Developmental origins of type 2 diabetes: a perspective from China

Association between tea consumption and glucose metabolism and insulin secretion in the Shanghai High-risk Diabetic Screen (SHiDS) study

INTRODUCTION

The relationship between tea consumption and glucose metabolism remains controversial. This study investigated the associations of tea consumption with impaired glucose regulation, insulin secretion and sensitivity in Shanghai High-risk Diabetic Screen project.

RESEARCH DESIGN AND METHODS

A total of 2337 Chinese subjects were enrolled in the study from 2014 to 2019. Each participant conducted a 75 g oral glucose tolerance test (OGTT) with five-point glucose and insulin level examined. They also completed a nurse-administered standard questionnaire including tea, coffee, and alcohol consumption, smoking habit, physical activity, education, sleep quality, etc. RESULTS: The result showed that tea consumption was positively associated with plasma glucose levels during OGTT after adjusting for confounder (Ps <0.05) and was associated with worsening glucose tolerance (OR 1.21, 95% CI 1.01-1.44; p=0.034). Strong tea consumption or long-term tea intake (>10 years) had an increased risk of glucose intolerance (all p<0.05). These associations did not vary in participants drinking green tea. In addition, insulin secretion indexes were decreased 7.0%-13.0% in tea consumption group. Logistic regression analysis showed that tea consumption was independently associated with lower insulin secretion (homeostasis model assessment of β-cell function (HOMA-β) (OR 0.81, 95% CI 0.68-0.97; p=0.021); Stumvoll first-phase index (OR 0.81, 95% CI 0.68-0.97; p=0.020)) in a fully adjusted model. Green tea consumption showed a negative association with insulin secretion (HOMA-β (OR 0.77, 95% CI 0.62-0.96; p=0.019)).

CONCLUSIONS

Tea intake is associated with an increased risk of glucose intolerance in a large high-risk diabetic Chinese population. Habitual tea consumption subjects might have lower pancreatic β-cell function.

Determinants of macrosomia among newborns delivered in northwest Ethiopia: a case–control study

Objective

Macrosomia is associated with the risk of mortality and morbidity in neonates and their mothers. Despite the considerable public health effect of macrosomia, evidence on the determinants of macrosomia is limited in Northwest Ethiopia in general and in Amhara region in particular. Therefore, this study aimed to identify determinants of macrosomia among newborns delivered in referral hospitals in 2020 in Amhara region, Northwest Ethiopia.

Methods

A facility-based unmatched case-control study was conducted among 279 mothers and their newborns in Amhara region referral hospitals. Newborns weighing 4000 g and above and between 2500 and 3999 g were considered cases and controls, respectively. Bivariable and multivariable binary logistic regression were used to identify the determinants of macrosomia.

Results

In total, 273 of 279 mothers and their newborns (97.8% response rate) were included. The mean birth weights of cases and controls were 4312.97 ± 357.53 g and 3161.92 ± 452.12 g, respectively. Weight gain over pregnancy, antenatal follow up, physical activity during pregnancy, and neonate sex were the main determinants of macrosomia.

Conclusion

The main determinants of macrosomia were determined in this study. Government should place special emphasis on reducing the modifiable factors of macrosomia.

Predicting the Risk of Incident Type 2 Diabetes Mellitus in Chinese Elderly Using Machine Learning Techniques

