Childhood BMI and Fasting Glucose and Insulin Predict Adult Type 2 Diabetes: The International Childhood Cardiovascular Cohort (i3C) Consortium

A Clinical Tool to Relate Youth Risk Factors to Adult Cardiovascular Events and Type 2 Diabetes: The i3C Consortium

OBJECTIVE

To translate data relating childhood cardiovascular (CV) risk factors and adult CV disease and type 2 diabetes mellitus (T2DM) to clinically actionable values.

STUDY DESIGN

A prospective observational study (n=38,589) in the International Childhood Cardiovascular Cohort (i3C) Consortium. Children at age 3 through 19 years were enrolled in the 1970s and 1980s and followed for over 30 years. Five childhood CV risk factors (smoking, body mass index [BMI], systolic blood pressure [SBP], triglycerides [TG], and total cholesterol [TC]) were related to adult CV events. Secondary analyses in a subset included low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), glucose and insulin level. Age- and sex-specific z-scores were calculated for each risk factor, and a combined-risk z-score was calculated by averaging z-scores for the 5 key CV risk factors. Risk factor z-scores were back-transformed to natural units for clinical interpretation, with hazard ratios for adult CV events presented in color coded tables (green: no increased risk; orange: 1.4 to <2.0-fold increased risk; red: at least doubling of risk). Risk levels for development of adult T2DM based on BMI, glucose, and insulin were similarly calculated and presented.

RESULTS

Increased risk for CV events was observed at levels lower than currently defined abnormal clinical thresholds except for TC. Doubling of risk was observed at high normal levels just below the clinical cut point for abnormality. Risk for adult T2DM began at levels of BMI and glucose currently considered normal.

CONCLUSION

Based on data showing significant relationships between childhood CV risk factors and adult CV events and T2DM, this study shows that risk in childhood begins below levels currently considered normal.

Interventions for Weight Management in Children and Adolescents: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force

Importance

Body mass index (BMI) of the 95th or greater percentile for age and sex is common among young people, and its prevalence has increased in recent decades.

Objective

To examine the benefits and harms of weight management interventions initiated in health care settings among children and adolescents with high BMI.

Data Sources

MEDLINE via Ovid, PsycINFO via Ovid, and the Cochrane Central Registry of Controlled Trials through January 12, 2023; ongoing surveillance through January 26, 2024.

Study Selection

English-language studies of weight management interventions (behavioral and pharmacologic, including liraglutide, semaglutide, orlistat, and phentermine/topiramate) among children aged 2 to 18 years with high BMI (eg, ≥85th or ≥95th percentile for age and sex) conducted in or recruited from health care settings.

Data Extraction and Synthesis

One investigator abstracted data; a second checked for accuracy. Outcomes with sufficient evidence for meta-analysis were pooled using random-effects models.

Main Outcomes and Measures

BMI and other weight-related outcomes, cardiometabolic measures, quality of life, physical activity, dietary pattern scores, and harms.

Results

Fifty-eight randomized clinical trials (RCTs) were included (N = 10 143). Behavioral interventions were associated with small reductions in BMI and other weight outcomes after 6 to 12 months (28 RCTs [n = 4494]; mean difference in change between groups, -0.7 [95% CI, -1.0 to -0.3]). Larger effects were seen in interventions with higher contact hours and that offered physical activity sessions. Reporting was sparse for outcomes other than BMI, with few significant findings. Semaglutide and phentermine/topiramate had the largest effects on BMI (eg, 1 RCT [n = 201] for semaglutide; mean difference, -6.0 [95% CI, -7.3 to -4.6]). The very few studies that evaluated outcomes after medication discontinuation showed immediate weight regain. Gastrointestinal adverse effects were common with liraglutide, semaglutide, and orlistat. Serious adverse effects were rare, but no studies had follow-up longer than 17 months.

Conclusions and Relevance

In the short term, weight management interventions led to lower BMI in children and adolescents, with no evidence of serious harm. Evidence is lacking about how weight management interventions affect BMI beyond 1 year and after medication discontinuation and about longer-term effects on other outcomes.

Development and validation of the baby eating behaviour coding system (BEBECS) to assess eating behaviour during complementary feeding

Eating behaviour in children is a matter of study for which diverse tools have been designed. Coding systems for videotaped meals allow the extraction of detailed in vivo information; however, there is no tool available for infants following a Baby-Led Weaning (BLW) method. This study aimed to create and validate a new tool to assess eating behaviour in infants during weaning, applicable regardless of the complementary feeding method. The Baby Eating Behaviour Coding System (BEBECS) was developed comprising time variables, behaviours, feeder-led actions, and other meal-related variables. Sixty videos of infants aged 6-18 months following spoon-feeding (SF) or BLW methods were coded by two trained coders. These scores were analysed together with intake and maternal ratings of liking and calmness. Additionally, combined analysis and internal comparison assessed the possible differences in BEBECS variables between SF and BLW. Inter-rater and test-retest reliability had good to excellent agreement: Cohen's Kappa >0.75, Lin's CCC >0.70, and Intraclass Correlation Coefficient >0.75, for almost all variables. Infants' liking and intake of the offered food correlated positively with meal duration and total count of mouth approaches but negatively with having leftovers and time between mouth approaches. Infants' calmness and tiredness were negatively correlated. More food than initially offered was available during the meal in BLW but not in SF. There was a tendency towards more autonomous behaviour in BLW infants regarding changes observed in the time the food was in the mouth at each stage (6, 12, and 18 months). In conclusion, BEBECS has the potential to be a valid tool for application in the research of infant eating behaviour during weaning by trained coders.

