In this narrative review, we describe the epidemiology (prevalence, incidence, temporal trends, and projections) of type 2 diabetes among children and adolescents (<20 years), focusing on data from the U.S. and reporting global estimates where available. Secondarily, we discuss the clinical course of youth-onset type 2 diabetes, from prediabetes to complications and comorbidities, drawing comparisons with youth type 1 diabetes to highlight the aggressive course of this condition, which, only recently, has become recognized as a pediatric disease by health care providers. Finally, we end with an overview of emerging topics in type 2 diabetes research that have potential to inform strategies for effective preventive action at the community and individual levels.

Objective To identify metabolite patterns associated with childhood obesity, to examine relations of these patterns with measures of adiposity and cardiometabolic risk, and to evaluate associations with maternal peripartum characteristics. Methods Untargeted metabolomic profiling was used to quantify metabolites in plasma of 262 children (6‐10 years). Principal components analysis was used to consolidate 345 metabolites into 18 factors and identified two that differed between obese (BMI ≥ 95‰; n = 84) and lean children (BMI < 85‰; n = 150). The relations of these factors with adiposity (fat mass, BMI, skinfold thicknesses) and cardiometabolic biomarkers (HOMA‐IR, triglycerides, leptin, adiponectin, hsCRP, IL‐6) using multivariable linear regression was then investigated. Finally, the associations of maternal prepregnancy obesity, gestational weight gain, and gestational glucose tolerance with the offspring metabolite patterns was examined. Results A branched‐chain amino acid (BCAA)‐related pattern and an androgen hormone pattern were higher in obese vs. lean children. Both patterns were associated with adiposity and worse cardiometabolic profiles. For example, each increment in the BCAA and androgen pattern scores corresponded with 6% (95% CI: 1, 13%) higher HOMA‐IR. Children of obese mothers had 0.61 (0.13, 1.08) higher BCAA score than their counterparts. Conclusions BCAA and androgen metabolites were associated with adiposity and cardiometabolic risk during mid‐childhood. Maternal obesity may contribute to altered offspring BCAA metabolism.

A goal of many research programmes in biology is to extract meaningful insights from large, complex datasets. Researchers in ecology, evolution and behavior (EEB) often grapple with long-term, observational datasets from which they construct models to test causal hypotheses about biological processes. Similarly, epidemiologists analyse large, complex observational datasets to understand the distribution and determinants of human health. A key difference in the analytical workflows for these two distinct areas of biology is the delineation of data analysis tasks and explicit use of causal directed acyclic graphs (DAGs), widely adopted by epidemiologists. Here, we review the most recent causal inference literature and describe an analytical workflow that has direct applications for EEB. We start this commentary by defining four distinct analytical tasks (description, prediction, association, causal inference). The remainder of the text is dedicated to causal inference, specifically focusing on the use of DAGs to inform the modelling strategy. Given the increasing interest in causal inference and misperceptions regarding this task, we seek to facilitate an exchange of ideas between disciplinary silos and provide an analytical framework that is particularly relevant for making causal inference from observational data.

In recent years, the prevalence of hypertension and prehypertension increased markedly among children and adolescents, highlighting the importance of identifying determinants of elevated blood pressure early in life. Low birth weight and rapid early childhood weight gain are associated with higher future blood pressure. However, few studies have examined the timing of postnatal weight gain in relation to later blood pressure, and little is known regarding the contribution of linear growth. We studied 957 participants in Project Viva, an ongoing US prebirth cohort. We examined the relations of gains in body mass index z-score and length/height z-score during 4 early life age intervals (birth to 6 months, 6 months to 1 year, 1 to 2 years, and 2 to 3 years) with blood pressure during mid-childhood (6–10 years) and evaluated whether these relations differed by birth size. After accounting for confounders, each additional z-score gain in body mass index during birth to 6 months and 2 to 3 years was associated with 0.81 (0.15, 1.46) and 1.61 (0.33, 2.89) mm Hg higher systolic blood pressure, respectively. Length/height gain was unrelated to mid-childhood blood pressure, and there was no evidence of effect modification by birth size for body mass index or length/height z-score gain. Our findings suggest that more rapid gain in body mass index during the first 6 postnatal months and in the preschool years may lead to higher systolic blood pressure in mid-childhood, regardless of size at birth. Strategies to reduce accrual of excess adiposity during early life may reduce mid-childhood blood pressure, which may also impact adult blood pressure and cardiovascular health.

Hypertensive disorders of pregnancy (HDP), defined here as hypertensive disorders with onset in pregnancy (i.e., gestational hypertension, preeclampsia, and preeclampsia superimposed on chronic hypertension), affect up to 10% of pregnancies in the United States and are associated with substantial maternal and neonatal morbidity and mortality. Per- and polyfluoroalkyl substances (PFAS) are associated with adverse cardiometabolic outcomes during pregnancy, but associations between PFAS and HDP are inconsistent and joint effects of PFAS mixtures have not been evaluated. We studied 1,558 pregnant individuals from the Project Viva cohort, recruited during 1999–2002. We quantified concentrations of eight PFAS in plasma samples (median 9.7 weeks of gestation). Using clinical records, we calculated trimester-specific mean systolic (SBP) and diastolic (DBP) blood pressure and categorized HDP status [no HDP (normotensive & chronic hypertension), gestational hypertension, preeclampsia]. We estimated associations of individual PFAS with HDP using multinomial logistic regression and estimated associations with blood pressure using linear regression. We used Bayesian kernel machine regression (BKMR) and quantile g-computation to assess joint effects of the PFAS mixture on HDP and blood pressure measures. Four percent of participants developed preeclampsia and 7% developed gestational hypertension. We observed higher odds of gestational hypertension, but not preeclampsia, per doubling of perfluorooctanoate (PFOA) [OR = 1.51 (95% confidence interval: 1.12, 2.03)], perfluorooctane sulfonate (PFOS) [OR = 1.38 (1.04, 1.82)], and perfluorohexane sulfonate [OR = 1.28 (1.06, 1.54)] concentrations. We observed higher mean DBP per doubling of PFOA [2nd trimester (T2): 0.39 mmHg (−0.01, 0.78); 3rd trimester (T3): 0.56 mmHg (0.14, 0.98)] and PFOS [T2: 0.46 mmHg (0.11, 0.82); T3: 0.43 mmHg (0.05, 0.80)]. The PFAS mixture was positively associated with odds of gestational hypertension [75th vs. 50th percentile: OR = 1.14 (95% credible interval:1.03, 1.25), BKMR] and mean DBP [T2 = 0.17 mmHg (−0.06, 0.40); T3 = 0.22 mmHg (−0.03, 0.48), BKMR]. These findings suggest that exposure to certain PFAS may increase the odds of gestational hypertension during pregnancy, with potential implications for subsequent maternal and child health outcomes.