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- Abstract: adrenarche x
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- Metabolic Syndrome and Diabetes x
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Background
Polycystic ovary syndrome (PCOS) is considered a risk factor for the development of type 2 diabetes mellitus (T2DM). However, which is the most appropriate way to evaluate dysglycemia in women with PCOS and who are at increased risk are as yet unclear.
Aim of the study
To determine the prevalence of T2DM, impaired glucose tolerance (IGT), and impaired fasting glucose (IFG) in PCOS women and potential factors to identify those at risk.
Subjects and methods
The oral glucose tolerance test (OGTT), biochemical/hormonal profile, and ovarian ultrasound data from 1614 Caucasian women with PCOS and 362 controls were analyzed in this cross-sectional multicenter study. The data were categorized according to age and BMI.
Results
Dysglycemia (T2DM, IGT, and IFG according to World Health Organization criteria) was more frequent in the PCOS group compared to controls: 2.2% vs 0.8%, P = 0.04; 9.5% vs 7.4%, P = 0.038; 14.2% vs 9.1%, P = 0.002, respectively. OGTT was essential for T2DM diagnosis, since in 88% of them basal glucose values were inconclusive for diagnosis. The presence of either T2DM or IFG was irrespective of age (P = 0.54) and BMI (P = 0.32), although the latter was associated with IGT (P = 0.021). There was no impact of age and BMI status on the prevalence of T2DM or IFG. Regression analysis revealed a role for age, BMI, fat deposition, androgens, and insulin resistance for dysglycemia. However, none of the factors prevailed as a useful marker employed in clinical practice.
Conclusions
One-third of our cohort of PCOS women with either T2DM or IGT displayed normal fasting glucose values but without confirming any specific predictor for dysglycemic condition. Hence, the evaluation of glycemic status using OGTT in all women with PCOS is strongly supported.
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Background
This study aimed to investigate the association of non-alcoholic fatty liver disease (NAFLD) and liver fibrosis with osteoporosis in postmenopausal women and men over 50 years of age with type 2 diabetes (T2DM).
Methods
In this study, 1243 patients with T2DM (T2DM with coexistent NAFLD, n = 760; T2DM with no NAFLD, n = 483) were analysed. Non-invasive markers, NAFLD fibrosis score (NFS) and fibrosis index based on four factors (FIB-4), were applied to evaluate NAFLD fibrosis risk.
Results
There was no significant difference in bone mineral density (BMD) between the NAFLD group and the non-NAFLD group or between males and females after adjusting for age, BMI and gender. In postmenopausal women, there was an increased risk of osteoporosis (odds ratio (OR): 4.41, 95% CI: 1.04–18.70, P = 0.039) in the FIB-4 high risk group compared to the low risk group. Similarly, in women with high risk NFS, there was an increased risk of osteoporosis (OR: 5.98, 95% CI: 1.40–25.60, P = 0.043) compared to the low risk group. Among men over 50 years old, there was no significant difference in bone mineral density between the NAFLD group and the non-NAFLD group and no significant difference between bone mineral density and incidence of osteopenia or osteoporosis among those with different NAFLD fibrosis risk.
Conclusion
There was a significant association of high risk for NAFLD liver fibrosis with osteoporosis in postmenopausal diabetic women but not men. In clinical practice, gender-specific evaluation of osteoporosis is needed in patients with T2DM and coexistent NAFLD.
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Background
The aim of this study was to address the intramuscular adipose tissue (IMAT) accumulation in the lower extremities and further detect the relationship between adipose tissue (AT) distribution in the muscle and glucose metabolism in subjects with obesity.
Methods
We conducted a cross-sectional study in 120 Chinese obese adults (80 male and 40 female) with BMI ≥ 28 kg/m2. MRI was applied to access the IMAT content in lower extremities. The oral glucose tolerance test was used to evaluate the glucose metabolism and insulin secretion in all individuals. The correlations between glucose metabolism and the fat content of the lower extremities were further assessed.