Use of lipid ratios to predict vascular target organ damage in youth

BACKGROUND

Elevated lipid levels are risk factors for early atherosclerosis. Lipid ratios have emerged as potentially stronger predictors of adverse cardiovascular changes and atherogenic cholesterol. Risk stratification in youth with obesity or type 2 diabetes may be improved by using lipid ratios. We sought to determine if lipid ratios would identify abnormalities in arterial structure and stiffness in adolescents and young adults.

METHODS

A total of 762 youth aged 10-24 years had laboratory, anthropometric, blood pressure, and carotid intima-media thickness and arterial stiffness data collected. Subjects were stratified into tertiles (low, mid, high) of lipid ratios and non-high-density lipoprotein cholesterol (HDL-C). Vascular outcomes by tertile were assessed by analyses of variance. General linear models were constructed for each lipid value and included demographics, risk factors, and vascular measures. Correlations between lipid markers, vascular measures, and low-density lipoprotein (LDL) particle size and number were conducted.

RESULTS

There was a progressive increase in arterial thickness and stiffness across all three lipid ratios and non-HDL-C. The triglyceride to HDL-C (TG/HDL-C) ratio remained an independent predictor of arterial thickness and stiffness after adjusting for other cardiovascular risk factors. TG/HDL-C had the highest correlations with arterial stiffness and small, dense LDL.

CONCLUSIONS

Arterial stiffness is increased in youth with high lipid ratios with TG/HDL-C being the most consistent marker of vascular changes. These data suggest that identification of high TG/HDL-C in these individuals may lead to earlier intervention to prevent atherosclerotic cardiovascular disease.

Tracking correlations and predictors of plasma glucose in young adulthood: A comprehensive analysis from adolescence to young adulthood in TLGS study

AIMS

We investigated the tracking correlations between fasting plasma glucose (FPG) in adolescence with both FPG and 2-hour post-load glucose (2 h-PG) in adulthood, and identified the predictors of FPG and 2 h-PG in young adulthood using traditional risk factors during adolescence and adulthood.

METHODS

We included 2188 participants (1033 male) from the Tehran lipid and glucose study within the age ranges 11-18 and 19-40 years during 1999-2018. The area under the curve (AUC) was computed using the growth curve models, and predictors were identified by the linear regression model.

RESULTS

The partial correlation between AUCs of FPG in adolescence and adulthood was 0.37 (P < 0.001). The correlation between AUCs of FPG in adolescence and 2 h-PG in adulthood was 0.17 (P < 0.001). The AUC of FPG was a significant positive predictor for both FPG and 2 h-PG in young adulthood. Other predictors of adult FPG included sex, as well as BMI and the ratio of triglycerides to HDL-cholesterol during both adolescence and adulthood.

CONCLUSIONS

Tracking correlation was observed for FPG, suggesting that monitoring and managing risk factors in adolescence may have implications for future glucose metabolism in young adulthood.

A Proposed Pediatric Clinical Cardiovascular Health Reference Standard

INTRODUCTION

Clinical cardiovascular health is a construct that includes 4 health factors-systolic and diastolic blood pressure, fasting glucose, total cholesterol, and body mass index-which together provide an evidence-based, more holistic view of cardiovascular health risk in adults than each component separately. Currently, no pediatric version of this construct exists. This study sought to develop sex-specific charts of clinical cardiovascular health for age to describe current patterns of clinical cardiovascular health throughout childhood.

METHODS

Data were used from children and adolescents aged 8-19 years in six pooled childhood cohorts (19,261 participants, collected between 1972 and 2010) to create reference standards for fasting glucose and total cholesterol. Using the models for glucose and cholesterol as well as previously published reference standards for body mass index and blood pressure, clinical cardiovascular health charts were developed. All models were estimated using sex-specific random-effects linear regression, and modeling was performed during 2020-2022.

RESULTS

Models were created to generate charts with smoothed means, percentiles, and standard deviations of clinical cardiovascular health for each year of childhood. For example, a 10-year-old girl with a body mass index of 16 kg/m2 (30th percentile), blood pressure of 100/60 mm Hg (46th/50th), glucose of 80 mg/dL (31st), and total cholesterol of 160 mg/dL (46th) (lower implies better) would have a clinical cardiovascular health percentile of 62 (higher implies better).

CONCLUSIONS

Clinical cardiovascular health charts based on pediatric data offer a standardized approach to express clinical cardiovascular health as an age- and sex-standardized percentile for clinicians to assess cardiovascular health in childhood to consider preventive approaches at early ages and proactively optimize lifetime trajectories of cardiovascular health.

Clinical Characterization of Data-Driven Diabetes Clusters of Pediatric Type 2 Diabetes

Background

Pediatric Type 2 diabetes (T2D) is highly heterogeneous. Previous reports on adult-onset diabetes demonstrated the existence of diabetes clusters. Therefore, we set out to identify unique diabetes subgroups with distinct characteristics among youth with T2D using commonly available demographic, clinical, and biochemical data.

Methods

We performed data-driven cluster analysis (K-prototypes clustering) to characterize diabetes subtypes in pediatrics using a dataset with 722 children and adolescents with autoantibody-negative T2D. The six variables included in our analysis were sex, race/ethnicity, age, BMI Z-score and hemoglobin A1c at the time of diagnosis, and non-HDL cholesterol within first year of diagnosis.

