Spectrum of Phenotypes and Causes of Type 2 Diabetes in Children.

Several factors, including genetics, family history, diet, physical activity, obesity, and insulin resistance in puberty, appear to increase the risk of type 2 diabetes in youth. Youth-onset type 2 diabetes is often thought of as a single entity but rather exists as a spectrum of disease with differences in presentation, metabolic characteristics, clinical progression, and complication rates. We review what is currently known regarding the risks associated with developing type 2 diabetes in youth. Additionally, we focus on the spectrum of phenotypes of pediatric type 2 diabetes, discuss the pathogenic underpinnings and potential therapeutic relevance of this heterogeneity, and compare youth-onset type 2 diabetes with type 1 diabetes and adult-onset type 2 diabetes. Finally, we highlight knowledge gaps in prediction and prevention of youth-onset type 2 diabetes.

Prenatal exposure to per- and polyfluoroalkyl substances and early childhood adiposity and cardiometabolic health in the Healthy Start study.

BACKGROUND/OBJECTIVES: Observational and experimental studies have suggested that prenatal exposure to per- and polyfluoroalkyl substances (PFAS) can increase childhood adiposity and cardiometabolic disruption. However, most previous studies have used weight-based measures that cannot distinguish between fat mass and lean mass. We evaluated associations of prenatal PFAS exposure with precisely measured body composition and cardiometabolic biomarkers in early childhood. SUBJECTS: 373 eligible mother-infant pairs in the Healthy Start longitudinal cohort. METHODS: We used multiple linear regression and Bayesian kernel machine regression models to estimate associations between five PFAS in maternal mid-pregnancy serum, and early childhood adiposity via air displacement plethysmography. Secondary outcomes included body mass index, waist circumference, and fasting serum lipids, glucose, insulin and adipokines. Models were adjusted for potential confounders and effect modification by child sex was evaluated. RESULTS: The median age of children at assessment was 4.6 years. Prenatal concentration of perfluorooctanoate (PFOA) was positively associated with percent fat mass (0.89% per log2-unit increase, 95% CI: 0.15, 1.64), while perfluorononanoate (PFNA) was positively associated with fat mass index and body mass index. Cardiometabolic markers in blood were generally not associated with prenatal PFAS in this population. Mixture models confirmed the importance of PFNA and PFOA in predicting percent fat mass, while PFNA was most important for fat mass index, body mass index, and waist circumference. There were no significant effects of the five PFAS as a mixture, potentially due to opposing effects of different PFAS. CONCLUSIONS: Our results agree with previous studies showing that prenatal serum concentrations of certain PFAS are positively associated with early childhood adiposity. Notably, associations were stronger for measures incorporating precisely measured fat mass compared to measures of body size or weight. Early life increases in adiposity may precede the development of adverse cardiometabolic health outcomes in children exposed to PFAS during gestation.

Diabetes Study of Children of Diverse Ethnicity and Race: Study design.

AIMS: Determining diabetes type in children has become increasingly difficult due to an overlap in typical characteristics between type 1 diabetes (T1D) and type 2 diabetes (T2D). The Diabetes Study in Children of Diverse Ethnicity and Race (DISCOVER) programme is a National Institutes of Health (NIH)-supported multicenter, prospective, observational study that enrols children and adolescents with non-secondary diabetes. The primary aim of the study was to develop improved models to differentiate between T1D and T2D in diverse youth. MATERIALS AND METHODS: The proposed models will evaluate the utility of three existing T1D genetic risk scores in combination with data on islet autoantibodies and other parameters typically available at the time of diabetes onset. Low non-fasting serum C-peptide (<0.6 nmol/L) between 3 and 10 years after diabetes diagnosis will be considered a biomarker for T1D as it reflects the loss of insulin secretion ability. Participating centres are enrolling youth (<19 years old) either with established diabetes (duration 3-10 years) for a cross-sectional evaluation or with recent onset diabetes (duration 3 weeks-15 months) for the longitudinal observation with annual visits for 3 years. Cross-sectional data will be used to develop models. Longitudinal data will be used to externally validate the best-fitting model. RESULTS: The results are expected to improve the ability to classify diabetes type in a large and growing subset of children who have an unclear form of diabetes at diagnosis. CONCLUSIONS: Accurate and timely classification of diabetes type will help establish the correct clinical management early in the course of the disease.

Self-Reported Food Security in Adolescents with Type 1 Diabetes: Association with Hemoglobin A1c and Mental Health Symptoms Independent of Household Food Security.

