Predictors Of Glucose Intolerance Research Articles

Maternal height as a predictor of glucose intolerance in the postpartum and its relationship with maternal pre-gestational weight.

Short stature predicts higher risk of developing type 2 diabetes. We studied the association between height and glucose intolerance in women with gestational diabetes mellitus (GDM) and whether this association differed according to body mass index (BMI). Retrospective study of the Portuguese GDM registry. missing data on postpartum oral glucose tolerance test (OGTT) or BMI. postpartum glucose intolerance (diabetes mellitus or prediabetes on the 6-8weeks postpartum OGTT). Women were divided by mean height and compared. A multivariate logistic regression was used, and the analysis was stratified by BMI (cut-off: 30kg/m2) and interaction was tested. We included 7402 women; mean height was 161.9 ± 6.2cm. Taller women had lower BMI and lower rates of glucose intolerance (6.8 vs. 8.8%, p = 0.002). Women with BMI < 30kg/m2 were taller than those with obesity. Height associated with glucose intolerance. The multivariate adjusted OR of glucose intolerance was 0.98 (95% CI 0.96-0.99), p = 0.001, per 1cm increase in height. This association was only observed in women with BMI < 30kg/m2: OR 0.97 (95% CI 0.95-0.99), < 0.001. There was no such association in women with BMI ≥ 30kg/m2: OR 0.99 (95% CI 0.97-1.02), p = 0.65. P for interaction between BMI and height was 0.09. In non-obese pre-gestational women, height is inversely associated with postpartum glucose intolerance. Per 1cm increase in height, women present a 3% decrease in the risk of developing diabetes mellitus or prediabetes.

An Analysis of Glucose Effectiveness in Subjects With or Without Type 2 Diabetes via Hierarchical Modeling.

Glucose effectiveness, defined as the ability of glucose itself to increase glucose utilization and inhibit hepatic glucose production, is an important mechanism maintaining normoglycemia. We conducted a minimal modeling analysis of glucose effectiveness at zero insulin (GEZI) using intravenous glucose tolerance test data from subjects with type 2 diabetes (T2D, n=154) and non-diabetic (ND) subjects (n=343). A hierarchical statistical analysis was performed, which provided a formal mechanism for pooling the data from all study subjects, to yield a single composite population model that quantifies the role of subject specific characteristics such as weight, height, age, sex, and glucose tolerance. Based on the resulting composite population model, GEZI was reduced from 0.021 min–1 (standard error – 0.00078 min–1) in the ND population to 0.011 min–1 (standard error – 0.00045 min–1) in T2D. The resulting model was also employed to calculate the proportion of the non–insulin-dependent net glucose uptake in each subject receiving an intravenous glucose load. Based on individual parameter estimates, the fraction of total glucose disposal independent of insulin was 72.8% ± 12.0% in the 238 ND subjects over the course of the experiment, indicating the major contribution to the whole-body glucose clearance under non-diabetic conditions. This fraction was significantly reduced to 48.8% ± 16.9% in the 30 T2D subjects, although still accounting for approximately half of the total in the T2D population based on our modeling analysis. Given the potential application of glucose effectiveness as a predictor of glucose intolerance and as a potential therapeutic target for treating diabetes, more investigations of glucose effectiveness in other disease conditions can be conducted using the hierarchical modeling framework reported herein.

Waist-height ratio: How well does it predict glucose intolerance and systemic hypertension?

AimThe aim of this study is to assess whether WHtR is a better predictor of glucose intolerance and systemic hypertension than some other obesity indices. MethodsThis is a cross-sectional observational study among four hundred (4 0 0) participants in a Northern Nigerian population. Four (4) participants were eventually excluded due to incomplete data, therefore data from three hundred and ninety six (3 9 6) participants were used in the final analysis. The study assessed whether WHtR is a better predictor of glucose intolerance and systemic hypertension compared to some other obesity indices. Participants were recruited after due consent, then bio-data, blood pressure levels, and some anthropometric measurements were obtained. Subsequently, plasma glucose levels (fasting [FPG] and 2-hour post 75 g glucose load [2HrPPG]) were measured. Data was entered into Microsoft Excel, then analyzed using IBM SPSS version 23. ResultsData from three hundred and ninety six (3 9 6) participants (4 excluded due to incomplete details) were analyzed. Logistic regression of obesity indices showed that WHtR was the best predictor of glucose intolerance with odds ratio (OD) of 20.74 (CI 2.80-155, p < 0.001), followed by WC with OD of 1.89 (CI 1.83-3.94, p < 0.001), then WHR with OD of 1.69 (CI 1.06-8.22, p = 0.009). The least but significant predictor of glucose intolerance was BMI with odds ratio of 1.12 (CI 1.06-3.18, p < 0.001).Furthermore, logistic regression of obesity indices showed that WHtR was the strongest predictor of systemic hypertension with OD of 2.32 (CI 4.85-14.96, p < 0.001), followed by BMI (OD 1.99, CI 1.96-2.05, p = 0.031), then WC (OD 1.95, CI 1.90-1.99, p = 0.020). The weakest predictor of systemic hypertension was WHR (OD 1.26, CI 0.04-1.88, p = 0.181). ConclusionWHtR had the highest predictive power for both glucose intolerance and systemic hypertension compared to BMI, WC, and WHR.