Results

We identified five distinct clusters of pediatric T2D, with different features, treatment regimens and risk of diabetes complications: Cluster 1 was characterized by higher A1c; Cluster 2, by higher non-HDL; Cluster 3, by lower age at diagnosis and lower A1c; Cluster 4, by lower BMI and higher A1c; and Cluster 5, by lower A1c and higher age. Youth in Cluster 1 had the highest rate of diabetic ketoacidosis (DKA) (p = 0.0001) and were most prescribed metformin (p = 0.06). Those in Cluster 2 were most prone to polycystic ovarian syndrome (p = 0.001). Younger individuals with lowest family history of diabetes were least frequently diagnosed with diabetic ketoacidosis (p = 0.001) and microalbuminuria (p = 0.06). Low-BMI individuals with higher A1c had the lowest prevalence of acanthosis nigricans (p = 0.0003) and hypertension (p = 0.03).

Conclusions

Utilizing clinical measures gathered at the time of diabetes diagnosis can be used to identify subgroups of pediatric T2D with prognostic value. Consequently, this advancement contributes to the progression and wider implementation of precision medicine in diabetes management.

Fasting indices of glucose-insulin-metabolism across life span and prediction of glycemic deterioration in children with obesity from new diagnostic cut-offs

Background

Fasting indices of glucose-insulin-metabolism are an easy and affordable tool to assess insulin resistance. We aimed to establish reference ranges for fasting insulin indices that reflect age-dependent variation over the entire life span and subsequently test their clinical application regarding the prediction of glycemic deterioration in children.

Methods

We calculated age- and puberty-dependent reference values for HOMA-IR, HOMA2-IR, HOMA-β, McAuley index, fasting insulin, and fasting glucose from 6994 observations of 5512 non-obese healthy subjects aged 5-80 years. Applying those references, we determined the prevalence of insulin resistance among 2538 subjects with obesity. Furthermore, we investigated the intraindividual stability and the predictive values for future dysglycemia of these fasting indices in 516 children and adolescents with obesity up to 19 years of follow-up. We validated the results in three independent cohorts.

Findings

There was a strong age-dependent variation of all indices throughout the life span, including prolonged recovery of pubertal insulin resistance and a subsequent continuous increase throughout adulthood. Already from age 5 years onwards, >40% of children with obesity presented with elevated parameters of insulin resistance. Applying newly developed reference ranges, insulin resistance among children with obesity doubled the risk for future glycemic deterioration (HOMA-IR HR 1.88 (95% CI 1.1-3.21)), fasting insulin HR 1.89 (95% CI 1.11-3.23). In contrast, fasting glucose alone was not predictive for emerging dysglycemia in children with obesity (HR 1.03 (95% CI 0.62-1.71)). The new insulin-based thresholds were superior to fasting glucose and HbA1c in detecting children eventually manifesting with dysglycemia in prospective analyses.

Interpretation

The variation of fasting glucose-insulin-metabolism across the life span necessitates age-specific reference ranges. The improved prediction of future glycemic deterioration by indices based on fasting insulin beyond simple glucose measures alone could help to stratify risk characteristics of children with obesity in order to guide patient-tailored prevention and intervention approaches.

Funding

German Research Foundation (DFG)-through SFB 1052, project number 209933838, subproject C5; Federal Ministry of Education and Research, Germany; European Union-European Regional Development Fund; Free State of Saxony. The German Diabetes Association, the CarbHealth consortium (01EA1908B). EU-IMI2-Consortium SOPHIA (grant agreement No 875534), German Center for Diabetes Research (DZD), grant number 82DZD14E03.

Childhood Obesity and Cardiovascular Disease Risk

PURPOSE OF REVIEW

The global epidemic of youth-onset obesity is tightly linked to the rising burden of cardiometabolic disease across the lifespan. While the link between childhood obesity and cardiovascular disease is established, this contemporary review summarizes recent and novel advances in this field that elucidate the mechanisms and impact of this public health issue.

RECENT FINDINGS

The review highlights the emerging data supporting the relationship between childhood adverse events, social determinants of health, and systemic and institutional systems as etiological factors. We also provide updates on new screening and treatment approaches including updated nutrition and dietary guidelines and benchmarks for pediatric obesity screening, novel pharmacological agents for pediatric obesity and type 2 diabetes such as glucagon-like 1 peptide receptor agonists, and we discuss the long-term safety and efficacy data on surgical management of pediatric obesity. The global burden of pediatric obesity continues to rise and is associated with accelerated and early vascular aging especially in youth with obesity and type 2 diabetes. Socio-ecological determinants of risk mediate and moderate the relationship of childhood obesity with cardiometabolic disease. Recognizing the importance of neighborhood level influences as etiological factors in the development of cardiovascular disease is critical for designing effective policies and interventions. Novel surgical and pharmacological interventions are effective pediatric weight-loss interventions, but future research is needed to assess whether these agents, within a socio-ecological framework, will be associated with abatement of the pediatric obesity epidemic and related increased cardiovascular disease risk.

Association of Complement C3 With Incident Type 2 Diabetes and the Mediating Role of BMI: A 10-Year Follow-Up Study

CONTEXT

Impairment of immune and inflammatory homeostasis is reported to be one of the causal factors of diabetes. However, the association of complement C3 levels with incident diabetes in humans remains unclear.

OBJECTIVE

This study aimed to examine the association between C3 levels and incident type 2 diabetes mellitus (T2DM), and further explore the potential mediating role of body mass index (BMI) in C3-T2DM associations.

METHODS

We determined serum C3 levels of 2662 nondiabetic middle-aged and elderly (64.62 ± 7.25 years) individuals from the Dongfeng-Tongji cohort at baseline. Cox regression was employed to examine the incidence of T2DM in relationship to C3 levels during 10 years of follow-up. Mediation analysis was further applied to assess potential effect of BMI on the C3-T2DM associations.