BACKGROUND: Typically, child exposure to food insecurity is assessed by caregiver reports of household food security. Child report has the potential for greater accuracy because it pertains only to the child whose experiences may differ from caregiver reports. OBJECTIVE: We assessed if adolescent-reported food insecurity was associated with levels of hemoglobin A1c (HbA1c), acute diabetes-related complications, depressive symptoms, and disordered eating behaviors in adolescents with type 1 diabetes, independently from household food security. METHODS: In a cross-sectional analysis of the multicenter SEARCH for Diabetes in Youth Cohort Study (phase 4, 2016-2019) including 601 adolescents aged 10-17 y with type 1 diabetes and their caregivers, household food security, and adolescent-reported food security were assessed using the 18-item Household Food Security Survey Module and the 6-item Child Food Security Assessment questionnaire. Age-stratified (10-13 and 14-17) regression models were performed to estimate independent associations, adjusting for sociodemographics, clinical factors, and household food security. RESULTS: Food insecurity was reported by 13.1% (n = 79) of adolescents and 15.6% (n = 94) of caregivers. Among adolescent-caregiver dyads, 82.5% (n = 496) of reports were concordant and 17.5% (n = 105) discordant, Cohen's κ= 0.3. Adolescent-reported food insecurity was not independently associated with HbA1c, diabetic ketoacidosis, and severe hypoglycemia, including in age-stratified analyses. Adolescent-reported food insecurity was independently associated with elevated odds of depressive symptoms [odds ratio (OR): 3.6; 95% confidence interval (CI): 1.3, 10.3] and disordered eating behaviors (OR: 2.5, 95% CI: 1.4, 4.6) compared with adolescents reporting food security; these associations remained in both age groups for disordered eating behaviors and in the older group for depressive symptoms. CONCLUSIONS: Adolescents with type 1 diabetes may experience food insecurity differently than caregivers. Adolescent-reported food insecurity was independently associated with depressive symptoms and disordered eating behaviors and thus may be an important attribute to assess in addition to household food security in adolescents with type 1 diabetes.

Heterogeneity in glycaemic control in children and adolescents with type 1 diabetes: A latent class trajectory analysis of Danish nationwide data.

AIMS: Suboptimal glycaemic control in children and adolescents with type 1 diabetes is prevalent and associated with increased risk of diabetes-related complications and mortality later in life. First, we aimed to identify distinct glycated haemoglobin (HbA1c) trajectories in children and adolescents (2-19 years) with type 1 diabetes. Second, we examined their associations with clinical and socio-demographic factors. METHODS: Data were obtained from the Danish Registry of Childhood and Adolescent Diabetes (DanDiabKids) comprising all Danish children and adolescents diagnosed with type 1 diabetes from 1996 to 2019. Subgroups of distinct mean trajectories of HbA1c were identified using data-driven latent class trajectory modelling. RESULTS: A total of 5889 children (47% female) had HbA1c measured a median of 6 times (interquartile range 3-8) and contributing to 36,504 measurements. We identified four mean HbA1c trajectories, referred to as 'Stable but elevated HbA1c' (83%), 'Increasing HbA1c' (5%), 'Late HbA1c peak' (7%), and 'Early HbA1c peak' (5%). Compared to the 'Stable but elevated HbA1c' group, the three other groups presented rapidly deteriorating glycaemic control during late childhood or adolescence, had higher HbA1c at study entry, and included fewer pump users, higher frequency of inadequate blood glucose monitoring, more severe hypoglycaemic events, lower proportions with Danish origin, and worse educational status of parents. The groups also represented significant differences by healthcare region. CONCLUSIONS: Children and adolescents with type 1 diabetes experience heterogenous trajectories with different timings and magnitudes of the deterioration of HbA1c levels, although the majority follow on average a stable, yet elevated HbA1c trajectory. The causes and long-term health implications of these heterogenous trajectories need to be addressed.

Airborne Lead Exposure and Childhood Cognition: The Environmental Influences on Child Health Outcomes (ECHO) Cohort (2003-2022).

