Adolescent growth and social development shape the early development of offspring from preconception through to the post-partum period through distinct processes in males and females. At a time of great change in the forces shaping adolescence, including the timing of parenthood, investments in today's adolescents, the largest cohort in human history, will yield great dividends for future generations.

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Adolescence and the next generation

Gestational diabetes mellitus (GDM) poses increased risk of short- and long-term complications for mother and offspring1–4. GDM is typically diagnosed at 24–28 weeks of gestation, but earlier detection is desirable as this may prevent or considerably reduce the risk of adverse pregnancy outcomes5,6. Here we used a machine-learning approach to predict GDM on retrospective data of 588,622 pregnancies in Israel for which comprehensive electronic health records were available. Our models predict GDM with high accuracy even at pregnancy initiation (area under the receiver operating curve (auROC) = 0.85), substantially outperforming a baseline risk score (auROC = 0.68). We validated our results on both a future validation set and a geographical validation set from the most populated city in Israel, Jerusalem, thereby emulating real-world performance. Interrogating our model, we uncovered previously unreported risk factors, including results of previous pregnancy glucose challenge tests. Finally, we devised a simpler model based on just nine questions that a patient could answer, with only a modest reduction in accuracy (auROC = 0.80). Overall, our models may allow early-stage intervention in high-risk women, as well as a cost-effective screening approach that could avoid the need for glucose tolerance tests by identifying low-risk women. Future prospective studies and studies on additional populations are needed to assess the real-world clinical utility of the model. Leveraging the availability of nationwide electronic health records from over 500,000 pregnancies in Israel, a machine-learning approach offers an alternative means of predicting gestational diabetes at high accuracy in the early stages of pregnancy.

Prediction of gestational diabetes based on nationwide electronic health records.

Insulin resistance changes over time during pregnancy, and in the last half of the pregnancy, insulin resistance increases considerably and can become severe, especially in women with gestational diabetes and type 2 diabetes. Numerous factors such as placental hormones, obesity, inactivity, an unhealthy diet, and genetic and epigenetic contributions influence insulin resistance in pregnancy, but the causal mechanisms are complex and still not completely elucidated. In this review, we strive to give an overview of the many components that have been ascribed to contribute to the insulin resistance in pregnancy. Knowledge about the causes and consequences of insulin resistance is of extreme importance in order to establish the best possible treatment during pregnancy as severe insulin resistance can result in metabolic dysfunction in both mother and offspring on a short as well as long-term basis.

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Determinants of Maternal Insulin Resistance during Pregnancy: An Updated Overview.

There has been a rapid escalation of type 2 diabetes (T2D) in developing countries, with varied prevalence according to rural vs urban habitat and degree of urbanization. Some ethnic groups (eg, South Asians, other Asians, and Africans), develop diabetes a decade earlier and at a lower body mass index than Whites, have prominent abdominal obesity, and accelerated the conversion from prediabetes to diabetes. The burden of complications, both macro- and microvascular, is substantial, but also varies according to populations. The syndemics of diabetes with HIV or tuberculosis are prevalent in many developing countries and predispose to each other. Screening for diabetes in large populations living in diverse habitats may not be cost-effective, but targeted high-risk screening may have a place. The cost of diagnostic tests and scarcity of health manpower pose substantial hurdles in the diagnosis and monitoring of patients. Efforts for prevention remain rudimentary in most developing countries. The quality of care is largely poor; hence, a substantial number of patients do not achieve treatment goals. This is further amplified by a delay in seeking treatment, "fatalistic attitudes", high cost and non-availability of drugs and insulins. To counter these numerous challenges, a renewed political commitment and mandate for health promotion and disease prevention are urgently needed. Several low-cost innovative approaches have been trialed with encouraging outcomes, including training and deployment of non-medical allied health professionals and the use of mobile phones and telemedicine to deliver simple health messages for the prevention and management of T2D.

Diabetes in developing countries

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

2. Classification and Diagnosis of Diabetes: Standards of Care in Diabetes-2023.

A randomized clinical trial of exercise during pregnancy to prevent gestational diabetes mellitus and improve pregnancy outcome in overweight and obese pregnant women

Background
This study aimed to investigate the association between maternal insulin resistance (IR) in the late second trimester and pregnancy outcomes, as well as to identify risk factors of IR among women with gestational diabetes mellitus (GDM).