RESULTS

Overall, 711 (26.7%) participants developed T2DM during 23 067 person-years of follow-up. Higher serum C3 was significantly associated with higher risk of incident T2DM after full adjustment (HR [95% CI] = 1.16 [1.05, 1.27]; per SD higher). Compared with the first quartile of C3 levels, the HR in the fourth quartile was 1.52 (95% CI = [1.14, 2.02]; Ptrend = 0.029). Robust significant linear dose-response relationship was observed between C3 levels and BMI (Poverall < 0.001, Pnonlinear = 0.96). Mediation analyses indicated that BMI might mediate 41.0% of the associations between C3 and T2DM.

CONCLUSION

The present prospective study revealed that C3 could be an early biomarker for incident T2DM, and that BMI might play a potential mediating role in the C3-T2DM associations, which provided clues for the pathogenesis of diabetes.

Cardiometabolic Risk and Its Relationship With Visceral Adiposity in Children With Cerebral Palsy

Context

Adults with cerebral palsy (CP) display a higher prevalence of cardiometabolic disease compared with the general population. Studies examining cardiometabolic disease risk in children with CP are limited.

Objective

The purpose of this study was to determine if children with CP exhibit higher cardiometabolic risk than typically developing children, and to examine its relationship with visceral adiposity and physical activity.

Methods

Thirty ambulatory children with CP and 30 age-, sex-, and race-matched typically developing control children were tested for blood lipids, glucose, and the homeostatic model assessment of insulin resistance (HOMA-IR). Visceral fat was assessed using dual-energy x-ray absorptiometry. Physical activity was assessed using accelerometer-based monitors.

Results

Children with CP had higher total cholesterol, low-density lipoprotein cholesterol, and non-high-density lipoprotein cholesterol (non-HDL-C), glucose, prevalence of dyslipidemia, prevalence of prediabetes, and visceral fat mass index (VFMI) and lower physical activity than controls (all P < .05). In the groups combined, non-HDL-C and glucose were positively related to VFMI (r = 0.337 and 0.313, respectively, P < .05), and non-HDL-C and HOMA-IR were negatively related to physical activity (r = -0.411 and -0.368, respectively, P < .05). HOMA-IR was positively related to VFMI in children with CP (r = 0.698, P < .05), but not in controls. Glucose was not related to physical activity in children with CP, but it was negatively related in controls (r = -0.454, P < .05).

Conclusion

Children with CP demonstrate early signs of cardiometabolic disease, which are more closely related to increased visceral adiposity than decreased physical activity.

Prospective Test Performance of Nonfasting Biomarkers to Identify Dysglycemia in Children and Adolescents

INTRODUCTION

Test performance screening measures for dysglycemia have not been evaluated prospectively in youth. This study evaluated the prospective test performance of random glucose (RG), 1-h nonfasting glucose challenge test (1-h GCT), hemoglobin A1c (HbA1c), fructosamine (FA), and 1,5-anhydroglucitol (1,5-AG) for identifying dysglycemia.

METHODS

Youth ages 8-17 years with overweight or obesity (body mass index, BMI, ≥85th percentile) without known diabetes completed nonfasting tests at baseline (n = 176) and returned an average of 1.1 years later for two formal fasting 2-h oral glucose tolerance tests. Outcomes included glucose-defined dysglycemia (fasting plasma glucose ≥100 mg/dL or 2-h plasma glucose ≥140 mg/dL) or elevated HbA1c (≥5.7%). Longitudinal test performance was evaluated using receiver-operating characteristic (ROC) curves and calculation of area under the curve (AUC).

RESULTS

Glucose-defined dysglycemia, elevated HbA1c, and either dysglycemia or elevated HbA1c were present in 15 (8.5%), 11 (6.3%), and 23 (13.1%) participants at baseline, and 16 (9.1%), 18 (10.3%), and 28 (15.9%) participants at follow-up. For prediction of glucose-defined dysglycemia at follow-up, RG, 1-h GCT, and HbA1c had similar performance (0.68 (95% CI: 0.55-0.80), 0.76 (95% CI: 0.64-0.89), and 0.70 (95% CI: 0.56-0.84)), while FA and 1,5-AG performed poorly. For prediction of HbA1c at follow-up, baseline HbA1c had strong performance (AUC 0.93 [95% CI: 0.88-0.98]), RG had moderate performance (AUC 0.67 [95% CI: 0.54-0.79]), while 1-h GCT, FA, and 1,5-AG performed poorly.

CONCLUSION

HbA1c and nonfasting glucose tests had reasonable longitudinal discrimination identifying adolescents at risk for dysglycemia, but performance depended on outcome definition.

Identification of robust deep neural network models of longitudinal clinical measurements

Deep learning (DL) from electronic health records holds promise for disease prediction, but systematic methods for learning from simulated longitudinal clinical measurements have yet to be reported. We compared nine DL frameworks using simulated body mass index (BMI), glucose, and systolic blood pressure trajectories, independently isolated shape and magnitude changes, and evaluated model performance across various parameters (e.g., irregularity, missingness). Overall, discrimination based on variation in shape was more challenging than magnitude. Time-series forest-convolutional neural networks (TSF-CNN) and Gramian angular field(GAF)-CNN outperformed other approaches (P < 0.05) with overall area-under-the-curve (AUCs) of 0.93 for both models, and 0.92 and 0.89 for variation in magnitude and shape with up to 50% missing data. Furthermore, in a real-world assessment, the TSF-CNN model predicted T2D with AUCs reaching 0.72 using only BMI trajectories. In conclusion, we performed an extensive evaluation of DL approaches and identified robust modeling frameworks for disease prediction based on longitudinal clinical measurements.

