Using Power Analysis to Choose the Unit of Randomization, Outcome, and Approach for Subgroup Analysis for a Multilevel Randomized Controlled Clinical Trial to Reduce Disparities in Cardiovascular Health.

We give examples of three features in the design of randomized controlled clinical trials which can increase power and thus decrease sample size and costs. We consider an example multilevel trial with several levels of clustering. For a fixed number of independent sampling units, we show that power can vary widely with the choice of the level of randomization. We demonstrate that power and interpretability can improve by testing a multivariate outcome rather than an unweighted composite outcome. Finally, we show that using a pooled analytic approach, which analyzes data for all subgroups in a single model, improves power for testing the intervention effect compared to a stratified analysis, which analyzes data for each subgroup in a separate model. The power results are computed for a proposed prevention research study. The trial plans to randomize adults to either telehealth (intervention) or in-person treatment (control) to reduce cardiovascular risk factors. The trial outcomes will be measures of the Essential Eight, a set of scores for cardiovascular health developed by the American Heart Association which can be combined into a single composite score. The proposed trial is a multilevel study, with outcomes measured on participants, participants treated by the same provider, providers nested within clinics, and clinics nested within hospitals. Investigators suspect that the intervention effect will be greater in rural participants, who live farther from clinics than urban participants. The results use published, exact analytic methods for power calculations with continuous outcomes. We provide example code for power analyses using validated software.

Household food insecurity and associations with hemoglobin A1c and acute diabetes-related complications in youth and young adults with type 1 diabetes: The SEARCH for Diabetes in Youth study.

AIMS: To examine, among youth and young adults (YYA) with type 1 diabetes (T1D), the association of household food insecurity (HFI) with: 1) HbA1c and 2) episodes of diabetic ketoacidosis (DKA) and severe hypoglycemia. METHODS: HFI was assessed using the U.S. Household Food Security Survey Module in SEARCH for Diabetes in Youth participants with T1D between 2016 and 2019. Linear and logistic regression models adjusted for age, diabetes duration, sex, race, ethnicity, clinic site, parent/participant education, household income, health insurance, and diabetes technology use. RESULTS: Of 1830 participants (mean age 20.8 ± 5.0 years, 70.0 % non-Hispanic White), HbA1c was collected for 1060 individuals (mean HbA1c 9.2 % ± 2.0 %). The prevalence of HFI was 16.4 %. In the past 12 months, 18.2 % and 9.9 % reported an episode of DKA or severe hypoglycemia, respectively. Compared to participants who were food secure, HFI was associated with a 0.33 % (95 % CI 0.003, 0.657) higher HbA1c level. Those with HFI had 1.58 (95 % CI 1.13, 2.21) times the adjusted odds of an episode of DKA and 1.53 (95 % CI 0.99, 2.37) times the adjusted odds of an episode of severe hypoglycemia as those without HFI. CONCLUSIONS: HFI is associated with higher HbA1c levels and increased odds of DKA in YYA with T1D.

Properties of the Household Food Security Survey Module Scale in Young Adults with Diabetes.

BACKGROUND: The Household Food Security Survey Module (HFSSM) was not tailored to people with chronic diseases or young adults (YAs). OBJECTIVES: We aim to evaluate whether the 18-item HFSSM meets assumptions underlying the scale among YAs with diabetes. METHODS: Data from 1887 YAs with youth-onset type 1 diabetes or type 2 diabetes were used from the SEARCH for Diabetes in Youth Study, 2016-2019, and on 925 who returned for the SEARCH Food Security Cohort Study, 2018-2021, all of whom had completed the HFSSM. Guttman scaling properties (affirmation of preceding less severe items) and Rasch model properties (probability to answer an item based on difficulty level) were assessed. RESULTS: Items 3 (balanced meals) and 6 (eating less than one should) were affirmed more frequently than expected (nonmonotonic response pattern). At 1.2%-3.5%, item nonresponse was rare among type 1 diabetes but higher among type 2 diabetes (range: 3.1%-10.6%). Items 9 (not eating the whole day) and 3 did not meet the Guttman scaling properties. Rasch modeling revealed that item 3 had the smallest difficulty parameter. INFIT indices suggested that some responses to item 3 did not match the pattern in the rest of the sample. Classifying household food insecurity (HFI) based on items 1 and 2 compared with other 2-item combinations, including item 3, revealed a substantial undercount of HFI ranging from 5% to 8% points. CONCLUSIONS: Use of the HFSSM among YAs with diabetes could potentially result in biased HFI reporting and affect estimates of HFI prevalence in this population.