Early identification of individuals at high risk of diabetes is crucial for implementing early intervention strategies. However, algorithms specific to elderly Chinese adults are lacking. The aim of this study is to build effective prediction models based on machine learning (ML) for the risk of type 2 diabetes mellitus (T2DM) in Chinese elderly. A retrospective cohort study was conducted using the health screening data of adults older than 65 years in Wuhan, China from 2018 to 2020. With a strict data filtration, 127,031 records from the eligible participants were utilized. Overall, 8298 participants were diagnosed with incident T2DM during the 2-year follow-up (2019–2020). The dataset was randomly split into training set (n = 101,625) and test set (n = 25,406). We developed prediction models based on four ML algorithms: logistic regression (LR), decision tree (DT), random forest (RF), and extreme gradient boosting (XGBoost). Using LASSO regression, 21 prediction features were selected. The Random under-sampling (RUS) was applied to address the class imbalance, and the Shapley Additive Explanations (SHAP) was used to calculate and visualize feature importance. Model performance was evaluated by the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy. The XGBoost model achieved the best performance (AUC = 0.7805, sensitivity = 0.6452, specificity = 0.7577, accuracy = 0.7503). Fasting plasma glucose (FPG), education, exercise, gender, and waist circumference (WC) were the top five important predictors. This study showed that XGBoost model can be applied to screen individuals at high risk of T2DM in the early phrase, which has the strong potential for intelligent prevention and control of diabetes. The key features could also be useful for developing targeted diabetes prevention interventions.

Ginseng-plus-Bai-Hu-Tang Combined with Western Medicine for the Treatment of Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis

Objective

Type 2 diabetes mellitus (T2DM) is a chronic disease characterized by chronic hyperglycemia, which is also accompanied by changes in blood lipids and protein. According to research reports, Ginseng-plus-Bai-Hu-Tang (GBHT) has significant antihyperglycemic activity. Nevertheless, the evidence of effectiveness is not enough. In order to verify the effectiveness and safety of GBHT combined with conventional Western medicine (CWM) in the treatment of T2DM, we carried out this meta-analysis.

Method

We collected 7 electronic databases from the inception to September 1, 2021; then, 12 studies were selected. The data analysis and methodological evaluation were conducted by the software RevMan 5.3.3 and Stata 12.0.

Results

The meta-analysis revealed that when GBHT was adopted in combination with CWM, the effective rate (OR = 2.98, 95% CI = [2.01, 4.43], P < 0.00001), the FBG (MD = −0.86, 95% CI = [−1.06, −0.65], P < 0.00001), 2hBG (MD = −0.80, 95% CI = [−1.05, −0.55], P < 0.00001), and HbA1c (MD = −0.64, 95% CI = [−0.98, −0.30], P = 0.0002) of T2DM patients improved significantly compared with the control group. After GBHT combined with CWM treatment, HOME-RI (MD = −0.75, 95% CI = [−1.38, −0.12] P = 0.02) of T2DM patients was superior to CWM alone. In comparison, the benefit from FINS (MD = −1.42, 95% CI = [−4.46, −1.62], P = 0.36) was not apparent. In addition, none of the adverse events mentioned occurred, indicating that it is safe enough.

Conclusion

GBHT combined with CWM is an effective and safe as adjunctive treatment for patients with T2DM. Nevertheless, due to the limitation of the quality of the included studies, additional high-quality researches are required to further confirm these results.

The effects of gestational diabetes mellitus with maternal age between 35 and 40 years on the metabolite profiles of plasma and urine

Background

Gestational diabetes mellitus (GDM) is defined as impaired glucose tolerance in pregnancy and without a history of diabetes mellitus. While there are limited metabolomic studies involving advanced maternal age in China, we aim to investigate the metabolomic profiling of plasma and urine in pregnancies complicated with GDM aged at 35–40 years at early and late gestation.

Methods

Twenty normal and 20 GDM pregnant participants (≥ 35 years old) were enlisted from the Complex Lipids in Mothers and Babies (CLIMB) study. Maternal plasma and urine collected at the first and third trimester were detected using gas chromatography-mass spectrometry (GC-MS).

Results

One hundred sixty-five metabolites and 192 metabolites were found in plasma and urine respectively. Urine metabolomic profiles were incapable to distinguish GDM from controls, in comparison, there were 14 and 39 significantly different plasma metabolites between the two groups in first and third trimester respectively. Especially, by integrating seven metabolites including cysteine, malonic acid, alanine, 11,14-eicosadienoic acid, stearic acid, arachidic acid, and 2-methyloctadecanoic acid using multivariant receiver operating characteristic models, we were capable of discriminating GDM from normal pregnancies with an area under curve of 0.928 at first trimester.