Results
Among 120 included subjects, 54 were classified as subjects with normal glucose tolerance (NGT) and 66 with impaired glucose regulation (IGR). We presented that those with IGR had higher fat accumulation in semitendinosus, adductor magnus, gracilis and sartorius than those with NGT (all P < 0.05). In sex-specific analyses, females have higher IMAT in adductor magnus than males (P < 0.001). Males with IGR had higher fat fraction of semitendinosus and sartorius than those with NGT (P = 0.020, P = 0.014, respectively). Logistic regression analyses revealed that IMAT content in semitendinosus was the independent factor of IGR in individuals with obesity after adjustment for age, gender, triglycerides, creatinine and albumin (odds ratio: 1.13, 95% CI: 1.02–1.26, P = 0.024).
Conclusions
Increased adipose tissue accumulation in thigh muscles was associated with glucose dysregulation in patients with obesity. IMAT content in semitendinosus may serve as a possible risk factor for impaired glucose metabolism.
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Objective
The aim of this study was to investigate the relationship between weight-adjusted-waist index (WWI) and diabetic kidney disease in individuals afflicted with type 2 diabetes.
Methods
Comprehensive data were ascertained from the National Health and Nutrition Examination Survey in 2013–March 2020. Weighted univariate, multivariate logistic regression models, subgroup analyses and tests for interaction were performed. Additionally, we employed smooth curve fitting to assess linear correlations and the threshold effects were calculated by applying a binary linear regression model. Breakpoints are identified by a model with maximum likelihood ratio and a two-step recursive approach. Receiver operating characteristic curve (ROC) along with the area under the curve (AUC) value predict the capability of WWI and body mass index for diabetic kidney disease.
Results
A total of 10,661 individuals diagnosed with type 2 diabetes were included, and the overall prevalence of diabetic kidney disease was 20.74%. WWI exhibited a positive correlation with the likelihood of diabetic kidney disease in type 2 diabetes patients (OR: 1.17, 95% CI: 1.03–1.33). The results of subgroup analysis showed significant interaction for gender (P < 0.05). Among female patients, U-shaped correlations were observed with a breakpoint at 11.48. Additionally, weight-adjusted waist index (AUC = 0.664) proved to be a more effective predictor of diabetic kidney disease compared to body mass index (AUC = 0.555).
Conclusion
In patients with type 2 diabetes, increased weight-adjusted-waist index is implicated with an increased risk of diabetic kidney disease. WWI can be used as a new anthropometric index to predict diabetic kidney disease, and its predictive ability is stronger than body mass index.
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Objective
Linear growth is impaired in children with type 1 diabetes (T1D) and poor metabolic control. A good metabolic control is a key therapeutic goal to prevent vascular complications and also to ensure appropriate anthropometric development during childhood. In this study, we aimed to identify and characterize the effects of glycemic variability on linear growth in children with T1D.
Methods
Data from 144 prepubertal children with T1D were evaluated. Anthropometric measurements (weight, weight-SDS, height, height-SDS, BMI, BMI-SDS) were collected and glycosylated hemoglobin (HbA1c) was measured at admission and every 4 months over a 2-year period. Glycemic variability indexes (glycemic coefficient of variation (CV), glycemic CV percentage (CV%), and the product between HbA1c-mean and HbA1c-SDS/100 (M*SDS-HbA1c/100)) were calculated. According to height-SDS changes after 2 years of follow-up, the study population was divided into three tertile groups and differences across groups were investigated for variables of interest.
Results
The three groups were similar in terms of age, gender, and follow-up period. After 2 years, all prepubertal children showed a significant positive trend of anthropometric data. Across the three tertile groups, HbA1c-SDS, CV, CV%, and M*SDS-HbA1c significantly decreased from the first to the third tertile of height-SDS. During follow-up, children with lower Δheight-SDS values reported higher values of HbA1c-SDS, CV, CV%, and M*SDS-HbA1c than subjects with higher linear growth.
Conclusions
Glycemic variability correlates with linear growth in children with T1D. Low glycemic variability indexes were reported in higher height-SDS tertiles. Δheight-SDS is inversely correlated with glycemic CV, CV%, and M*SDS-HbA1c.