Objectives. To examine whether a previously reported association between airborne lead exposure and children's cognitive function replicates across a geographically diverse sample of the United States. Methods. Residential addresses of children (< 5 years) were spatially joined to the Risk-Screening Environmental Indicators model of relative airborne lead toxicity. Cognitive outcomes for children younger than 8 years were available for 1629 children with IQ data and 1476 with measures of executive function (EF; inhibitory control, cognitive flexibility). We used generalized linear models using generalized estimating equations to examine the associations of lead, scaled by interquartile range (IQR), accounting for individual- and area-level confounders. Results. An IQR increase in airborne lead was associated with a 0.74-point lower mean IQ score (b = -0.74; 95% confidence interval = -1.00, -0.48). The association between lead and EF was nonlinear and was modeled with a knot at the 97.5th percentile of lead in our sample. Lead was significantly associated with lower mean inhibitory control but not with cognitive flexibility. This effect was stronger among males for both IQ and inhibitory control. Conclusions. Early-life exposure to airborne lead is associated with lower cognitive functioning. (Am J Public Health. 2024;114(3):309-318. https://doi.org/10.2105/AJPH.2023.307519).

Associations of Urinary Biomarkers of Phthalates, Phenols, Parabens, and Organophosphate Esters with Glycemic Traits in Pregnancy: The Healthy Start Study.

BACKGROUND: Certain endocrine-disrupting chemicals (EDCs) are widespread in consumer products and may alter glucose metabolism. However, the impact of EDC exposures on glucose and insulin regulation during pregnancy is incompletely understood, despite potential adverse consequences for maternal and infant health. We estimated associations between 37 urinary biomarkers of EDCs and glucose-insulin traits among pregnant women. METHODS: Seventeen phthalate or phthalate substitute metabolites, six environmental phenols, four parabens, and ten organophosphate ester metabolites were quantified in mid-pregnancy urine from 298 participants in the Healthy Start Study. Fasting blood glucose, insulin, and hemoglobin A1c were assessed concurrently, and Homeostasis Model Assessment 2-Insulin Resistance (HOMA2-IR) was calculated. Gestational diabetes diagnoses and screening results were obtained from medical records for a subset of participants. We estimated associations between each EDC and outcome separately using linear and robust Poisson regression models and analyzed EDC mixture effects. RESULTS: The EDC mixture was positively associated with glucose, insulin, and HOMA2-IR, although overall associations were attenuated after adjustment for maternal BMI. Two mixture approaches identified di(2-ethylhexyl) phthalate (DEHP) metabolites as top contributors to the mixture's positive associations. In single-pollutant models, DEHP metabolites were positively associated with fasting glucose, fasting insulin, and HOMA2-IR even after adjustment for maternal BMI. For example, each interquartile range increase in log2-transformed mono(2-ethyl-5-oxohexyl) phthalate was associated with 2.4 mg/dL (95% confidence interval (CI): 1.1, 3.6) higher fasting glucose, 11.8% (95%CI: 3.6, 20.5) higher fasting insulin, and 12.3% (95%CI: 4.2, 21.1) higher HOMA2-IR. Few EDCs were associated with hemoglobin A1c or with a combined outcome of impaired glucose tolerance or gestational diabetes. DISCUSSION: Exposures to phthalates and particularly DEHP during pregnancy are associated with altered glucose-insulin regulation. Disruptions in maternal glucose metabolism during pregnancy may contribute to adverse pregnancy outcomes including gestational diabetes and fetal macrosomia, and associated long-term consequences for maternal and child health.

Independent and joint effects of neighborhood-level environmental and socioeconomic exposures on body mass index in early childhood: The environmental influences on child health outcomes (ECHO) cohort.

Past studies support the hypothesis that the prenatal period influences childhood growth. However, few studies explore the joint effects of exposures that occur simultaneously during pregnancy. To explore the feasibility of using mixtures methods with neighborhood-level environmental exposures, we assessed the effects of multiple prenatal exposures on body mass index (BMI) from birth to age 24 months. We used data from two cohorts: Healthy Start (n = 977) and Maternal and Developmental Risks from Environmental and Social Stressors (MADRES; n = 303). BMI was measured at delivery and 6, 12, and 24 months and standardized as z-scores. We included variables for air pollutants, built and natural environments, food access, and neighborhood socioeconomic status (SES). We used two complementary statistical approaches: single-exposure linear regression and quantile-based g-computation. Models were fit separately for each cohort and time point and were adjusted for relevant covariates. Single-exposure models identified negative associations between NO2 and distance to parks and positive associations between low neighborhood SES and BMI z-scores for Healthy Start participants; for MADRES participants, we observed negative associations between O3 and distance to parks and BMI z-scores. G-computations models produced comparable results for each cohort: higher exposures were generally associated with lower BMI, although results were not significant. Results from the g-computation models, which do not require a priori knowledge of the direction of associations, indicated that the direction of associations between mixture components and BMI varied by cohort and time point. Our study highlights challenges in assessing mixtures effects at the neighborhood level and in harmonizing exposure data across cohorts. For example, geospatial data of neighborhood-level exposures may not fully capture the qualities that might influence health behavior. Studies aiming to harmonize geospatial data from different geographical regions should consider contextual factors when operationalizing exposure variables.