Conclusion

This study explores metabolomic profiles between GDM and normal pregnancies at the age of 35–40 years longitudinally. Several compounds have the potential to be biomarkers to predict GDM with advanced maternal age. Moreover, the discordant metabolome profiles between the two groups could be useful to understand the etiology of GDM with advanced maternal age.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-022-04416-5.

The influence of maternal blood glucose during pregnancy on weight outcomes at birth and preschool age in offspring exposed to hyperglycemia first detected during pregnancy, in a South African cohort

Introduction

Little is known about the influence of hyperglycemia first detected in pregnancy (HFDP) on weight outcomes in exposed offspring in Africa. We investigated the influence of maternal blood glucose concentrations during pregnancy on offspring weight outcomes at birth and preschool age, in offspring exposed to HFDP, in South Africa.

Research design and methods

Women diagnosed with HFDP had data routinely collected during the pregnancy and at delivery, at a referral hospital, and the offspring followed up at preschool age. Maternal fasting, oral glucose tolerance test 1 and 2-hour blood glucose were measured at diagnosis of HFDP and 2-hour postprandial blood glucose during the third trimester. Offspring were classified as either those exposed to diabetes first recognized in pregnancy (DIP) or gestational diabetes (GDM). At birth, neonates were classified into macrosomia, low birth weight (LBW), large for gestational age (LGA), appropriate (AGA) and small for gestational age (SGA)groups. At preschool age, offspring had height and weight measured and Z-scores for weight, height and BMI calculated.

Results

Four hundred and forty-three neonates were included in the study at birth, with 165 exposed to DIP and 278 exposed to GDM. At birth, the prevalence of LGA, macrosomia and LBW were 29.6%, 12.2% and 7.5%, respectively, with a higher prevalence of LGA and macrosomia in neonates exposed to DIP. At pre-school age, the combined prevalence of overweight and obesity was 26.5%. Maternal third trimester 2-hour postprandial blood glucose was significantly associated with z-scores for weight at birth and preschool age, and both SGA and LGA at birth.

Conclusion

In offspring exposed to HFDP, there is a high prevalence of LGA and macrosomia at birth, and overweight and obesity at preschool age, with higher prevalence in those exposed to DIP, compared to GDM. Maternal blood glucose control during the pregnancy influences offspring weight at birth and preschool age.

Assisted reproduction technology and long-term cardiometabolic health in the offspring

Ronald Ma and co-authors discuss Emma Norrman and colleagues' accompanying research study on the health of children born with assisted reproductive technology.

Diabetes and cardiometabolic risk in South Asian youth: A review

South Asians are at increased risk for developing type 2 diabetes and cardiovascular disease at lower body mass index compared to other ancestral groups. Many factors contribute to this increased risk, including genetics, maternal-fetal factors, diet, fitness, body composition, and unique pathophysiology. Increased cardiometabolic risk is also seen at younger ages in South Asian individuals as compared to their White counterparts. This risk persists in migrant communities outside of South Asia. With the growing prevalence of obesity, diabetes, and cardiovascular disease in the South Asian population, it is imperative that we had better understand the mechanisms underlying this increased risk and implement strategies to address this growing public health problem during childhood and adolescence.

Evaluation of dietary pattern in early pregnancy using the FIGO Nutrition Checklist compared to a food frequency questionnaire

Objective

To evaluate the reliability and utility of the FIGO Nutrition Checklist to identify dietary and nutritional inadequacy in early pregnancy by comparing it against nutritional indicators and dietary quality indices (Dietary Approaches to Stop Hypertension [DASH] score, Mediterranean Diet Score [MDS], and Dietary Quality Index‐International [DQI‐I]), derived by a locally validated food frequency questionnaire (FFQ).