Childhood Cardiovascular Risk Factors and Adult Cardiovascular Events

BACKGROUND

Childhood cardiovascular risk factors predict subclinical adult cardiovascular disease, but links to clinical events are unclear.

METHODS

In a prospective cohort study involving participants in the International Childhood Cardiovascular Cohort (i3C) Consortium, we evaluated whether childhood risk factors (at the ages of 3 to 19 years) were associated with cardiovascular events in adulthood after a mean follow-up of 35 years. Body-mass index, systolic blood pressure, total cholesterol level, triglyceride level, and youth smoking were analyzed with the use of i3C-derived age- and sex-specific z scores and with a combined-risk z score that was calculated as the unweighted mean of the five risk z scores. An algebraically comparable adult combined-risk z score (before any cardiovascular event) was analyzed jointly with the childhood risk factors. Study outcomes were fatal cardiovascular events and fatal or nonfatal cardiovascular events, and analyses were performed after multiple imputation with the use of proportional-hazards regression.

RESULTS

In the analysis of 319 fatal cardiovascular events that occurred among 38,589 participants (49.7% male and 15.0% Black; mean [±SD] age at childhood visits, 11.8±3.1 years), the hazard ratios for a fatal cardiovascular event in adulthood ranged from 1.30 (95% confidence interval [CI], 1.14 to 1.47) per unit increase in the z score for total cholesterol level to 1.61 (95% CI, 1.21 to 2.13) for youth smoking (yes vs. no). The hazard ratio for a fatal cardiovascular event with respect to the combined-risk z score was 2.71 (95% CI, 2.23 to 3.29) per unit increase. The hazard ratios and their 95% confidence intervals in the analyses of fatal cardiovascular events were similar to those in the analyses of 779 fatal or nonfatal cardiovascular events that occurred among 20,656 participants who could be evaluated for this outcome. In the analysis of 115 fatal cardiovascular events that occurred in a subgroup of 13,401 participants (31.0±5.6 years of age at the adult measurement) who had data on adult risk factors, the adjusted hazard ratio with respect to the childhood combined-risk z score was 3.54 (95% CI, 2.57 to 4.87) per unit increase, and the mutually adjusted hazard ratio with respect to the change in the combined-risk z score from childhood to adulthood was 2.88 (95% CI, 2.06 to 4.05) per unit increase. The results were similar in the analysis of 524 fatal or nonfatal cardiovascular events.

CONCLUSIONS

In this prospective cohort study, childhood risk factors and the change in the combined-risk z score between childhood and adulthood were associated with cardiovascular events in midlife. (Funded by the National Institutes of Health.).

Natural history and determinants of dysglycemia in Canadian children with parental obesity from ages 8-10 to 15-17 years: The QUALITY cohort

In children, the mechanisms implicated in deterioration of glucose homeostasis versus reversion to normal glucose tolerance (NGT) remain uncertain. We aimed to describe the natural history of dysglycemia from childhood to late adolescence and to identify its early determinants. We used baseline (8-10 years, n = 630), 1st follow-up (10-12 years, n = 564) and 2nd follow-up (15-17 years, n = 377) data from the QUALITY cohort of White Canadian children with parental obesity. Children underwent a 2-h oral glucose tolerance test at each cycle with plasma glucose and insulin measured at 0/30/60/90/120 min. American Diabetes Association criteria defined dysglycemia (impaired fasting glucose, impaired glucose tolerance or type 2 diabetes). Longitudinal patterns of insulin sensitivity and beta-cell function were estimated using generalized additive mixed models. Model averaging identified biological, sociodemographic and lifestyle-related determinants of dysglycemia. Of the children NGT at baseline, 66 (21%) developed dysglycemia without reverting to NGT. Among children with dysglycemia at baseline, 24 (73%) reverted to NGT. In children with dysglycemia at 1st follow-up, 18 (53%) later reverted to NGT. Among biological, sociodemographic and lifestyle determinants at 8-10 years, only fasting and 2-h glucose were associated with developing dysglycemia (odds ratio [95% CI] per 1 mmol/L increase: 4.50 [1.06; 19.02] and 1.74 [1.11; 2.73], respectively). Beta-cell function decreased by 40% in children with overweight or obesity. In conclusion, up to 75% of children with dysglycemia reverted to NGT during puberty. Children with higher fasting and 2-h glucose were at higher risk for progression to dysglycemia, while no demographic/lifestyle determinants were identified.

Genetically predicted childhood obesity and adult atrial fibrillation: A mendelian randomization study

BACKGROUND AND AIMS

It is unclear whether the association of childhood obesity with adult atrial fibrillation observed in observational studies reflects causal effects. The aim of this study was to evaluate the association of childhood obesity with adult atrial fibrillation using genetic instruments.

METHODS AND RESULTS

We used a two-sample Mendelian randomization (MR) design to evaluate the association between childhood obesity and adult atrial fibrillation. Two sets of genetic variants (15 single nucleotide polymorphisms [SNPs] for childhood body mass index [BMI] and 12 SNPs for dichotomous childhood obesity) were selected as instruments. Summary data on SNP-childhood obesity and SNP-atrial fibrillation associations were obtained from recently published genome-wide association studies. Effect estimates were evaluated using inverse-variance weighted (IVW) methods. Other MR analyses, including MR-Egger, simple and weighted median, weighted MBE and MR-PRESSO methods were performed in sensitivity analyses. The IVW models showed that both a genetically predicted one-standard deviation increase in childhood BMI (kg/m²) and higher log-odds of childhood obesity were associated with a substantial increase in the risk of atrial fibrillation (OR = 1.22, 95% CI: 1.11-1.34, P < 0.001; OR = 1.09, 95% CI: 1.04-1.14, P < 0.001). MR-Egger regression showed no evidence of genetic pleiotropy for childhood BMI (intercept = 0.000, 95% CI: -0.024 to 0.023), but for childhood obesity (intercept = -0.036, 95% CI: -0.057 to -0.015). Similar results were observed using leave-one-out and other MR methods in sensitivity analyses.