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.

Household Food Insecurity Is Associated With Physical Activity in Youth and Young Adults With Diabetes: A Cross-Sectional Study.

BACKGROUND: Physical activity (PA) is essential for optimal diabetes management. Household food insecurity (HFI) may negatively affect diabetes management behaviors. The purpose of this study was to cross-sectionally examine the association between HFI and PA in youth and young adults (YYA) with type 1 (N = 1998) and type 2 (N = 391) diabetes from the SEARCH for Diabetes in Youth Study. METHODS: HFI was measured with the US Household Food Security Survey Module. PA was measured with the International Physical Activity Questionnaire Short Form. Walking, moderate-intensity PA (excluding walking), vigorous-intensity PA, moderate- to vigorous-intensity PA, and total PA were estimated as minutes per week, while time spent sitting was assessed in minutes per day. All were modeled with median regression. Meeting PA guidelines or not was modeled using logistic regression. RESULTS: YYA with type 1 diabetes who experienced HFI spent more time walking than those who were food secure. YYA with type 2 diabetes who experienced HFI spent more time sitting than those who were food secure. CONCLUSIONS: Future research should examine walking for leisure versus other domains of walking in relation to HFI and use objective PA measures to corroborate associations between HFI and PA in YYA with diabetes.

Maternal Pre-Pregnancy BMI, Breastfeeding, and Child BMI.

OBJECTIVES: Breastfeeding practices may protect against offspring obesity, but this relationship is understudied among women with obesity. We describe the associations between breastfeeding practices and child BMI for age z-score (BMIz), stratified by maternal BMI. METHODS: We analyzed 8134 dyads from 21 cohorts in the Environmental Influences on Child Health Outcomes Program. Dyads with data for maternal pre-pregnancy BMI, infant feeding practices, and ≥1 child BMI assessment between the ages of 2 and 6 years were included. The associations between breastfeeding practices and continuous child BMIz were assessed by using multivariable linear mixed models. RESULTS: Maternal pre-pregnancy BMI category prevalence was underweight: 2.5%, healthy weight: 45.8%, overweight: 26.0%, and obese: 25.6%. Median child ages at the cessation of any breastfeeding and exclusive breastfeeding across the 4 BMI categories were 19, 26, 24, and 17 weeks and 12, 20, 17, and 12 weeks, respectively. Results were in the hypothesized directions for BMI categories. Three months of any breastfeeding was associated with a lower BMIz among children whose mothers were a healthy weight (-0.02 [-0.04 to 0.001], P = .06), overweight (-0.04 [-0.07 to -0.004], P = .03), or obese (-0.04 [-0.07 to -0.006], P = .02). Three months of exclusive breastfeeding was associated with a lower BMIz among children whose mothers were a healthy weight (-0.06 [-0.10 to -0.02], P = .002), overweight (-0.05 [-0.10 to 0.005], P = .07), or obese (-0.08 [-0.12 to -0.03], P = .001). CONCLUSIONS: Human milk exposure, regardless of maternal BMI category, was associated with a lower child BMIz in the Environmental Influences on Child Health Outcomes cohorts, supporting breastfeeding recommendations as a potential strategy for decreasing the risk of offspring obesity.

Opportunities for Examining Child Health Impacts of Early-Life Nutrition in the ECHO Program: Maternal and Child Dietary Intake Data from Pregnancy to Adolescence.