Methods

A prospective cohort study of healthy Chinese pregnant women randomly recruited between September 2017 and April 2018 at their first antenatal appointment. Women completed the FIGO Nutrition Checklist (translated into Chinese) and the FFQ. Spearman correlation was performed to examine association between the Checklist and dietary quality indices or food and nutrient intakes, calculated based on dietary data from the FFQ.

Results

Of 160 participants, 156 (97.5%) completed both the FIGO Nutrition Checklist and FFQ and were included. There were 148 (95%) women who reported at least one suboptimal dietary behavior using the Checklist. Checklist score was significantly associated with dietary quality indices (DASH ρ=0.344, P<0.001; DQI‐I ρ=0.304, P<0.001; MDS ρ=0.164, P=0.041). The Checklist question on fruit/vegetables was significantly associated with fiber, vitamin C, and fruit and vegetable intake as calculated from the FFQ (0.325 ≤ ρ ≤0.441, P<0.001). The question on dairy intake was significantly associated with intake of calcium, milk and dairy products captured via FFQ (0.576 ≤ ρ ≤0.655, P<0.001).

Conclusion

This study supports the use of the FIGO Nutrition Checklist to identify women with suboptimal dietary quality in early pregnancy.

The FIGO Nutrition Checklist was significantly associated with dietary quality indices derived from a validated food frequency questionnaire. The Checklist can help identify nutritional issues in pregnancy.

Nomogram for prediction of gestational diabetes mellitus in urban, Chinese, pregnant women

Background

This study sought to develop and validate a nomogram for prediction of gestational diabetes mellitus (GDM) in an urban, Chinese, antenatal population.

Methods

Age, pre-pregnancy body mass index (BMI), fasting plasma glucose (FPG) in the first trimester and diabetes in first degree relatives were incorporated as validated risk factors. A prediction model (nomogram) for GDM was developed using multiple logistic regression analysis, from a retrospective study conducted on 3956 women who underwent their first antenatal visit during 2015 in Shanghai. Performance of the nomogram was assessed through discrimination and calibration. We refined the predicting model with t-distributed stochastic neighbor embedding (t-SNE) to distinguish GDM from non-GDM. The results were validated using bootstrap resampling and a prospective cohort of 6572 women during 2016 at the same institution.

Results

Advanced age, pre-pregnancy BMI, high first-trimester, fasting, plasma glucose, and, a family history of diabetes were positively correlated with the development of GDM. This model had an area under the receiver operating characteristic (ROC) curve of 0.69 [95% CI:0.67–0.72, p < 0.0001]. The calibration curve for probability of GDM showed good consistency between nomogram prediction and actual observation. In the validation cohort, the ROC curve was 0.70 [95% CI: 0.68–0.72, p < 0.0001] and the calibration plot was well calibrated. In exploratory and validation cohorts, the distinct regions of GDM and non-GDM were distinctly separated in the t-SNE, generating transitional boundaries in the image by color difference. Decision curve analysis showed that the model had a positive net benefit at threshold between 0.05 and 0.78.

Conclusions

This study demonstrates the ability of our model to predict the development of GDM in women, during early stage of pregnancy.

Progression to type 2 diabetes mellitus and associated risk factors after hyperglycemia first detected in pregnancy: A cross-sectional study in Cape Town, South Africa

BACKGROUND

Global data indicate that women with a history of hyperglycemia first detected in pregnancy (HFDP) are at up to 7 times risk of progressing to type 2 diabetes mellitus (T2DM) compared with their counterparts who have pregnancies that are not complicated by hyperglycemia. However, there are no data from the sub-Saharan African region, which has the highest projected rise in diabetes prevalence globally. The aim of this study was to determine the proportion of women who progress to T2DM and associated risk factors 5 to 6 years after HFDP in Cape Town, South Africa.

