Diabetes: Leveraging the Tipping Point of the Diabetes Pandemic

Effects of the amount and type of carbohydrates used in type 2 diabetes diets in animal models: A systematic review

Type 2 diabetes mellitus (T2DM) is among the most prevalent diseases in the world, affecting over 420 million people. The disease is marked by a poor metabolic effect of insulin leading to chronic hyperglycaemia, which can result in microvascular complications. It is widely known that postprandial glycaemia is reliant on the total carbohydrate content of a meal. However, the importance of the amount and the source of these carbohydrates remains controversial due to mechanisms other than insulin secretion. Oxidative stress, inflammation, pyruvate production and the quality of the intestinal microbiota, resulting in plasma lipopolysaccharides and short-chain fatty acids production, play an important role in blood sugar control and consequently in type 2 diabetes. Thus, we systematically reviewed the preclinical evidences on the impact of the amount and type of carbohydrate found in different diets and its influence on blood glucose levels in diabetic animals. We used a comprehensive and structured search in biomedical databases Medline (PubMed), Scopus and Web of Science, recovering and analyzing 27 original studies. Results showed that sucrose-rich diets deteriorated diabetic condition in animal models regardless of the total dietary carbohydrate content. On the other hand, fiber, particularly resistant starch, improved blood glucose parameters through direct and indirect mechanisms, such as delayed gastric emptying and improved gut microbiota. All studies used rodents as animal models and male animals were preferred over females. Improvements in T2DM parameters in animal models were more closely related to the type of dietary carbohydrate than to its content on a diet, i. e., resistant starch seems to be the most beneficial source for maintaining normoglycemia. Results show that current literature is at high risk of bias due to neglecting experimental methods.

Glucose metabolism among obese and non-obese children of mothers with gestational diabetes

OBJECTIVES

Abdominal obesity is more closely associated with diabetes than general obesity in adults, however, it is unknown which kind of obesity is more closely associated with abnormal glucose metabolism in children.

RESEARCH DESIGN AND METHODS

We recruited 973 children (aged 3.08±1.06) of mothers with prior gestational diabetes mellitus (GDM). Children's height, weight, waist circumstance, fasting glucose and insulin were measured using standardized methods. Logistic regression models were used to assess the single and joint associations of general and abdominal obesity with the risks of hyperglycemia (the upper quartile of fasting glucose), insulin resistance (the upper quartile of homeostatic model assessment of insulin resistance (HOMA-IR)), and β-cell dysfunction (the lower quartile of HOMA-%β).

RESULTS

Compared with normal weight children, children with general overweight/obesity had higher levels of HOMA-IR and HOMA-%β, higher ORs for hyperglycemia (1.56, 95% CI 1.06 to 2.30) and insulin resistance (3.44, 95% CI 2.32 to 5.09), but a lower OR for β-cell dysfunction (0.65, 95% CI 0.41 to 1.04). Children with abdominal obesity had an increased risk of insulin resistance (2.54, 95% CI 1.71 to 3.76) but not hyperglycemia and β-cell dysfunction compared with children with normal waist circumstance. In the joint analyses, general overweight children with and without abdominal obesity had an increased risk of hyperglycemia and insulin resistance compared with normal weight children.

CONCLUSIONS

General obesity was more closely associated with abnormal glucose metabolism than abdominal obesity in children of mothers with GDM.

Effects of obesity and a history of gestational diabetes on the risk of postpartum diabetes and hyperglycemia in Chinese women: Obesity, GDM and diabetes risk

OBJECTIVE

To evaluate the independent or combined effects of gestational diabetes (GDM) and pre-pregnancy and postpartum BMI on the odds of postpartum diabetes and hyperglycemia.

METHODS

The study samples included 1263 women with prior GDM and 705 women without GDM. Postpartum 1-7 years diabetes was diagnosed by the standard oral glucose tolerance test.

RESULTS

The multivariable-adjusted odds ratios among women with prior GDM, compared with those without it, were 7.52 for diabetes and 2.27 for hyperglycemia. The multivariable-adjusted odds ratios at different postpartum BMI levels (<24, 24-27.9, and ≥ 28 kg/m²) were 1.00, 2.80, and 8.08 for diabetes (P_trend < 0.001), and 1.00, 2.10, and 4.42 for hyperglycemia (P_trend < 0.001), respectively. Women with high body fat (≥31.9%) or abdominal obesity (≥85 cm) had a 2.7-6.9-fold higher odds ratio for diabetes or hyperglycemia. Women with both obesity and prior GDM had the highest risk of diabetes or hyperglycemia compared with non-obese women without GDM. Non-obese women with prior GDM had the same risk of diabetes and hyperglycemia as non-GDM women with obesity. When using Cox regression models, the results were very close to those using logistic regression models.