Background: Longitudinal measures of diet spanning pregnancy through adolescence are needed from a large, diverse sample to advance research on the effect of early-life nutrition on child health. The Environmental influences on Child Health Outcomes (ECHO) Program, which includes 69 cohorts, >33,000 pregnancies, and >31,000 children in its first 7-y cycle, provides such data, now publicly available. Objectives: This study aimed to describe dietary intake data available in the ECHO Program as of 31 August, 2022 (end of year 6 of Cycle 1) from pregnancy through adolescence, including estimated sample sizes, and to highlight the potential for future analyses of nutrition and child health. Methods: We identified and categorized ECHO Program dietary intake data, by assessment method, participant (pregnant person or child), and life stage of data collection. We calculated the number of maternal-child dyads with dietary data and the number of participants with repeated measures. We identified diet-related variables derived from raw dietary intake data and nutrient biomarkers measured from biospecimens. Results: Overall, 66 cohorts (26,941 pregnancies, 27,103 children, including 22,712 dyads) across 34 US states/territories provided dietary intake data. Dietary intake assessments included 24-h recalls (1548 pregnancies and 1457 children), food frequency questionnaires (4902 and 4117), dietary screeners (8816 and 23,626), and dietary supplement use questionnaires (24,798 and 26,513). Repeated measures were available for ∼70%, ∼30%, and ∼15% of participants with 24-h recalls, food frequency questionnaires, and dietary screeners, respectively. The available diet-related variables describe nutrient and food intake, diet patterns, and breastfeeding practices. Overall, 17% of participants with dietary intake data had measured nutrient biomarkers. Conclusions: ECHO cohorts have collected longitudinal dietary intake data spanning pregnancy through adolescence from a geographically, socioeconomically, and ethnically diverse US sample. As data collection continues in Cycle 2, these data present an opportunity to advance the field of nutrition and child health.

A mixed-methods analysis to understand the implementation of a multistakeholder research consortium: Environmental influences on child health outcomes (ECHO).

Introduction: Large, transdisciplinary research consortia have increasingly been called upon to address complex and challenging health problems. The National Institutes of Health's (NIH) Environmental influences on Child Health Outcomes (ECHO) Program developed multisite collaboration strategies to promote impactful collaborative observational research on child health. Team science and implementation science offer theoretical and methodological structure to answer questions about the strategies that facilitate successful consortia. We sought to characterize the elements and conditions that influence the implementation of a complex, interdisciplinary longitudinal research program, ECHO. Methods: Informed by the Practical, Robust, Implementation and Sustainability Model, our ethnographic research included semi-structured interviews with internal stakeholders and program evaluation metrics. We conducted template and matrix analysis and triangulated the qualitative and quantitative data to understand the implementation of ECHO. Results: Between February and May 2022, we conducted 24 virtual interviews with representatives from ECHO components. The main cross-cutting topics that emerged from thematic analysis were collaboration and team science; communication and decision-making; data processes and harmonization; and diversity, equity, and inclusion. Both the qualitative and secondary quantitative evaluation data provided insights into the reach, adoption, implementation, and effectiveness of the program. Conclusion: A large, multidisciplinary research consortium such as ECHO has produced conceptual, instrumental, capacity building, and connectivity impact for internal and external stakeholders. Facilitators included infrastructure that supported collaboration and learning, alignment of data processes, and harmonization. Opportunities for enhanced impact include multidisciplinary, multimethod communication strategies, and alignment of research priorities.

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.

A pre-conception clinical trial to reduce intergenerational obesity and diabetes risks: The NDPP-NextGen trial protocol.

BACKGROUND: Intrauterine exposure to maternal overweight/obesity or diabetes transmits risks to offspring, perpetuating a disease cycle across generations. Prenatal interventions to reduce maternal weight or dysglycemia have limited impact, while postpartum interventions can alter the intrauterine environment only if child-bearing continues. Efficacious preconception interventions are needed, especially for underserved populations, and with the potential to be scaled up sustainably. Research is also needed to assess intervention effects at conception, throughout pregnancy, and among offspring. METHODS: This two-arm, parallel randomized clinical trial will include 360 biological females with overweight/obesity and moderate-to-high likelihood of pregnancy within 24 months. Participants will be randomized 1:1 to a yearlong pre-conception lifestyle intervention based on the National Diabetes Prevention Program (NDPP-NextGen) or usual care. Data collection will occur at enrollment (before conception), post-conception (<8 weeks gestation), late pregnancy (28-32 weeks gestation), and delivery (before discharge) for participants who become pregnant within 24 months of enrollment. Main outcomes are post-conception body mass index (<8 weeks gestation; primary outcome), post-conception fasting glucose (<8 weeks gestation; secondary outcome), and neonatal adiposity (<2 days post-birth). Additional clinical, behavioral, perinatal and offspring data will be collected, and biospecimens (blood, urine, stool, cord blood) will be banked for future ancillary studies. CONCLUSION: This clinical trial will evaluate an intervention model (NDPP-NextGen) with potential to improve maternal health among the >50% of US females with overweight/obesity or diabetes risks in pregnancy. If successful, it can be scaled among >1800 organizations delivering NDPP in the United States to benefit the health of future generations.

