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.

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.

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 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.

Stratified split sampling of electronic health records.

Although superficially similar to data from clinical research, data extracted from electronic health records may require fundamentally different approaches for model building and analysis. Because electronic health record data is designed for clinical, rather than scientific use, researchers must first provide clear definitions of outcome and predictor variables. Yet an iterative process of defining outcomes and predictors, assessing association, and then repeating the process may increase Type I error rates, and thus decrease the chance of replicability, defined by the National Academy of Sciences as the chance of "obtaining consistent results across studies aimed at answering the same scientific question, each of which has obtained its own data."[1] In addition, failure to account for subgroups may mask heterogeneous associations between predictor and outcome by subgroups, and decrease the generalizability of the findings. To increase chances of replicability and generalizability, we recommend using a stratified split sample approach for studies using electronic health records. A split sample approach divides the data randomly into an exploratory set for iterative variable definition, iterative analyses of association, and consideration of subgroups. The confirmatory set is used only to replicate results found in the first set. The addition of the word 'stratified' indicates that rare subgroups are oversampled randomly by including them in the exploratory sample at higher rates than appear in the population. The stratified sampling provides a sufficient sample size for assessing heterogeneity of association by testing for effect modification by group membership. An electronic health record study of the associations between socio-demographic factors and uptake of hepatic cancer screening, and potential heterogeneity of association in subgroups defined by gender, self-identified race and ethnicity, census-tract level poverty and insurance type illustrates the recommended approach.

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.

Early-life exposure to residential black carbon and childhood cardiometabolic health.

BACKGROUND: Early life exposure to air pollution, such as particulate matter ≤2.5 µm (PM2.5), may be associated with obesity and adverse cardiometabolic health outcomes in childhood. However, the toxicity of PM2.5 varies according to its chemical composition. Black carbon (BC) is a constituent of PM2.5, but few studies have examined its impact on childhood cardiometabolic health. Therefore, we examined relationships between prenatal and early childhood exposure to BC and markers of adiposity and cardiometabolic health in early childhood. METHODS: This study included 578 mother-child pairs enrolled in the Healthy Start study (2009-2014) living in the Denver-metro area. Using a spatiotemporal prediction model, we assessed average residential black carbon levels during pregnancy and in the year prior to the early childhood follow-up visit at approximately 5 years old. We estimated associations between prenatal and early childhood BC and indicators of adiposity and cardiometabolic biomarkers in early childhood (mean 4.8 years; range, 4.0, 8.3), using linear regression. RESULTS: We found higher early childhood BC was associated with higher percent fat mass, fat mass index, insulin, and homeostatic model assessment for insulin resistance (HOMA-IR), and lower leptin and waist circumference at approximately 5 years old, after adjusting for covariates. For example, per interquartile range (IQR) increase in early childhood BC (IQR, 0.49 µg/m3) there was 3.32% higher fat mass (95% CI; 2.05, 4.49). Generally, we did not find consistent evidence of associations between prenatal BC and cardiometabolic health outcomes in early childhood, except for an inverse association between prenatal BC and adiponectin, an adipocyte-secreted hormone typically inversely associated with adiposity. CONCLUSIONS: Higher early childhood, but not in utero, ambient concentrations of black carbon, a component of air pollution, were associated with greater adiposity and altered insulin homeostasis at approximately 5 years old. Future studies should examine whether these changes persist later in life.

Prenatal exposure to poly- and perfluoroalkyl substances and the incidence of asthma in early childhood.

EXPOSURE TO POLY: and perfluoroalkyl substances (PFAS) in early life may increase the risk of childhood asthma, but evidence has been inconsistent. We estimated associations between maternal serum concentrations of PFAS during pregnancy and clinician-diagnosed asthma incidence in offspring through age eight. We included 597 mother-child pairs with PFAS quantified in mid-pregnancy serum and childhood medical records reviewed for asthma diagnoses. We used separate Cox proportional hazards models to assess the relationship between log-transformed concentrations of five PFAS and the incidence of asthma. We estimated associations between the PFAS mixture and clinician-diagnosed asthma incidence using quantile-based g-computation. PFAS concentrations were similar to those among females in the US general population. Seventeen percent of children (N = 104) were diagnosed with asthma during follow-up. Median (interquartile range) duration of follow-up was 4.7 (4.0, 6.2) years, and median age at asthma diagnosis was 1.7 (0.9, 2.8) years. All adjusted hazard ratios (HRs) were elevated, but all 95% confidence intervals (CI) included the null. The HR (95% CI) of asthma for a one-quartile increase in the PFAS mixture was 1.17 (0.86, 1.61). In this cohort of children followed to eight years of age, prenatal PFAS concentrations were not significantly associated with incidence of clinician-diagnosed asthma.