Demographic and health characteristics associated with fish and n-3 fatty acid supplement intake during pregnancy: results from pregnancy cohorts in the ECHO programme.

OBJECTIVE: n-3 fatty acid consumption during pregnancy is recommended for optimal pregnancy outcomes and offspring health. We examined characteristics associated with self-reported fish or n-3 supplement intake. DESIGN: Pooled pregnancy cohort studies. SETTING: Cohorts participating in the Environmental influences on Child Health Outcomes (ECHO) consortium with births from 1999 to 2020. PARTICIPANTS: A total of 10 800 pregnant women in twenty-three cohorts with food frequency data on fish consumption; 12 646 from thirty-five cohorts with information on supplement use. RESULTS: Overall, 24·6 % reported consuming fish never or less than once per month, 40·1 % less than once a week, 22·1 % 1-2 times per week and 13·2 % more than twice per week. The relative risk (RR) of ever (v. never) consuming fish was higher in participants who were older (1·14, 95 % CI 1·10, 1·18 for 35-40 v. <29 years), were other than non-Hispanic White (1·13, 95 % CI 1·08, 1·18 for non-Hispanic Black; 1·05, 95 % CI 1·01, 1·10 for non-Hispanic Asian; 1·06, 95 % CI 1·02, 1·10 for Hispanic) or used tobacco (1·04, 95 % CI 1·01, 1·08). The RR was lower in those with overweight v. healthy weight (0·97, 95 % CI 0·95, 1·0). Only 16·2 % reported n-3 supplement use, which was more common among individuals with a higher age and education, a lower BMI, and fish consumption (RR 1·5, 95 % CI 1·23, 1·82 for twice-weekly v. never). CONCLUSIONS: One-quarter of participants in this large nationwide dataset rarely or never consumed fish during pregnancy, and n-3 supplement use was uncommon, even among those who did not consume fish.

Incidence rates of childhood asthma with recurrent exacerbations in the US Environmental influences on Child Health Outcomes (ECHO) program.

BACKGROUND: Descriptive epidemiological data on incidence rates (IRs) of asthma with recurrent exacerbations (ARE) are sparse. OBJECTIVES: This study hypothesized that IRs for ARE would vary by time, geography, age, and race and ethnicity, irrespective of parental asthma history. METHODS: The investigators leveraged data from 17,246 children born after 1990 enrolled in 59 US with 1 Puerto Rican cohort in the Environmental Influences on Child Health Outcomes (ECHO) consortium to estimate IRs for ARE. RESULTS: The overall crude IR for ARE was 6.07 per 1000 person-years (95% CI: 5.63-6.51) and was highest for children aged 2-4 years, for Hispanic Black and non-Hispanic Black children, and for those with a parental history of asthma. ARE IRs were higher for 2- to 4-year-olds in each race and ethnicity category and for both sexes. Multivariable analysis confirmed higher adjusted ARE IRs (aIRRs) for children born 2000-2009 compared with those born 1990-1999 and 2010-2017, 2-4 versus 10-19 years old (aIRR = 15.36; 95% CI: 12.09-19.52), and for males versus females (aIRR = 1.34; 95% CI 1.16-1.55). Black children (non-Hispanic and Hispanic) had higher rates than non-Hispanic White children (aIRR = 2.51; 95% CI 2.10-2.99; and aIRR = 2.04; 95% CI: 1.22-3.39, respectively). Children born in the Midwest, Northeast and South had higher rates than those born in the West (P < .01 for each comparison). Children with a parental history of asthma had rates nearly 3 times higher than those without such history (aIRR = 2.90; 95% CI: 2.43-3.46). CONCLUSIONS: Factors associated with time, geography, age, race and ethnicity, sex, and parental history appear to influence the inception of ARE among children and adolescents.

Maternal Serum Metabolomics in Mid-Pregnancy Identifies Lipid Pathways as a Key Link to Offspring Obesity in Early Childhood.