Greater Gestational Vitamin D Status is Associated with Reduced Childhood Behavioral Problems in the Environmental Influences on Child Health Outcomes Program.

BACKGROUND: Vitamin D deficiency is common in pregnancy. Vitamin D plays an important role in the developing brain, and deficiency may impair childhood behavioral development. OBJECTIVES: This study examined the relationship between gestational 25(OH)D concentrations and childhood behavior in the Environmental influences on Child Health Outcomes (ECHO) Program. METHODS: Mother-child dyads from ECHO cohorts with data available on prenatal (first trimester through delivery) or cord blood 25(OH)D and childhood behavioral outcomes were included. Behavior was assessed using the Strengths and Difficulties Questionnaire or the Child Behavior Checklist, and data were harmonized using a crosswalk conversion. Linear mixed-effects models examined associations of 25(OH)D with total, internalizing, and externalizing problem scores while adjusting for important confounders, including age, sex, and socioeconomic and lifestyle factors. The effect modification by maternal race was also assessed. RESULTS: Early (1.5-5 y) and middle childhood (6-13 y) outcomes were examined in 1688 and 1480 dyads, respectively. Approximately 45% were vitamin D deficient [25(OH)D < 20 ng/mL], with Black women overrepresented in this group. In fully adjusted models, 25(OH)D concentrations in prenatal or cord blood were negatively associated with externalizing behavior T-scores in middle childhood [-0.73 (95% CI: -1.36, -0.10) per 10 ng/mL increase in gestational 25(OH)D]. We found no evidence of effect modification by race. In a sensitivity analysis restricted to those with 25(OH)D assessed in prenatal maternal samples, 25(OH)D was negatively associated with externalizing and total behavioral problems in early childhood. CONCLUSIONS: This study confirmed a high prevalence of vitamin D deficiency in pregnancy, particularly among Black women, and revealed evidence of an association between lower gestational 25(OH)D and childhood behavioral problems. Associations were more apparent in analyses restricted to prenatal rather than cord blood samples. Interventions to correct vitamin D deficiency during pregnancy should be explored as a strategy to improve childhood behavioral outcomes.

Association of Maternal BMI and Rapid Infant Weight Gain With Childhood Body Size and Composition.

OBJECTIVES: Maternal prepregnancy BMI (ppBMI) and an infant's rapid weight gain (RWG) are each associated with increased risk for childhood obesity. We hypothesized that ppBMI and RWG interact to further raise childhood obesity risk. METHODS: Mother-infant dyads (n = 414) from the Healthy Start Study, an observational prebirth cohort, were included. RWG was defined as a weight-for-age z score increase of ≥0.67 from birth to 3 to 7 months. Body composition was measured by air displacement plethysmography at age 4 to 7 years. General linear regression models were fit to characterize associations between ppBMI, RWG, and their interaction with the outcomes of childhood BMI-for-age z score and percent fat mass (%FM). RESULTS: A total of 18.6% (n = 77) of offspring experienced RWG. Maternal ppBMI and RWG were both positively associated with offspring BMI z score and %FM. RWG amplified the association between ppBMI and BMI z score, especially among females. Females exposed to maternal obesity and RWG had an average BMI at the 94th percentile (1.50 increase in childhood BMI z score) compared with those exposed to normal ppBMI and no RWG (average childhood BMI at the 51st percentile). RWG had a weaker effect on the association between ppBMI and %FM. Adjustment for breastfeeding status or childhood daily caloric intake did not significantly alter findings. CONCLUSIONS: Rapid infant weight gain interacts with maternal ppBMI to jointly exacerbate risk of childhood obesity. Pediatric providers should monitor infants for RWG, especially in the context of maternal obesity, to reduce future risk of obesity.

Preconception Counseling in Women With Diabetes: The SEARCH for Diabetes in Youth Study.

Preconception counseling is recommended for all women with diabetes starting at puberty to convey the importance of optimal diabetes management for maternal and fetal outcomes. This study included 622 female participants from the SEARCH for Diabetes in Youth study with a mean age of 22.2 years (range 14-35 years). Only 53.7% reported ever receiving preconception counseling, which was significantly lower among women seeing pediatric providers than those seeing adult or all-age providers. Older age and history of prior pregnancy were associated with increased odds of reporting having received preconception counseling. Identification of barriers to delivering preconception counseling to young females with diabetes and strategies to overcome them are needed to reduce the risk for pregnancy complications and adverse offspring health outcomes.