Infant negative affectivity and patterns of affect-biased attention.

Biased attention toward affective cues often cooccurs with the emergence and maintenance of internalizing disorders. However, few studies have assessed whether affect-biased attention in infancy relates to early indicators of psychopathological risk, such as negative affectivity. The current study evaluates whether negative affectivity relates to affect-biased attention in 6-month-old infants. Affect-biased attention was assessed via a free-viewing eye-tracking task in which infants were presented with a series of face pairs (comprised of a happy, angry, or sad face and a neutral face). Attention was quantified with metrics of both attention orienting and attention holding. Overall, infants showed no differences in attention orienting (i.e., speed of looking) or attention holding (i.e., duration of looking) toward emotional faces in comparison to the neutral face pairs. Negative affectivity, assessed via parent report, did not relate to attention orienting but was associated with biased attention toward positive, happy faces and away from threat-cueing, angry faces in comparison to the neutral faces they were paired with. These findings suggest that negative affectivity is associated with differences in attention holding, but not initial orienting toward emotional faces; biases which have important implications for the trajectory of socioemotional development.

The maternal diet index in pregnancy is associated with offspring allergic diseases: the Healthy Start study.

BACKGROUND: A systematic review showed limited associations between pregnancy diet and offspring allergy. We developed a maternal diet index during pregnancy that was associated with offspring allergy outcomes. METHODS: Data came from Healthy Start, a Colorado pre-birth cohort of mother/offspring dyads. Food propensity questionnaires were completed during pregnancy. Offspring allergic rhinitis, atopic dermatitis, asthma, wheeze, and food allergy diagnosis up to age four were verified from electronic medical records. Data were randomized into test and replication sets. The index included the weighted combination of variables that best predicted a combined outcome of any allergy in the test set. Index utility was verified in the replication set. Separate adjusted and unadjusted logistic models estimated associations between the index and each offspring allergy diagnosis in the full sample. RESULTS: The index included weighted measures of intake of vegetables, yogurt, fried potatoes, rice/grains, red meats, pure fruit juice, and cold cereals. Vegetables and yogurt were associated with the prevention of any allergy, while other components were associated with increased disease. In adjusted models, a one-unit increase in the index was significantly associated with reduced odds of offspring allergic rhinitis (odds ratio (CI) 0.82 [0.72-0.94]), atopic dermatitis (0.77 [0.69-0.86]), asthma (0.84 [0.74-0.96]), and wheeze (0.80 [0.71-0.90]), but not food allergy (0.84 [0.66-1.08]). CONCLUSIONS: This is the first study that has shown associations between an index of maternal dietary intake during pregnancy and multiple offspring allergic diseases. The results give hope for prevention of allergic diseases in utero.

Gestational diabetes mellitus, epigenetic age and offspring metabolism.

AIMS: No reports examine the relationship between in-utero exposure to gestational diabetes mellitus (GDM), offspring epigenetic age acceleration (EAA), and offspring insulin sensitivity. METHODS: Using data from a cohort study, we examined associations between GDM in-utero exposure and offspring EAA at approximately 10 years of age, using separate regression models adjusting for offspring chronological age and sex. We also examined associations between EAA with updated homeostasis model assessment of insulin sensitivity and secretion (HOMA2-S and HOMA2-ß) measured at approximately 10 and 16 years of age, using mixed linear regression models accounting for repeated measures after adjustment for offspring chronological age and sex. RESULTS: Compared to unexposed offspring (n = 91), offspring exposed to GDM (n = 88) had greater EAA or older extrinsic age compared to chronological age (ß-coefficient 2.00, 95% confidence interval [0.71, 3.28], p = 0.0025), but not greater intrinsic EAA (ß-coefficient -0.07, 95% CI [-0.71, 0.57], p = 0.93). Extrinsic EAA was associated with lower insulin sensitivity (ß-coefficient -0.018, 95% CI [-0.035, -0.002], p = 0.03) and greater insulin secretion (ß-coefficient 0.018, 95% CI [0.006, 0.03], p = 0.003), and these associations persisted after further adjustment for measures of maternal and child adiposity. No associations were observed between intrinsic EAA and insulin sensitivity and secretion, before or after adjustment for measures of maternal and child adiposity. CONCLUSIONS: In this study, children exposed to GDM experience greater extrinsic EAA, which is associated with lower insulin sensitivity and greater insulin secretion. Further studies are needed to determine the directionality of these associations.