Methods
A retrospective study was conducted among 2647 women diagnosed with GDM. IR was evaluated using the homeostasis model assessment method for IR (HOMA-IR) in the late second trimester (between 24 and 28 weeks), and the lipid profiles were measured at the same time. Patients were divided into groups based on quartiles of HOMA-IR. The information on pregnancy outcomes and risk factors was extracted from the medical records of all participants and entered electronically. Logistic regression models were used to analyze the associations between HOMA-IR and pregnancy outcomes, as well as the associations between risk factors and HOMA-IR.

Results
Greater IR was associated with cesarean delivery, preterm delivery, macrosomia, and large for gestational age newborns, but only significantly associated with preterm delivery after adjustment for potential confounders (P < .001). Prepregnancy body mass index (BMI), weight gain before diagnosis of GDM, and triglycerides were significantly related with IR in the late second trimester (P < .001). Besides, the total area under the curve of the diagnostic 75-g oral glucose tolerance test and glycosylated hemoglobin A1c increased from the lowest to the highest HOMA-IR groups.

Conclusions
Increasing IR in the late second trimester predicts adverse pregnancy outcomes especially for preterm delivery in women with GDM. Additionally, prepregnancy BMI and weight gain before diagnosis of GDM are independent risk factors for the development of IR.

Increasing insulin resistance predicts adverse pregnancy outcomes in women with gestational diabetes mellitus

Background To estimate the progression rates to type 2 diabetes mellitus (T2DM) in women with gestational diabetes mellitus (GDM) diagnosed by the International Association of Diabetes and Pregnancy Study Group (IADPSG) criteria. Methods Systematic review and meta-analysis were conducted by searching Medline, Embase, and Cochrane between January 1, 2010 and December 31, 2021 for observational studies investigating progression to T2DM after GDM. Inclusion criteria were IADPSG-diagnosed GDM, studies with both GDM and controls, postpartum follow-up duration at least one year. Data were pooled by random effects meta-analysis models. Heterogeneity was assessed by I2 statistic. The pooled relative risk for incidence of T2DM and pre-diabetes between GDM participants and controls were estimated. Reasons for heterogeneity among studies were investigated by prespecified subgroup and meta-regression analysis. Publication bias was assessed by the Begg’s and Egger’s tests. Results This meta-analysis of six studies assessed a total of 61932 individuals (21978 women with GDM and 39954 controls). Women with IADPSG-diagnosed GDM were 6.43 times (RR=6.43, 95% CI:3.45-11.96) more likely to develop T2DM in the future compared with controls. For GDM women, the cumulative incidence of T2DM was 12.1% (95% CI: 6.9%-17.3%), while the pooled cumulative incidence of T2DM was estimated to be 8% (95% CI: 5-11%) in studies with 1 to 5 years of follow-up and increased to 19% (95% CI: 3-34%) for studies with more than 5 years of follow-up. Women with IADPSG-diagnosed GDM had 3.69 times (RR=3.69, 95% CI:2.70-5.06) higher risk of developing pre-diabetes (including impaired fasting glucose and/or impaired glucose tolerance) than controls. Meta-regression analysis showed that the study effect size was not significantly associated with study design, race, length of follow-up, and maternal age (P>0.05). Overall, the studies had a relatively low risk of bias. Conclusions Women with IADPSG-diagnosed GDM have higher risk of developing T2DM and pre-diabetes. The risk of T2DM in GDM women are higher with longer follow-up duration. Our results highlight the importance of promoting postpartum screening and keeping health lifestyle as well as pharmacological interventions to delay/prevent the onset of T2DM/pre-diabetes in GDM women. Systematic review registration https://www.crd.york.ac.uk/prospero, identifier (CRD42022314776)

Yiying Sun

Papers

A randomized clinical trial of exercise during pregnancy to prevent gestational diabetes mellitus and improve pregnancy outcome in overweight and obese pregnant women

Increasing insulin resistance predicts adverse pregnancy outcomes in women with gestational diabetes mellitus

Progression to type 2 diabetes mellitus after gestational diabetes mellitus diagnosed by IADPSG criteria: Systematic review and meta-analysis