Selecting a dietary supplement with appropriate dosing for 6 key nutrients in pregnancy.

BACKGROUND: Most pregnant women in the United States (US) are at risk of inadequate intake of key nutrients during pregnancy from foods alone. Current dietary supplement practices reduce risk of inadequacy for only some nutrients and induce excessive intake of other nutrients. OBJECTIVES: Our study aimed to estimate the doses of supplementation needed to help most pregnant women achieve the recommended intake without exceeding upper limits for key prenatal nutrients and to identify US dietary supplements providing these doses. METHODS: We conducted 24-h dietary recalls in 2450 pregnant participants aged 14-50 y from 2007 to 2019. We estimated the usual intake of vitamins A and D, folate, calcium, iron, and ω-3 FAs from foods alone. We calculated the target doses of supplementation needed to shift 90% of participants to consume above the estimated average requirement and keep 90% below the tolerable upper limit. We identified products in the Dietary Supplement Label Database providing these target doses of supplementation. RESULTS: The target dose for supplementation was ≥198 mcg retinol activity equivalents of total vitamin A (with ≤2063 mcg preformed retinol); 7-91 mcg vitamin D; 169-720 mcg dietary folate equivalents of folic acid; 383-943 mg calcium; 13-22 mg iron; and ≥59 mg ω-3 FAs. Out of 20,547 dietary supplements (including 421 prenatal products), 69 products (33 prenatal) contained all 6 nutrients; 7 products (2 prenatal) contained target doses for 5 nutrients. Only 1 product (not a prenatal) contained target doses for all 6 nutrients, but it currently costs ∼USD200/mo and requires 7 tablets per daily serving. CONCLUSIONS: Almost no US dietary supplements provide key nutrients in the doses needed for pregnant women. Affordable and convenient products that fill the gap between food-based intake and estimated requirements of pregnancy without inducing excess intake are needed to support pregnant women and their offspring. Am J Clin Nutr 20XX;xx:xx-xx.

Trends in incidence of youth-onset type 1 and type 2 diabetes in the USA, 2002-18: results from the population-based SEARCH for Diabetes in Youth study.

BACKGROUND: The incidence of diabetes is increasing in children and young people. We aimed to describe the incidence of type 1 and type 2 diabetes in children and young people aged younger than 20 years over a 17-year period. METHODS: The SEARCH for Diabetes in Youth study identified children and young people aged 0-19 years with a physician diagnosis of type 1 or type 2 diabetes at five centres in the USA between 2002 and 2018. Eligible participants included non-military and non-institutionalised individuals who resided in one of the study areas at the time of diagnosis. The number of children and young people at risk of diabetes was obtained from the census or health plan member counts. Generalised autoregressive moving average models were used to examine trends, and data are presented as incidence of type 1 diabetes per 100 000 children and young people younger than 20 years and incidence of type 2 diabetes per 100 000 children and young people aged between 10 years and younger than 20 years across categories of age, sex, race or ethnicity, geographical region, and month or season of diagnosis. FINDINGS: We identified 18 169 children and young people aged 0-19 years with type 1 diabetes in 85 million person-years and 5293 children and young people aged 10-19 years with type 2 diabetes in 44 million person-years. In 2017-18, the annual incidence of type 1 diabetes was 22·2 per 100 000 and that of type 2 diabetes was 17·9 per 100 000. The model for trend captured both a linear effect and a moving-average effect, with a significant increasing (annual) linear effect for both type 1 diabetes (2·02% [95% CI 1·54-2·49]) and type 2 diabetes (5·31% [4·46-6·17]). Children and young people from racial and ethnic minority groups such as non-Hispanic Black and Hispanic children and young people had greater increases in incidence for both types of diabetes. Peak age at diagnosis was 10 years (95% CI 8-11) for type 1 diabetes and 16 years (16-17) for type 2 diabetes. Season was significant for type 1 diabetes (p=0·0062) and type 2 diabetes (p=0·0006), with a January peak in diagnoses of type 1 diabetes and an August peak in diagnoses of type 2 diabetes. INTERPRETATION: The increasing incidence of type 1 and type 2 diabetes in children and young people in the USA will result in an expanding population of young adults at risk of developing early complications of diabetes whose health-care needs will exceed those of their peers. Findings regarding age and season of diagnosis will inform focused prevention efforts. FUNDING: US Centers for Disease Control and Prevention and US National Institutes of Health.