Associations between child filaggrin mutations and maternal diet with the development of allergic diseases in children.

BACKGROUND: Filaggrin (FLG) loss-of-function mutations in children and maternal diet in pregnancy have been implicated in child allergy outcomes. This paper studies the questions: "do FLG mutations modify the effect of maternal diet on the odds of development of allergic diseases?" and "which factor leads to the highest rate of diagnosis allergic diseases over time, maternal diet, or FLG mutations?". METHODS: Exact logistic regressions studied effect modification. Cox proportional hazard models compared the rate of allergic disease development in three groups (N = 624): (1) children with FLG mutation, (2) children without FLG mutation whose mothers did not eat an allergy preventive diet, and (3) children without FLG mutation whose mothers ate an allergy preventive diet. Maternal diet was classified using a validated index. RESULTS: Cox models showed the development of atopic dermatitis, asthma, and wheeze was significantly higher for children in group 1 versus 3 (HR = 2.40 [1.32, 4.37], HR = 2.29 [1.05, 4.97], and HR 2.10 [1.004, 4.38], respectively), but not significantly higher for children in group 1 versus 2 (HR = 1.30 [0.74, 2.29], HR = 1.27 [0.61, 2.63], and HR = 1.29 [0.65, 2.58], respectively). Development of allergic rhinitis was significantly higher for group 1 versus 2 and 3 (1 vs. 2: HR = 2.29 [1.10, 4.76]; 1 vs. 3: HR = 3.21 [1.46, 7.08]). There was no significant effect modification for any outcome. CONCLUSION: Children with FLG mutation had similar risk of atopic dermatitis, asthma, and wheeze as children without an FLG mutation whose mothers did not eat an allergy preventive diet during pregnancy. Child FLG mutation did not modify the effect of maternal diet. The results suggest that maternal diet in pregnancy, a modifiable risk factor, could be a target for preventive interventions.

A comparison of the remote food photography method and the automated self-administered 24-h dietary assessment tool for measuring full-day dietary intake among school-age children.

The limitations of self-report measures of dietary intake are well-known. Novel, technology-based measures of dietary intake may provide a more accurate, less burdensome alternative to existing tools. The first objective of this study was to compare participant burden for two technology-based measures of dietary intake among school-age children: the Automated-Self-Administered 24-hour Dietary Assessment Tool-2018 (ASA24-2018) and the Remote Food Photography Method (RFPM). The second objective was to compare reported energy intake for each method to the Estimated Energy Requirement for each child, as a benchmark for actual intake. Forty parent-child dyads participated in two, 3-d dietary assessments: a parent proxy-reported version of the ASA24 and the RFPM. A parent survey was subsequently administered to compare satisfaction, ease of use and burden with each method. A linear mixed model examined differences in total daily energy intake between assessments, and between each assessment method and the Estimated Energy Requirement (EER). Reported energy intake was 379 kcal higher with the ASA24 than the RFPM (P = 0·0002). Reported energy intake with the ASA24 was 231 kcal higher than the EER (P = 0·008). Reported energy intake with the RFPM did not differ significantly from the EER (difference in predicted means = -148 kcal, P = 0·09). Median satisfaction and ease of use scores were five out of six for both methods. A higher proportion of parents reported that the ASA24 was more time-consuming than the RFPM (74·4 % v. 25·6 %, P = 0·002). Utilisation of both methods is warranted given their high satisfaction among parents.

Adherence to index-based dietary patterns in childhood and BMI trajectory during the transition to adolescence: the EPOCH study.