METHODS AND FINDINGS

All women with HFDP, at a major referral hospital in Cape Town, were followed up 5 to 6 years later using a cross-sectional study. Each participant had a 75 g oral glucose tolerance test; anthropometric measurements and a survey were administered. A total of 220 participants were followed up. At this time, their mean age was 37.2 years (SD 6.0). Forty-eight percent (95% CI 41.2-54.4) progressed to T2DM, 5.5% (95% CI 3.1-9.4) had impaired fasting glucose, and 10.5% (95% CI 7.0-15.3) had impaired glucose tolerance. Of the participants who progressed to T2DM, 47% were unaware of their diabetes status. When HFDP was categorized post hoc according to WHO 2013 guidelines, progression in the diabetes in pregnancy (DIP) group was 81% (95% CI 70.2-89.0) and 31.3% (95% CI 24.4-39.3) in the gestational diabetes mellitus (GDM) category. Factors associated with risk of progression to T2DM were; at follow-up: waist circumference (odds ratios [OR] 1.1, 95% CI 1.0-1.1, p = 0.007), hip circumference (OR 0.9, 95% CI 0.8-1.0, p = 0.001), and BMI (OR 1.1, 95% CI 1.0-1.3, p = 0.001), and at baseline: insulin (OR 25.8, 95% CI 3.9-171.4, p = 0.001) and oral hypoglycaemic treatment during HFDP (OR 4.1, 95% CI 1.3-12.9, p = 0.018), fasting (OR 2.7, 95% CI 1.5-4.8, p = 0.001), and oral glucose tolerance test 2-hour glucose concentration at HFDP diagnosis (OR 4.3, 95% CI 2.4-7.7, p < 0.001). Our findings have limitations in that we did not include a control group of women without a history of HFDP.

CONCLUSIONS

The progression to T2DM in women with previous HFDP found in this study highlights the need for interventions to delay or prevent progression to T2DM after HFDP. In addition, interventions to prevent HFDP may also contribute to reducing the risk of T2DM.

Epidemic T2DM, early development and epigenetics: implications of the Chinese Famine

The gene-environment interactions resulting from famine and the subsequent increased intergenerational risk of type 2 diabetes mellitus (T2DM) have contributed to the current epidemic of T2DM in China, which poses major social, health and economic challenges. The epidemic of T2DM could threaten national development in China through premature morbidity and mortality from T2DM and associated non-communicable diseases. The Chinese Famine (1959-1961), as a contributor to the nation's current national T2DM epidemic, provides an important and urgent public health warning. The effects of the famine give a strong message that research and actions that address the prevention of T2DM cannot be confined to lifestyle measures, as used in the landmark Da Qing study and the lifestyle prevention programmes and pharmaceutical interventions used in Western nations. To stem the T2DM epidemic, a new paradigm for prevention of T2DM must be developed. This paradigm should include a very strong emphasis on pregnancy planning and maternal and child health during and after the pregnancy. Without action, intergenerational cycles initiated by epigenetic modifications resulting from adverse environmental stimuli during the critical window of early development in utero might continue to fuel the T2DM epidemic in future generations.

Berberine Could Ameliorate Cardiac Dysfunction via Interfering Myocardial Lipidomic Profiles in the Rat Model of Diabetic Cardiomyopathy