Maternal metabolism during pregnancy shapes offspring health via in utero programming. In the Healthy Start study, we identified five subgroups of pregnant women based on conventional metabolic biomarkers: Reference (n = 360); High HDL-C (n = 289); Dyslipidemic-High TG (n = 149); Dyslipidemic-High FFA (n = 180); Insulin Resistant (IR)-Hyperglycemic (n = 87). These subgroups not only captured metabolic heterogeneity among pregnant participants but were also associated with offspring obesity in early childhood, even among women without obesity or diabetes. Here, we utilize metabolomics data to enrich characterization of the metabolic subgroups and identify key compounds driving between-group differences. We analyzed fasting blood samples from 1065 pregnant women at 18 gestational weeks using untargeted metabolomics. We used weighted gene correlation network analysis (WGCNA) to derive a global network based on the Reference subgroup and characterized distinct metabolite modules representative of the different metabolomic profiles. We used the mummichog algorithm for pathway enrichment and identified key compounds that differed across the subgroups. Eight metabolite modules representing pathways such as the carnitine-acylcarnitine translocase system, fatty acid biosynthesis and activation, and glycerophospholipid metabolism were identified. A module that included 189 compounds related to DHA peroxidation, oxidative stress, and sex hormone biosynthesis was elevated in the Insulin Resistant-Hyperglycemic vs. the Reference subgroup. This module was positively correlated with total cholesterol (R:0.10; p-value < 0.0001) and free fatty acids (R:0.07; p-value < 0.05). Oxidative stress and inflammatory pathways may underlie insulin resistance during pregnancy, even below clinical diabetes thresholds. These findings highlight potential therapeutic targets and strategies for pregnancy risk stratification and reveal mechanisms underlying the developmental origins of metabolic disease risk.

The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes.

AIMS/HYPOTHESIS: The Latino population has been systematically underrepresented in large-scale genetic analyses, and previous studies have relied on the imputation of ungenotyped variants based on the 1000 Genomes (1000G) imputation panel, which results in suboptimal capture of low-frequency or Latino-enriched variants. The National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) released the largest multi-ancestry genotype reference panel representing a unique opportunity to analyse rare genetic variations in the Latino population. We hypothesise that a more comprehensive analysis of low/rare variation using the TOPMed panel would improve our knowledge of the genetics of type 2 diabetes in the Latino population. METHODS: We evaluated the TOPMed imputation performance using genotyping array and whole-exome sequence data in six Latino cohorts. To evaluate the ability of TOPMed imputation to increase the number of identified loci, we performed a Latino type 2 diabetes genome-wide association study (GWAS) meta-analysis in 8150 individuals with type 2 diabetes and 10,735 control individuals and replicated the results in six additional cohorts including whole-genome sequence data from the All of Us cohort. RESULTS: Compared with imputation with 1000G, the TOPMed panel improved the identification of rare and low-frequency variants. We identified 26 genome-wide significant signals including a novel variant (minor allele frequency 1.7%; OR 1.37, p=3.4 × 10-9). A Latino-tailored polygenic score constructed from our data and GWAS data from East Asian and European populations improved the prediction accuracy in a Latino target dataset, explaining up to 7.6% of the type 2 diabetes risk variance. CONCLUSIONS/INTERPRETATION: Our results demonstrate the utility of TOPMed imputation for identifying low-frequency variants in understudied populations, leading to the discovery of novel disease associations and the improvement of polygenic scores. DATA AVAILABILITY: Full summary statistics are available through the Common Metabolic Diseases Knowledge Portal ( https://t2d.hugeamp.org/downloads.html ) and through the GWAS catalog ( https://www.ebi.ac.uk/gwas/ , accession ID: GCST90255648). Polygenic score (PS) weights for each ancestry are available via the PGS catalog ( https://www.pgscatalog.org , publication ID: PGP000445, scores IDs: PGS003443, PGS003444 and PGS003445).

Effects of Long-term Metformin and Lifestyle Interventions on Cardiovascular Events in the Diabetes Prevention Program and Its Outcome Study.