BACKGROUND: In the United States, one in five adolescents are obese. Index-based dietary patterns are measures of the overall diet that have the potential to serve as valuable obesity risk stratification tools. However, little is known about the association between adherence to index-based dietary patterns in childhood and BMI during the transition from childhood to adolescence. OBJECTIVE: To prospectively examine the relationship between adherence to three index-based dietary patterns in childhood and BMI trajectory during the transition to adolescence. METHODS: The study included 581 children enrolled in a Colorado prospective cohort study conducted between 2006 and 2015. Dietary intake was assessed with the Block Kids Food Frequency Questionnaire at age 10 years. Scores were calculated for the Healthy Eating Index-2010 (HEI-2010), the alternate Mediterranean (aMED) diet, and the Dietary Approaches to Stop Hypertension (DASH) diet. Weight and height were assessed via anthropometry at two research visits (ages 10 and 16 years), with interim clinical measurements extracted from Kaiser Permanente medical records. Separate mixed models were used to assess the association between each diet index score and BMI over a 6-year period. Models were stratified by sex and adjusted for age, race/ethnicity, income, and exposure to gestational diabetes. RESULTS: Median (IQR) number of BMI assessments was 14 (10-18). Among girls, for every ten-unit increase in HEI-2010 score, there was an average 0.64 kg/m2 decrease (p = 0.007) in BMI over time, after adjustment for covariates. Among girls, there was no association between BMI and aMED (ß = -0.19, p = 0.24) or DASH (ß = 0.28, p = 0.38). Among boys, there was no statistically significant association between BMI and HEI-2010 (0.06, p = 0.83), aMED (0.07, p = 0.70), or DASH (0.42, p = 0.06). CONCLUSIONS: Efforts to prevent adolescent obesity could benefit from considering the degree of adherence to federal dietary guidance, as assessed by the HEI, in the period preceding adolescence, especially among girls.

Disparities in Risks of Inadequate and Excessive Intake of Micronutrients during Pregnancy.

BACKGROUND: Inadequate or excessive intake of micronutrients in pregnancy has potential to negatively impact maternal/offspring health outcomes. OBJECTIVE: The aim was to compare risks of inadequate or excessive micronutrient intake in diverse females with singleton pregnancies by strata of maternal age, race/ethnicity, education, and prepregnancy BMI. METHODS: Fifteen observational cohorts in the US Environmental influences on Child Health Outcomes (ECHO) Consortium assessed participant dietary intake with 24-h dietary recalls (n = 1910) or food-frequency questionnaires (n = 7891) from 1999-2019. We compared the distributions of usual intake of 19 micronutrients from food alone (15 cohorts; n = 9801) and food plus dietary supplements (10 cohorts with supplement data; n = 7082) to estimate the proportion with usual daily intakes below their age-specific daily Estimated Average Requirement (EAR), above their Adequate Intake (AI), and above their Tolerable Upper Intake Level (UL), overall and within sociodemographic and anthropometric subgroups. RESULTS: Risk of inadequate intake from food alone ranged from 0% to 87%, depending on the micronutrient and assessment methodology. When dietary supplements were included, some women were below the EAR for vitamin D (20-38%), vitamin E (17-22%), and magnesium (39-41%); some women were above the AI for vitamin K (63-75%), choline (7%), and potassium (37-53%); and some were above the UL for folic acid (32-51%), iron (39-40%), and zinc (19-20%). Highest risks for inadequate intakes were observed among participants with age 14-18 y (6 nutrients), non-White race or Hispanic ethnicity (10 nutrients), less than a high school education (9 nutrients), or obesity (9 nutrients). CONCLUSIONS: Improved diet quality is needed for most pregnant females. Even with dietary supplement use, >20% of participants were at risk of inadequate intake of ≥1 micronutrients, especially in some population subgroups. Pregnancy may be a window of opportunity to address disparities in micronutrient intake that could contribute to intergenerational health inequalities.

Dietary factors during pregnancy and atopic outcomes in childhood: A systematic review from the European Academy of Allergy and Clinical Immunology.