Prevalence and Risk Factors for Glucose Intolerance among Saudi Women with Gestational Diabetes.

Objectives The objective of this study was to determine the incidence and risk factors of glucose intolerance one year after delivery in women with gestational diabetes (GDM). Methods All women who had GDM and completed one year since delivery at King Khalid University Hospital were contacted to participate in the study. Based on to the American Diabetes Association criteria and the results of fasting blood glucose (FPG) and HbA1c, participants were classified into three groups: diabetic, impaired glucose tolerance (IGT), and normal. The incidence of diabetes and IGT was calculated. Clinical, biochemical, and sociodemographic predictors of glucose intolerance were compared between the three groups. Odds ratio (OR) for risk factors with P value less than 0.05 was calculated. Results From a total 316 eligible women, 133 fulfilled the inclusion criteria and agreed to participate in the study. From the study participants, 58 (44%) women were normoglycemic, 60 (45%) women had IGT, and 15 (11%) women were diabetic. The odds of developing IGT or diabetes increased to nearly fourfold when women needed insulin for the control of GDM during pregnancy (OR 3.8, 95% CI 0.81–18.3, P = 0.08) and to nearly one-and-a-half-fold when they have positive family history of T2DM (OR 1.2, 95% CI 0.74–2.09, P = 0.40). Nevertheless, none of the odds ratios was statistically significant. Conclusion The incidence of postpartum hyperglycemia (diabetes and IGT) is very high in Saudi women with GDM. Family history of diabetes and insulin treatment of GDM may be predictors of postpartum hyperglycemia.

Risk factors for postpartum glucose intolerance in women with gestational diabetes mellitus

Objectives: To determine the risk factors for glucose intolerance (GI) during the postpartum period in women with gestational diabetes mellitus (GDM).Methods: This prospective cohort study included 72 Japanese women with GDM who underwent 75 g oral glucose tolerance tests (OGTT) at 12 weeks after delivery. These women were divided into the GI group and the normal group based on postpartum OGTT. Risk factors for GI, including levels of blood glucose (BG), area under the curve (AUC) of glucose, AUC insulin, HbA1c, homeostasis model assessment-insulin resistance (HOMA-IR), HOMA-β, insulinogenic index (II) and the oral disposition index (DI) in antepartum OGTT, were analyzed by logistic regression analyses.Results: Of the 72 women, 60 (83.3%) were normal and 12 (16.7%) had GI. By univariate logistic regression analyses, fasting BG, AUC glucose, HOMA-β, II and oral DI were selected as risk factors for GI. Multivariate logistic regression analysis revealed that the level of II in antepartum OGTT was a significant factor that predicted GI after delivery (odds ratio, 0.008; 95% CI, 0.0001–0.9; p < 0.05).Conclusions: II measured by OGTT during pregnancy might be a useful predictor of GI within the early postpartum period in women with GDM.

Promoting women's health in a complex world

Promoting women's health in a complex world

Hypoadiponectinaemia enhances waist circumference as a predictor of glucose intolerance and clustering of risk factors in Chinese men

Aim This study aimed to confirm the hypothesis that adiponectin levels can enhance the discriminative value of waist circumference (WC) in predicting impaired glycaemic status and clustering of risk factors. Methods We used receiver operating characteristic (ROC) curve analysis to define the optimal cut-off value of adiponectin to predict diabetes in Chinese men with no relevant past medical history. This value was combined with WC to increase its discriminative power in ascertaining impaired glycaemic status and various cardiovascular risk factors. Results In 360 men (mean ± S.D.; age: 41.3 ± 9.2 years), the mean ± S.D. adiponectin level was 5.2 ± 2.7 μg/mL. Based on oral glucose tolerance tests (OGTTs), 84 men (23.3%) had undiagnosed diabetes, 52 (14.4%) had impaired glucose tolerance (IGT) and 224 (62.3%) had normal glucose tolerance. On ROC analysis, 5.7 μg/mL was the optimal cut-off value of adiponectin in this population to predict diabetes. Compared with subjects who had normal WC (defined as less than 90 cm) and high adiponectin levels (≥ 5.7 μg/mL), the likelihood ratio of diabetes was 2.54 in those with central obesity and hypoadiponectinaemia. Conclusion The combined use of low adiponectin levels and large WC measures has greater discriminative power than using either index alone to identify subjects at particular risk of glucose intolerance and clustering of risk factors.

Use of glucose, insulin, and C-reactive protein to determine need for glucose tolerance testing.