BACKGROUND: Lifestyle intervention and metformin have been shown to prevent diabetes; however, their efficacy in preventing cardiovascular disease associated with the development of diabetes is unclear. We examined whether these interventions reduced the incidence of major cardiovascular events over a 21-year median follow-up of participants in the DPP trial (Diabetes Prevention Program) and DPPOS (Diabetes Prevention Program Outcomes Study). METHODS: During DPP, 3234 participants with impaired glucose tolerance were randomly assigned to metformin 850 mg twice daily, intensive lifestyle or placebo, and followed for 3 years. During the next 18-year average follow-up in DPPOS, all participants were offered a less intensive group lifestyle intervention, and unmasked metformin was continued in the metformin group. The primary outcome was the first occurrence of nonfatal myocardial infarction, stroke, or cardiovascular death adjudicated by standard criteria. An extended cardiovascular outcome included the primary outcome or hospitalization for heart failure or unstable angina, coronary or peripheral revascularization, coronary heart disease diagnosed by angiography, or silent myocardial infarction by ECG. ECGs and cardiovascular risk factors were measured annually. RESULTS: Neither metformin nor lifestyle intervention reduced the primary outcome: metformin versus placebo hazard ratio 1.03 (95% CI, 0.78-1.37; P = 0.81) and lifestyle versus placebo hazard ratio 1.14 (95% CI, 0.87-1.50; P = 0.34). Risk factor adjustment did not change these results. No effect of either intervention was seen on the extended cardiovascular outcome. CONCLUSIONS: Neither metformin nor lifestyle reduced major cardiovascular events in DPPOS over 21 years despite long-term prevention of diabetes. Provision of group lifestyle intervention to all, extensive out-of-study use of statin and antihypertensive agents, and reduction in the use of study metformin together with out-of-study metformin use over time may have diluted the effects of the interventions. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifiers: DPP (NCT00004992) and DPPOS (NCT00038727).

The Environmental Influences on Child Health Outcomes (ECHO)-Wide Cohort.

The Environmental Influences on Child Health Outcomes (ECHO)-Wide Cohort Study (EWC), a collaborative research design comprising 69 cohorts in 31 consortia, was funded by the National Institutes of Health (NIH) in 2016 to improve children's health in the United States. The EWC harmonizes extant data and collects new data using a standardized protocol, the ECHO-Wide Cohort Data Collection Protocol (EWCP). EWCP visits occur at least once per life stage, but the frequency and timing of the visits vary across cohorts. As of March 4, 2022, the EWC cohorts contributed data from 60,553 children and consented 29,622 children for new EWCP data and biospecimen collection. The median (interquartile range) age of EWCP-enrolled children was 7.5 years (3.7-11.1). Surveys, interviews, standardized examinations, laboratory analyses, and medical record abstraction are used to obtain information in 5 main outcome areas: pre-, peri-, and postnatal outcomes; neurodevelopment; obesity; airways; and positive health. Exposures include factors at the level of place (e.g., air pollution, neighborhood socioeconomic status), family (e.g., parental mental health), and individuals (e.g., diet, genomics).

Maternal Diet Quality During Pregnancy and Offspring Hepatic Fat in Early Childhood: The Healthy Start Study.

BACKGROUND: Overnutrition in utero may increase offspring risk of nonalcoholic fatty liver disease (NAFLD), but the specific contribution of maternal diet quality during pregnancy to this association remains understudied in humans. OBJECTIVES: This study aimed to examine the associations of maternal diet quality during pregnancy with offspring hepatic fat in early childhood (median: 5 y old, range: 4-8 y old). METHODS: Data were from 278 mother-child pairs in the longitudinal, Colorado-based Healthy Start Study. Multiple 24-h recalls were collected from mothers during pregnancy on a monthly basis (median: 3 recalls, range: 1-8 recalls starting after enrollment), and used to estimate maternal usual nutrient intakes and dietary pattern scores [Healthy Eating Index-2010 (HEI-2010), Dietary Inflammatory Index (DII), and Relative Mediterranean Diet Score (rMED)]. Offspring hepatic fat was measured in early childhood by MRI. Associations of maternal dietary predictors during pregnancy with offspring log-transformed hepatic fat were assessed using linear regression models adjusted for offspring demographics, maternal/perinatal confounders, and maternal total energy intake. RESULTS: Higher maternal fiber intake and rMED scores during pregnancy were associated with lower offspring hepatic fat in early childhood in fully adjusted models [Back-transformed ß (95% CI): 0.82 (0.72, 0.94) per 5 g/1000 kcal fiber; 0.93 (0.88, 0.99) per 1 SD for rMED]. In contrast, higher maternal total sugar and added sugar intakes, and DII scores were associated with higher offspring hepatic fat [Back-transformed ß (95% CI): 1.18 (1.05, 1.32) per 5% kcal/d added sugar; 1.08 (0.99, 1.18) per 1 SD for DII]. Analyses of dietary pattern subcomponents also revealed that lower maternal intakes of green vegetables and legumes and higher intake of "empty calories" were associated with higher offspring hepatic fat in early childhood. CONCLUSIONS: Poorer maternal diet quality during pregnancy was associated with greater offspring susceptibility to hepatic fat in early childhood. Our findings provide insights into potential perinatal targets for the primordial prevention of pediatric NAFLD.