Reducing Maternal Obesity and Diabetes Risks Prior to Conception with the National Diabetes Prevention Program.

INTRODUCTION: Intrauterine exposure to maternal obesity and hyperglycemia greatly increases offspring health risks. Scalable lifestyle interventions to lower weight and glycemia prior to conception are needed, but have been understudied, especially in diverse and low-income women with disproportionately high risks of negative maternal-child outcomes. The objective of this report is to provide initial evidence of the National Diabetes Prevention Program's (NDPP) effects on maternal-child outcomes in diverse, low-income women and their offspring. METHODS: The yearlong NDPP was delivered in a safety net healthcare system to 1,569 participants from 2013 to 2019. Using medical records, we evaluated outcomes for women < 40 years who became pregnant and delivered after attending the NDPP for ≥ 1 month (n = 32), as compared to a usual care group of women < 40 years (n = 26) who were initially eligible for the NDPP but were excluded due to pregnancy at enrollment. RESULTS: Most women in either group were Latinx, had Medicaid or were uninsured, and had obesity at baseline. The mean difference in BMI change from baseline to conception was - 1.8 ± 0.6 kg/m2 (p = 0.002) for NDPP versus usual care. Fewer NDPP participants had obesity at conception (56.7% vs. 88.0%, p = 0.011) and hyperglycemia in early pregnancy (4.0% vs. 25.0%; p = 0.020) than usual care. No other differences were statistically significant, yet nearly all outcomes favored the NDPP. Covariate-adjusted results were consistent, except the difference in frequency of obesity at conception was no longer significant (p = 0.132). DISCUSSION: Results provide preliminary evidence that the NDPP may support a reduction in peri-conceptional obesity/diabetes risks among diverse and low-income women.

SIGNIFICANCE: Scalable lifestyle interventions to lower weight and glycemia prior to conception are needed, especially to support diverse and low-income women with disproportionately high risks of negative maternal-child outcomes. This report presents initial evidence of the National Diabetes Prevention Program?s effects on maternal-child outcomes in diverse, low-income women and their offspring. Results encouragingly suggest that the program can reduce peri-conceptional obesity and glycemia, and may be a resource to help break the cycle of disease across generations.

Exploring Racial and Ethnic Differences in Arterial Stiffness Among Youth and Young Adults With Type 1 Diabetes.

Background We examined arterial stiffness in individuals with type 1 diabetes, and explored whether differences between Hispanic, non-Hispanic Black (NHB), and non-Hispanic White (NHW) individuals were attributable to modifiable clinical and social factors. Methods and Results Participants (n=1162; 22% Hispanic, 18% NHB, and 60% NHW) completed 2 to 3 research visits from ≈10 months to ≈11 years post type 1 diabetes diagnosis (mean ages of ≈9 to ≈20 years, respectively) providing data on socioeconomic factors, type 1 diabetes characteristics, cardiovascular risk factors, health behaviors, quality of clinical care, and perception of clinical care. Arterial stiffness (carotid-femoral pulse wave velocity [PWV], m/s) was measured at ≈20 years of age. We analyzed differences in PWV by race and ethnicity, then explored the individual and combined impact of the clinical and social factors on these differences. PWV did not differ between Hispanic (adjusted mean 6.18 [SE 0.12]) and NHW (6.04 [0.11]) participants after adjustment for cardiovascular risks (P=0.06) and socioeconomic factors (P=0.12), or between Hispanic and NHB participants (6.36 [0.12]) after adjustment for all factors (P=0.08). PWV was higher in NHB versus NHW participants in all models (all P<0.001). Adjustment for modifiable factors reduced the difference in PWV by 15% for Hispanic versus NHW participants; by 25% for Hispanic versus NHB; and by 21% for NHB versus NHW. Conclusions Cardiovascular and socioeconomic factors explain one-quarter of the racial and ethnic differences in PWV of young people with type 1 diabetes, but NHB individuals still experienced greater PWV. Exploration of pervasive inequities potentially driving these persistent differences is needed.