Glucose intolerance has been shown to be a better predictor of morbidity and mortality than impaired fasting glucose. However, glucose tolerance tests are inconvenient and expensive. This study evaluated the relative frequencies of glucose intolerance and impaired fasting glucose and sought to determine if 2-hour glucose could be predicted from simple demographic and laboratory data in an obese population. Eighty-nine obese subjects (median BMI 35 kg/m(2), range 30 to 40 kg/m(2)) underwent glucose tolerance testing. Using step-wise linear and logistic regression analysis, fasting glucose, high-sensitivity C-reactive protein (hsCRP), fasting insulin, high-density lipoprotein cholesterol, triglycerides, weight, height, BMI, waist circumference, hip circumference, waist-to-hip ratio, sex, and age were assessed as predictors of glucose intolerance. Impaired glucose tolerance was more prevalent (27%) than impaired fasting glucose (5.6%). Only fasting glucose and hsCRP were significant (p < 0.05) independent predictors of impaired 2-hour glucose (>140 mg/dL). A fasting glucose > or =100 mg/dL or an hsCRP > 0.32 mg/dL (upper quartile of the normal range) detected 81% (sensitivity) of obese subjects with impaired glucose tolerance; however, specificity was poor (46%). Fasting insulin > or =6 micro U/mL had better sensitivity (92%) but poorer specificity (30%). Impaired glucose tolerance is more common than impaired fasting glucose in an obese population. Possible strategies to avoid doing glucose tolerance tests in all obese patients would be to do glucose tolerance testing only in those whose fasting glucose is > or =100 mg/dL or whose hsCRP exceeds 0.32 mg/dL or those whose fasting insulin is > or =6 micro U/mL.

Predictors of glucose intolerance (GI) in the West of Scotland Coronary Prevention Study (WOSCOPS)

Predictors of glucose intolerance (GI) in the West of Scotland Coronary Prevention Study (WOSCOPS)

Discriminating glucose tolerance status by regions of interest of dual-energy X-ray absorptiometry. Clinical implications of body fat distribution.

To determine whether measuring body fat distribution by dual-energy X-ray absorptiometry (DEXA) can be used to discriminate glucose tolerance status. Using a 75-g oral glucose tolerance test, a total of 1,015 Chinese subjects (559 men and 456 women) were categorized as having normal glucose tolerance (NGT), impaired glucose tolerance (IGT), or diabetes. Blood pressure and lipid profiles of these subjects were measured. Waist-to-hip ratio (WHR) and DEXA were used to evaluate the varying patterns of body fat distribution among the groups. Body fat distribution, as reflected by WHR and the centrality index, showed significant partial correlation coefficients with glycosylated hemoglobin, blood pressure, and lipid profiles in all subjects. After adjusting for age and BMI, there were significant differences among the three glycemic groups for all the cardiovascular risk factors except for total cholesterol level. The diabetic group had a significantly higher WHR and centrality index, but lower femoral fat percentage than the NGT and IGT groups. The diabetic group also showed higher abdominal fat percentage than the NGT group. Moreover, the IGT group had a higher centrality index than the NGT group. However, no significant differences were found in the percentage of lean tissue mass among the three groups. Using multiple stepwise logistic regression models, the centrality index remained a significant factor for discriminating different glucose tolerance status independent of the percentage total body fat. Central obesity has shown significant correlation with cardiovascular risk factors among the three different glycemic groups. Centrality index measured by DEXA appears to be the better predictor of glucose intolerance, compared with WHR, abdominal fat, and general obesity (reflected by percentage total body fat or BMI) in a large cohort of the Chinese population.

Postpartum testing for antecedent gestational diabetes

Gestational diabetes is a predictor of glucose intolerance in subsequent pregnancies and in the nongravid state. Many pregnant women are not tested for gestational diabetes, although they or their offspring may show signs suggestive of antecedent hyperglycemia. We examined the diagnostic utility of a postpartum (within 48 hours), 100 gm, oral glucose tolerance test and cord plasma glucose, cord plasma C-peptide, and 2-hour neonatal plasma glucose tests to detect antecedent gestational diabetes in women with documented gestational diabetes (n = 37) or with normal glucose tolerance test results late in the third trimester (n = 28). The 1-hour, 2-hour, and incremental 1-hour + 2-hour ([1-hour − fasting] + [2-hour − fasting]) glucose values of the postpartum glucose toelrance test showed significant differences between study participants with and without gestational diabetes (164 ± 30 versus 115 ± 22, 145 ± 31 versus 101 ± 21, and 153 ± 51 versus 67 ± 33 mg/dl, respectively, p < 0.025). Maternal fasting and 3-hour postpartum glucose tolerance test glucose, cord plasma glucose, cord plasma C-peptide, and 2-hour neonatal plasma glucose values showed no significant between-group differences. Receiver operating characteristic curve analyses for these tests indicated that the incremental 1-hour + 2-hour postpartum glucose tolerance test glucose values best sustain test specificity at the low test threshold values necessary for high test sensitivity. A threshold of 110 mg/dl for this test yielded a predicted specificity of 90% and sensitivity of 80% with regard to antecedent gestational diabetes.