Background: Diabetic cardiomyopathy (DCM) is considered to be a distinct clinical entity independent of concomitant macro- and microvascular disorders, which is initiated partly by disturbances in energy substrates. This study was to observe the dynamic modulations of berberine in DCM rats and explore the changes of lipidomic profiles of myocardial tissue. Methods: Sprague-Dawley (SD) rats were fed high-sucrose and high-fat diet (HSHFD) for totally 22 weeks and intraperitoneally (i.p.) injected with 30 mg/kg of streptozotocin (STZ) at the fifth week to induce DCM. Seventy-two hours after STZ injection, the rats were orally given with berberine at 10, 30 mg/kg and metformin at 200 mg/kg, respectively. Dynamic changes of cardiac function, heart mass ratios and blood lipids were observed at f 4, 10, 16, and 22, respectively. Furthermore, lipid metabolites in myocardial tissue at week 16 were profiled by the ultra-high-performance liquid chromatography coupled to a quadruple time of flight mass spectrometer (UPLC/Q-TOF/MS) approach. Results: Berberine could protect against cardiac diastolic and systolic dysfunctions, as well as cardiac hypertrophy, and the most effective duration is with 16-week of administration. Meanwhile, 17 potential biomarkers of phosphatidylcholines (PCs), phosphatidylethanolamines (PEs) and sphingolipids (SMs) of DCM induced by HSFD/STZ were identified. The perturbations of lipidomic profiles could be partly reversed with berberine intervention, i.e., PC (16:0/20:4), PC (18:2/0:0), PC (18:0/18:2), PC (18:0/22:5), PC (20:4/0:0), PC (20:4/18:0), PC (20:4/18:1), PC (20:4/20:2), PE (18:2/0:0), and SM (d18:0/16:0). Conclusions: These results indicated a close relationship between PCs, PEs and SMs and cardiac damage mechanisms during development of DCM. The therapeutic effects of berberine on DCM are partly caused by interferences with PCs, PEs, and SMs metabolisms.

The Effects of Tai Chi on Type 2 Diabetes Mellitus: A Meta-Analysis

OBJECTIVE

To investigate the effects of Tai chi in type 2 diabetes mellitus (type-2 DM) patients using systematic review and meta-analysis.

METHODS

Seven electronic resource databases were searched, and randomized controlled trials on the role of Tai chi in type-2 DM patients were retrieved. The meta-analysis was performed with RevMan 5.3, and research quality evaluation was conducted with the modified Jadad scale.

RESULTS

Fourteen studies, with 798 individuals related to the intervention of Tai chi on diabetes, were included. The results showed that, compared with nonexercise, Tai chi had the effect of lowering fasting blood glucose [MD = -1.39, 95% CI (-1.95, -0.84), P < 0.0001] and the subgroup effect size decreased with the increase of total exercise amount, there is no significant difference between Tai chi and other aerobic exercises [MD = -0.50, 95% CI (-1.02, 0.02), P = 0.06]; compared with nonexercise, Tai chi could reduce HbA1c [MD = -0.21, 95% CI (-0.61, 0.19), P = 0.31], and the group effect size decreased with the increase of total exercise amount. The reducing HbA1c effect of Tai chi was better than that of other aerobic exercises, but the difference was at the margin of statistical significance [MD = -0.19, 95% CI (-0.37, 0.00), P = 0.05]; compared with nonexercise, Tai chi had the effect of reducing 2 h postprandial blood glucose [MD = -2.07, 95% CI (-2.89, -1.26), P = 0.0002], there is no significant difference between Tai chi and other aerobic exercises in reducing 2 h postprandial blood glucose [MD = -0.44, 95% CI (-1.42, 0.54), P = 0.38].

CONCLUSION

Tai chi can effectively affect the management of blood glucose and HbA1c in type-2 DM patients. Long-term adherence to Tai chi has a better role in reducing blood glucose and HbA1c levels in type 2 DM patients.

Epidemiology of diabetes and diabetic complications in China

The People's Republic of China (herein referred to as China) has witnessed one of the most dramatic rises in diabetes prevalence anywhere in the world. The latest epidemiological study suggests that approximately 11% of the population has diabetes, with a significant proportion remaining undiagnosed. Risk factors for diabetes in the Chinese population are similar to those in other populations, though gestational diabetes and young-onset diabetes is becoming increasingly common. Data on the prevalence of diabetic complications remain limited, though cardio-renal complications account for significant morbidity and mortality. Other diabetes-related comorbidities are becoming increasingly common, with cancer emerging as a major cause of mortality among individuals with diabetes. There are many challenges and obstacles that impede effective diabetes prevention and the delivery of care, though much progress has occurred over recent years. Lessons learnt from how China has responded to the challenges posed by the diabetes epidemic will be invaluable for other countries facing the many threats of diabetes and its complications.