CONCLUSIONS

This MR analysis found a consistent association between genetically predicted childhood obesity and an increased risk of adult atrial fibrillation. Further research is warranted to validate our findings.

Status of Cardiovascular Health in Chinese Children and Adolescents

Background

The American Heart Association defined “ideal cardiovascular health (CVH)” in pediatric populations to promote primordial prevention in cardiovascular diseases. Little is known about CVH and associated sociodemographic factors among Chinese children and adolescents.

Objectives

This study aimed to evaluate CVH and the associations with sociodemographic characteristics in Chinese children and adolescents.

Methods

This cross-sectional study analyzed baseline data of 15,583 participants aged 7 to 17 years from a Chinese national intervention program against obesity (2013-2014). CVH status was estimated according to 4 health behaviors (nonsmoking, body mass index, physical activity, and diet) and 3 health factors (total cholesterol, blood pressure, and fasting plasma glucose), using revised American Heart Association criteria. Multinomial logistic regression was used to assess the association between sociodemographic characteristics and the number of ideal CVH metrics.

Results

The prevalence of ideal CVH status was 1.7% (males: 1.9%; females: 1.6%) in the study population. The prevalence of ideal CVH behaviors and ideal health factors was 3.1% (males 3.3%; females: 3.0%) and 53.6% (males: 52.4%; females: 54.9%), respectively. Ideal fasting plasma glucose was the most prevalent component (males: 94.4%; females: 97.4%), whereas ideal physical activity (males: 34.6%; females: 23.9%) and diet (males: 28.3%; females: 30.1%) were the least prevalent. Female sex, younger age, undeveloped economy, residence in the southern region, and no family history of cardiovascular diseases were associated with more ideal CVH metrics.

Conclusions

Ideal CVH status in Chinese children and adolescents is alarmingly rare. Physical activity and diet are key to promotion of CVH. Effective interventions are needed to promote CVH and reduce health disparities in early life.

A Mini-Review of Pediatric Anthropometrics as Predictors of Future Insulin Resistance

The impact of rising rates of childhood obesity is far reaching. Metabolic syndrome in children is increasing, yet for most children the consequences of excess adiposity will manifest in adulthood. Excess early fat accrual is a risk factor for future insulin resistance. However, certain types of fat and patterns of fat distribution are more relevant than others to metabolic risk. Therefore, adiposity measures are important. The link between childhood obesity and future insulin resistance was initially established with body mass index (BMI), but BMI is an in imperfect measure of adiposity. It is worthwhile to evaluate other anthropometrics as they may more accurately capture metabolic risk. While measures such as waist to height ratio are established as superior screening measures in adulthood - the findings are not as robust in pediatrics. Emerging evidence suggests that alternative anthropometrics may be slightly superior to BMI in identifying those youth most at risk of developing insulin resistance, but the clinical significance of that superiority appears limited. Increasing study is needed in longitudinal and varied cohorts to identify which pediatric anthropometric best predicts adult insulin resistance. We review alternative anthropometrics as predictors of future insulin resistance and identify current gaps in knowledge and potential future directions of inquiry.

Characteristics associated with early- vs. later-onset adult diabetes: The CARDIA study

AIMS

Differences in risk profiles for individuals with early- (<40 years old) vs. later-onset (≥40 years old) diabetes were examined.

METHODS

A nested case-comparison study design using 30-year longitudinal data from the Coronary Artery Risk Development in Young Adults (CARDIA) study was used. Survey data (socio-demographics, family history, medical records, and lifestyle behaviors), obesity-related measures (body mass index, weight), blood pressure, and laboratory data (insulin, fasting glucose, 2-h glucose, and lipids) were used to examine progression patterns of diabetes development in those with early-onset vs. later-onset diabetes.

RESULTS

Of 605 participants, 120 were in early-onset group while 485 were in later-onset group. Early-onset group had a lower A Priori Diet Quality Score, but not statistically significant at baseline; however, the between-group difference became significant at the time that diabetes was first detected (p = 0.026). The physical activity intensity score consistently decreased from baseline to the development of diabetes in both the early- and later-onset groups. Early-onset group showed more dyslipidemia at baseline and at the time that diabetes was first detected, and rapid weight gain from baseline to the development of diabetes.

CONCLUSIONS

Emphases on lifestyle modification and risk-based diabetes screening in asymptomatic young adults are necessary for early detection and prevention.

Poor In Utero Growth, and Reduced β-Cell Compensation and High Fasting Glucose From Childhood, Are Harbingers of Glucose Intolerance in Young Indians

OBJECTIVE

India is a double world capital of early-life undernutrition and type 2 diabetes. We aimed to characterize life course growth and metabolic trajectories in those developing glucose intolerance as young adults in the Pune Maternal Nutrition Study (PMNS).

RESEARCH DESIGN AND METHODS

PMNS is a community-based intergenerational birth cohort established in 1993, with serial information on parents and children through pregnancy, childhood, and adolescence. We compared normal glucose-tolerant and glucose-intolerant participants for serial growth, estimates of insulin sensitivity and secretion (HOMA and dynamic indices), and β-cell compensation accounting for prevailing insulin sensitivity.