Identifying Foods That Optimize Intake of Key Micronutrients During Pregnancy.

BACKGROUND: Most pregnant women in the United States are at risk of inadequate intake of vitamin A, vitamin D, folic acid, calcium, iron, and omega-3 fatty acids from foods alone. Very few United States dietary supplements provide sufficient doses of all 6 nutrients without inducing excess intake. OBJECTIVE: We aimed to identify energy-efficient foods that provide sufficient doses of these nutrients and could be consumed in lieu of dietary supplements to achieve the recommended intake in pregnancy. METHODS: In a previous analysis of 2,450 pregnant women, we calculated the range of additional intake needed to shift 90% of participants to intake above the estimated average requirement and keep 90% below the tolerable upper level for these 6 nutrients. Here, we identified foods and beverages from the 2019 to 2020 Food and Nutrient Database for Dietary Studies that provide target levels of these nutrients without exceeding the additional energy intake recommended for pregnancy beginning in the second trimester (340 kilocalories). RESULTS: We identified 2358 candidate foods meeting the target intake range for at least one nutrient. No candidate foods provided target amounts of all 6 nutrients. Seaweed (raw or cooked without fat) provided sufficient vitamin A, folate, calcium, iron, and omega-3s (5 of 6 nutrients) but would require an intake of >5 cups/d. Twenty-one other foods/beverages (mainly fish, vegetables, and beverages) provided target amounts of 4 of the 6 nutrients. Few foods met targets for vitamin D (n = 54) or iron (n = 93). CONCLUSIONS: Results highlight the difficulty in meeting nutritional requirements from diet alone and imply that dietary supplements are likely necessary to meet vitamin D and iron targets in pregnancy, as well as omega-3 fatty acid targets for individuals who do not consume fish products. Other foods could be added in limited amounts to help meet intake targets without exceeding caloric recommendations or nutrient safety limits.

Impact of sedentary behavior and emotional support on prenatal psychological distress and birth outcomes during the COVID-19 pandemic.

Abstract. BACKGROUND: Studies have reported mixed findings regarding the impact of the coronavirus disease 2019 (COVID-19) pandemic on pregnant women and birth outcomes. This study used a quasi-experimental design to account for potential confounding by sociodemographic characteristics. METHODS: Data were drawn from 16 prenatal cohorts participating in the Environmental influences on Child Health Outcomes (ECHO) program. Women exposed to the pandemic (delivered between 12 March 2020 and 30 May 2021) (n = 501) were propensity-score matched on maternal age, race and ethnicity, and child assigned sex at birth with 501 women who delivered before 11 March 2020. Participants reported on perceived stress, depressive symptoms, sedentary behavior, and emotional support during pregnancy. Infant gestational age (GA) at birth and birthweight were gathered from medical record abstraction or maternal report. RESULTS: After adjusting for propensity matching and covariates (maternal education, public assistance, employment status, prepregnancy body mass index), results showed a small effect of pandemic exposure on shorter GA at birth, but no effect on birthweight adjusted for GA. Women who were pregnant during the pandemic reported higher levels of prenatal stress and depressive symptoms, but neither mediated the association between pandemic exposure and GA. Sedentary behavior and emotional support were each associated with prenatal stress and depressive symptoms in opposite directions, but no moderation effects were revealed. CONCLUSIONS: There was no strong evidence for an association between pandemic exposure and adverse birth outcomes. Furthermore, results highlight the importance of reducing maternal sedentary behavior and encouraging emotional support for optimizing maternal health regardless of pandemic conditions.

Impact of the COVID-19 pandemic on children's sleep habits: an ECHO study.