CONCLUSIONS

Maternal prior GDM and pre-pregnancy or postpartum obesity contribute equally to postpartum diabetes and hyperglycemia risk.

Nomograms for incident risk of post-partum type 2 diabetes in Chinese women with prior gestational diabetes mellitus

OBJECTIVE

Counselling patients with gestational diabetes mellitus (GDM) on their individual risk of post-partum type 2 diabetes (T2D) is challenging. This study aimed to develop nomograms for predicting incident risk of post-partum T2D in women with GDM diagnosed by WHO 1998 criteria.

METHODS

We performed a retrospective cohort study in 1263 Chinese women with GDM, of whom 83 were diagnosed as T2D at 2.3 years post-partum. Multivariate Cox proportional hazards models were used to investigate the independent predictors for post-partum T2D. The results of multivariate analyses were used to formulate nomograms for predicting incident risk of post-partum T2D. The predictive accuracy was evaluated using the area under the receiver operating characteristic curve (AUROC).

RESULTS

On multivariate analysis, independent predictors of post-partum T2DM in women with GDM included family history of diabetes [hazard ratio (HR) and its 95% confidential interval (95% CI): 2.06 (95% CI: 1.32-3.22)], history of pregnancy-induced hypertension [3.11 (95% CI: 1.86-5.21)], pre-pregnancy BMI [1.00, 1.90 (95% CI: 1.14-3.16), and 3.67 (95% CI: 2.03-6.63) for BMI <24, 24-28, and ≥28 kg/m² ], and 2-hour glucose at 26-30 gestational weeks [1.00, 2.84 (95% CI: 1.42-5.69), and 9.42 (95% CI: 4.46-19.90) for 2-hour glucose at 7.8 ~ <8.5, 8.5 ~ <11.1, and ≥11.1 mmol/L). The overall AUROC of nomogram was 82.8% (95% CI: 78.1%-87.5%), with AUROCs of 85.9% (95% CI: 79.7%-92.1%) and 83.2% (95% CI: 77.9%-88.6%) for post-partum 2-year and 3-year risk of T2D, respectively.

CONCLUSIONS

This easy-to-use nomogram, with non-invasive clinical characteristics, can accurately predict the risk of post-partum T2D in women with GDM. It may facilitate risk communication between patients and clinicians.

DEXAMETHASONE STRESS TEST: A PILOT CLINICAL STUDY FOR IDENTIFICATION OF INDIVIDUALS HIGHLY PRONE TO DEVELOP TYPE 2 DIABETES

OBJECTIVE

We examined whether the "Dexamethasone Stress Test" exhibits the requisite high predictive ability to identify individuals highly prone to develop type 2 diabetes mellitus (T2DM).

METHODS

Seven years ago, we administered an oral glucose tolerance test (OGTT) to 33 individuals without T2DM and repeated the OGTT 24 hours after a single oral dose of 8 mg dexamethasone (Dex); all participants had a first-degree relative with T2DM, and close to half had prediabetes. We calculated receiver operating characteristic (ROC) curves for all parameters derived from the OGTT before and after Dex in individuals who subsequently developed diabetes compared to individuals who did not.

RESULTS

At 7 years of follow-up, 9 individuals had developed T2DM, while 24 remained without diabetes. None of the OGTT-derived parameters before administration of Dex had an area under the ROC curve of >0.8. However, 24 hours after Dex, three parameters, including fasting plasma insulin, homeostatic model assessment-insulin resistance, and 2-hour plasma glucose level, exhibited areas under the ROC curves of 0.84, 0.86, and 0.92, respectively.

CONCLUSION

The Dexamethasone Stress Test appears to be a good to excellent test in identifying individuals highly prone to develop T2DM.

ABBREVIATIONS

AUC = area under the curve; Dex = dexamethasone; HOMA-IR = homeostatic model assessment-insulin resistance; NGT = normal glucose tolerance; OGTT = oral glucose tolerance test; PreDiab = prediabetes; ROC = receiver operating characteristic; T2DM = type 2 diabetes mellitus.