RESULTS

At 18 years (N = 619), 37% of men and 20% of women were glucose intolerant (prediabetes n = 184; diabetes n = 1) despite 48% being underweight (BMI <18.5 kg/m²). Glucose-intolerant participants had higher fasting glucose from childhood. Mothers of glucose-intolerant participants had higher glycemia in pregnancy. Glucose-intolerant participants were shorter at birth. Insulin sensitivity decreased with age in all participants, and those with glucose intolerance had consistently lower compensatory insulin secretion from childhood. Participants in the highest quintile of fasting glucose at 6 and 12 years had 2.5- and 4.0-fold higher risks, respectively, of 18-year glucose intolerance; this finding was replicated in two other cohorts.

CONCLUSIONS

Inadequate compensatory insulin secretory response to decreasing insulin sensitivity in early life is the major pathophysiology underlying glucose intolerance in thin rural Indians. Smaller birth size, maternal pregnancy hyperglycemia, and higher glycemia from childhood herald future glucose intolerance, mandating a strategy for diabetes prevention from early life, preferably intergenerationally.

Diabetes: Concepts of β-Cell Organ Dysfunction and Failure Would Lead to Earlier Diagnoses and Prevention

As the world endures a viral pandemic superimposed on a diabetes pandemic, the latter incorporates most of the comorbidities associated with the former, thereby exacerbating risk of death in both. An essential approach to both pandemics is prevention and unrealized earlier treatment. Thus, in this Perspective relating to diabetes, we emphasize a paradigm of, first, reversible β-cell organ dysfunction and then irreversible β-cell organ failure, which directly indicate the potential for earlier prevention, also unrealized in current guidelines. Four pillars support this paradigm: epidemiology, pathophysiology, molecular pathology, and genetics. A substantial worldwide knowledge base defines each pillar and informs a more aggressive preventive approach to most forms of the disorder. This analysis seeks to clarify the temporal and therapeutic relationships between lost β-cell function and content, illuminating the potential for earlier diagnoses and, thus, prevention. We also propose that myriad pathways leading to most forms of diabetes converge at the endoplasmic reticulum, where stress can result in β-cell death and content loss. Finally, genetic and nongenetic origins common to major types of diabetes can inform earlier diagnosis and, potentially, prevention, with the aim of preserving β-cell mass.

Establishment of noninvasive diabetes risk prediction model based on tongue features and machine learning techniques

BACKGROUND

Diabetes is a chronic noncommunicable disease with high incidence rate. Diabetics without early diagnosis or standard treatment may contribute to serious multisystem complications, which can be life threatening. Timely detection and intervention of prediabetes is very important to prevent diabetes, because it is inevitable in the development and progress of the disease.

OBJECTIVE

Our objective was to establish the predictive model that can be applied to evaluate people with blood glucose in high and critical state.

METHODS

We established the diabetes risk prediction model formed by a combined TCM tongue diagnosis with machine learning techniques. 1512 subjects were recruited from the hospital. After data preprocessing, we got the dataset 1 and dataset 2. Dataset 1 was used to train classical machine learning model, while dataset 2 was used to train deep learning model. To evaluate the performance of the prediction model, we used Classification Accuracy(CA), Precision, Recall, F1-score, Precision-Recall curve(P-R curve), Area Under the Precision-Recall curve(AUPRC), Receiver Operating Characteristic curve(ROC curve), Area Under the Receiver Operating Characteristic curve(AUROC), then selected the best diabetes risk prediction model.

RESULTS

On the test set of dataset 1, the CA of non-invasive Stacking model was 71 %, micro average AUROC was 0.87, macro average AUROC was 0.84, and micro average AUPRC was 0.77. In the critical blood glucose group, the AUROC was 0.84, AUPRC was 0.67. In the high blood glucose group, AUROC was 0.87, AUPRC was 0.83. On the validation set of dataset 2, the CA of ResNet50 model was 69 %, micro average AUROC was 0.84, macro average AUROC was 0.83, and micro average AUPRC was 0.73. In the critical blood glucose group, AUROC was 0.88, AUPRC was 0.71. In the high blood glucose group, AUROC was 0.80, AUPRC was 0.76. On the test set of dataset 2, the CA of ResNet50 model was 65 %, micro average AUROC was 0.83, macro average AUROC was 0.82, and micro average AUPRC was 0.71. In the critical blood glucose group, the prediction of AUROC was 0.84, AUPRC was 0.60. In the high blood glucose group, AUROC was 0.87, AUPRC was 0.71.

CONCLUSIONS

Tongue features can improve the prediction accuracy of the diabetes risk prediction model formed by classical machine learning model significantly. In addition to the excellent performance, Stacking model and ResNet50 model which were recommended had non-invasive operation and were easy to use. Stacking model and ResNet50 model had high precision, low false positive rate and low misdiagnosis rate on detecting hyperglycemia. While on detecting blood glucose value in critical state, Stacking model and ResNet50 model had a high sensitivity, a low false negative rate and a low missed diagnosis rate. The study had proved that the differential changes of tongue features reflected the abnormal glucose metabolism, thus the diabetes risk prediction model formed by a combined TCM tongue diagnosis and machine learning technique was feasible.

Life-Course Implications of Pediatric Risk Factors for Cardiovascular Disease

The concept that origins of cardiovascular disease (CVD) begin in childhood is supported by substantial evidence. Prospective studies beginning in childhood report associations of childhood obesity, abnormal blood pressure (BP), dyslipidemia, diabetes, and tobacco use with intermediate CVD markers, including left ventricular hypertrophy and vascular stiffness in young adulthood. Trajectory analyses from longitudinal studies describe discrete BP pathways from childhood to young adult status of hypertension and prehypertension. Among individuals with familial hypercholesterolemia, abnormal low-density lipoprotein cholesterol levels are present in childhood. Some children are at risk for future CVD owing to hereditary factors, psychosocial stress, race, low birth weight, or other nonmodifiable exposures. Behavioural factors, including suboptimal diet, sedentary activity, and tobacco use, in childhood augment risk and can be modified to reduce risk. Pharmacologic treatments are reserved for those at high levels of the BP and cholesterol distributions and for those with diabetes and additional risk factors.

