 2.464. No association was observed between RFM and diabetic retinopathy. Conclusion: The RFM better predicts microvascular complications of diabetes than BMI except for retinopathy. It is also associated with a worse profile of metabolic syndrome. This study is unique in its discovery of the potential role of RFM as a tool which could rule out neuropathy in diabetic patients.

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