BACKGROUND: Sleep in childhood is affected by behavioral, environmental, and parental factors. We propose that these factors were altered during the COVID-19 pandemic. This study investigates sleep habit changes during the pandemic in 528 children 4-12 years old in the US, leveraging data from the Environmental Influences on Child Health Outcomes (ECHO) Program. METHODS: Data collection occurred in July 2019-March 2020 (pre-pandemic) and two pandemic periods: December 2020-April 2021 and May-August 2021. Qualitative interviews were performed in 38 participants. RESULTS: We found no changes in sleep duration, but a shift to later sleep midpoint during the pandemic periods. There was an increase in latency at the first pandemic collection period but no increase in the frequency of bedtime resistance, and a reduced frequency of naps during the pandemic. Qualitative interviews revealed that parents prioritized routines to maintain sleep duration but were more flexible regarding timing. Children from racial/ethnic minoritized communities slept less at night, had later sleep midpoint, and napped more frequently across all collection periods, warranting in-depth investigation to examine and address root causes. CONCLUSIONS: The COVID-19 pandemic significantly impacted children sleep, but parental knowledge of the importance of sleep might have played a significant protective role. IMPACT: During the COVID-19 pandemic, US children changed their sleep habits, going to bed and waking up later, but their sleep duration did not change. Sleep latency was longer. Parental knowledge of sleep importance might have played a protective role. Regardless of data collection periods, children from racial/ethnic minoritized communities slept less and went to bed later. This is one of the first study on this topic in the US, including prospective pre-pandemic qualitative and quantitative data on sleep habits. Our findings highlight the pandemic long-term impact on childhood sleep. Results warrants further investigations on implications for overall childhood health.

Power and sample size analysis for longitudinal mixed models of health in populations exposed to environmental contaminants: a tutorial.

BACKGROUND: When evaluating the impact of environmental exposures on human health, study designs often include a series of repeated measurements. The goal is to determine whether populations have different trajectories of the environmental exposure over time. Power analyses for longitudinal mixed models require multiple inputs, including clinically significant differences, standard deviations, and correlations of measurements. Further, methods for power analyses of longitudinal mixed models are complex and often challenging for the non-statistician. We discuss methods for extracting clinically relevant inputs from literature, and explain how to conduct a power analysis that appropriately accounts for longitudinal repeated measures. Finally, we provide careful recommendations for describing complex power analyses in a concise and clear manner. METHODS: For longitudinal studies of health outcomes from environmental exposures, we show how to [1] conduct a power analysis that aligns with the planned mixed model data analysis, [2] gather the inputs required for the power analysis, and [3] conduct repeated measures power analysis with a highly-cited, validated, free, point-and-click, web-based, open source software platform which was developed specifically for scientists. RESULTS: As an example, we describe the power analysis for a proposed study of repeated measures of per- and polyfluoroalkyl substances (PFAS) in human blood. We show how to align data analysis and power analysis plan to account for within-participant correlation across repeated measures. We illustrate how to perform a literature review to find inputs for the power analysis. We emphasize the need to examine the sensitivity of the power values by considering standard deviations and differences in means that are smaller and larger than the speculated, literature-based values. Finally, we provide an example power calculation and a summary checklist for describing power and sample size analysis. CONCLUSIONS: This paper provides a detailed roadmap for conducting and describing power analyses for longitudinal studies of environmental exposures. It provides a template and checklist for those seeking to write power analyses for grant applications.

Estimating incidence of type 1 and type 2 diabetes using prevalence data: the SEARCH for Diabetes in Youth study.

BACKGROUND: Incidence is one of the most important epidemiologic indices in surveillance. However, determining incidence is complex and requires time-consuming cohort studies or registries with date of diagnosis. Estimating incidence from prevalence using mathematical relationships may facilitate surveillance efforts. The aim of this study was to examine whether a partial differential equation (PDE) can be used to estimate diabetes incidence from prevalence in youth. METHODS: We used age-, sex-, and race/ethnicity-specific estimates of prevalence in 2001 and 2009 as reported in the SEARCH for Diabetes in Youth study. Using these data, a PDE was applied to estimate the average incidence rates of type 1 and type 2 diabetes for the period between 2001 and 2009. Estimates were compared to annual incidence rates observed in SEARCH. Precision of the estimates was evaluated using 95% bootstrap confidence intervals. RESULTS: Despite the long period between prevalence measures, the estimated average incidence rates mirror the average of the observed annual incidence rates. Absolute values of the age-standardized sex- and type-specific mean relative errors are below 8%. CONCLUSIONS: Incidence of diabetes can be accurately estimated from prevalence. Since only cross-sectional prevalence data is required, employing this methodology in future studies may result in considerable cost savings.