A Journey in Diabetes: From Clinical Physiology to Novel Therapeutics: The 2020 Banting Medal for Scientific Achievement Lecture

Insulin resistance and β-cell dysfunction are the core pathophysiological mechanisms of all hyperglycemic syndromes. Advances in in vivo investigative techniques have made it possible to quantify insulin resistance in multiple sites (skeletal and myocardial muscle, subcutaneous and visceral fat depots, liver, kidney, vascular tissues, brain and intestine), to clarify its consequences for tissue substrate selection, and to establish its relation to tissue perfusion. Physiological modeling of β-cell function has provided a uniform tool to measure β-cell glucose sensitivity and potentiation in response to a variety of secretory stimuli, thereby allowing us to establish feedbacks with insulin resistance, to delineate the biphasic time course of conversion to diabetes, to gauge incretin effects, and to identify primary insulin hypersecretion. As insulin resistance also characterizes several of the comorbidities of diabetes (e.g., obesity, hypertension, dyslipidemia), with shared genetic and acquired influences, the concept is put forward that diabetes is a systemic disease from the outset, actually from the prediabetic stage. In fact, early multifactorial therapy, particularly with newer antihyperglycemic agents, has shown that the burden of micro- and macrovascular complications can be favorably modified despite the rising pressure imposed by protracted obesity.

Nuclear Magnetic Resonance Derived Biomarkers for Evaluating Cardiometabolic Risk in Youth and Young Adults Across the Spectrum of Glucose Tolerance

Youth with obesity have an increased risk for cardiometabolic disease, but identifying those at highest risk remains a challenge. Four biomarkers that might serve this purpose are "by products" of clinical NMR LipoProfile^® lipid testing: LPIR (Lipoprotein Insulin Resistance Index), GlycA (inflammation marker), BCAA (total branched-chain amino acids), and glycine. All are strongly related to insulin resistance and type 2 diabetes (T2DM) in adults (glycine inversely) and are independent of biological and methodological variations in insulin assays. However, their clinical utility in youth is unclear. We compared fasting levels of these biomarkers in 186 youth (42 lean normal glucose tolerant (NGT), 88 obese NGT, 23 with prediabetes (PreDM), and 33 with T2DM. All four biomarkers were associated with obesity and glycemia in youth. LPIR and GlycA were highest in youth with PreDM and T2DM, whereas glycine was lowest in youth with T2DM. While all four were correlated with HOMA-IR (Homeostatic Model Assessment for Insulin Resistance), LPIR had the strongest correlation (LPIR: r = 0.6; GlycA: r = 0.4, glycine: r = -0.4, BCAA: r = 0.2, all P < 0.01). All four markers correlated with HbA1c (LPIR, GlycA, BCAA: r ≥ 0.3 and glycine: r = -0.3, all P < 0.001). In multi-variable regression models, LPIR, GlycA, and glycine were independently associated with HOMA-IR (Adjusted R² = 0.473, P < 0.001) and LPIR, glycine, and BCAA were independently associated with HbA1c (Adjusted R² = 0.33, P < 0.001). An LPIR index of >44 was associated with elevated blood pressure, BMI, and dyslipidemia. Plasma NMR-derived markers were related to adverse markers of cardiometabolic risk in youth. LPIR, either alone or in combination with GlycA, should be explored as a non-insulin dependent predictive tool for development of insulin resistance and diabetes in youth.

CLINICAL TRIAL REGISTRATION

Clinicaltrials.gov, identifier NCT:02960659.

Cross-Sectional and Longitudinal Examination of Insulin Sensitivity and Secretion across Puberty among Non-Hispanic Black and White Children

BACKGROUND

Few studies using criterion measures of insulin sensitivity (SI) and insulin secretory capacity (ISC) have been conducted across puberty to adulthood. We examined how SI and ISC change from pre-puberty through adulthood.

METHODS

Hyperglycemic clamp studies were performed in a convenience sample of non-Hispanic Black (NHB) and White children evaluated at age 6 to 12 years and at approximately 5-year intervals into adulthood (maximum age 27 years). SI and ISC (first-phase and steady-state insulin secretion) were determined cross-sectionally in 133 unique participants across puberty and in adulthood. Additionally, longitudinal changes in SI and ISC were compared at two timepoints among three groups defined by changes in pubertal development: pre-pubertal at baseline and late-pubertal at follow-up (n=27), early-pubertal at baseline and late-pubertal at follow-up (n=27), and late-pubertal at baseline and adult at follow-up (n=24).

RESULTS

Cross-sectionally, SI was highest in pre-puberty and early puberty and lowest in mid-puberty (analysis of covariance [ANCOVA] P=0.001). Longitudinally, SI decreased from pre-puberty to late puberty (P<0.001), then increased somewhat from late puberty to adulthood. Cross-sectionally, first-phase and steady-state ISC increased during puberty and decreased in adulthood (ANCOVA P<0.02). Longitudinally, steady-state and first-phase ISC increased from pre-puberty to late puberty (P<0.007), and steady-state ISC decreased from late puberty to adulthood. The NHB group had lower SI (P=0.003) and greater first-phase and steady-state ISC (P≤0.001), independent of pubertal development.

CONCLUSION

This study confirms that SI decreases and ISC increases transiently during puberty and shows that these changes largely resolve in adulthood.