RATIONALE: Allergic diseases are an increasing public health concern, and early life environment is critical to immune development. Maternal diet during pregnancy has been linked to offspring allergy risk. In turn, maternal diet is a potentially modifiable factor, which could be targeted as an allergy prevention strategy. In this systematic review, we focused on non-allergen-specific modifying factors of the maternal diet in pregnancy on allergy outcomes in their offspring. METHODS: We undertook a systematic review of studies investigating the association between maternal diet during pregnancy and allergic outcomes (asthma/wheeze, hay fever/allergic rhinitis/seasonal allergies, eczema/atopic dermatitis (AD), food allergies, and allergic sensitization) in offspring. Studies evaluating the effect of food allergen intake were excluded. We searched three bibliographic databases (MEDLINE, EMBASE, and Web of Science) through February 26, 2019. Evidence was critically appraised using modified versions of the Cochrane Collaboration Risk of Bias tool for intervention trials and the National Institute for Clinical Excellence methodological checklist for cohort and case-control studies and meta-analysis performed from RCTs. RESULTS: We identified 95 papers: 17 RCTs and 78 observational (case-control, cross-sectional, and cohort) studies. Observational studies varied in design and dietary intakes and often had contradictory findings. Based on our meta-analysis, RCTs showed that vitamin D supplementation (OR: 0.72; 95% CI: 0.56-0.92) is associated with a reduced risk of wheeze/asthma. A positive trend for omega-3 fatty acids was observed for asthma/wheeze, but this did not reach statistical significance (OR: 0.70; 95% CI: 0.45-1.08). Omega-3 supplementation was also associated with a non-significant decreased risk of allergic rhinitis (OR: 0.76; 95% CI: 0.56-1.04). Neither vitamin D nor omega-3 fatty acids were associated with an altered risk of AD or food allergy. CONCLUSIONS: Prenatal supplementation with vitamin D may have beneficial effects for prevention of asthma. Additional nutritional factors seem to be required for modulating the risk of skin and gastrointestinal outcomes. We found no consistent evidence regarding other dietary factors, perhaps due to differences in study design and host features that were not considered. While confirmatory studies are required, there is also a need for performing RCTs beyond single nutrients/foods.

Persistent effects of in utero overnutrition on offspring adiposity: the Exploring Perinatal Outcomes among Children (EPOCH) study.

AIMS/HYPOTHESIS: We previously showed that intrauterine exposure to gestational diabetes mellitus (GDM) increases selected markers of adiposity in pre-pubertal adolescents. In the present study, we examined these associations in adolescence, and explored whether they are strengthened as the participants transition through puberty. METHODS: Data from 597 individuals (505 unexposed, 92 exposed) participating in the longitudinal Exploring Perinatal Outcomes among Children (EPOCH) study in Colorado were collected at two research visits when the participants were, on average, 10.4 and 16.7 years old. Adiposity measures included BMI, waist/height ratio, and visceral and subcutaneous adipose tissue (as determined by MRI). Separate general linear mixed models were used to assess the longitudinal relationships between exposure to maternal GDM and each adiposity outcome. We tested whether the effect changed over time by including an interaction term between exposure and age in our models, and whether the associations were explained by postnatal behaviours. RESULTS: Compared with unexposed participants, those exposed to maternal GDM had higher BMI (ß = 1.28; 95% CI 0.35, 2.21; p < 0.007), waist/height ratio (ß = 0.03; 95% CI 0.01, 0.04; p = 0.0004), visceral adipose tissue (ß = 4.81; 95% CI 1.08, 8.54; p = 0.01) and subcutaneous adipose tissue (ß = 35.15; 95% CI 12.43, 57.87; p < 0.003). The magnitude of these differences did not change over time and the associations did not appear to be explained by postnatal behaviours. CONCLUSIONS/INTERPRETATION: Our data provide further evidence that intrauterine exposure to maternal GDM is associated with increased offspring adiposity, an effect that appears early in life and tracks throughout adolescence. Efforts to prevent childhood obesity following intrauterine exposure to maternal GDM should target the prenatal or early life periods.

Fetal exposure to maternal active and secondhand smoking with offspring early-life growth in the Healthy Start study.

BACKGROUND: Previous studies have modeled the association between fetal exposure to tobacco smoke and body mass index (BMI) growth trajectories, but not the timing of catch-up growth. Research on fetal exposure to maternal secondhand smoking is limited. OBJECTIVES: To explore the associations between fetal exposure to maternal active and secondhand smoking with body composition at birth and BMI growth trajectories through age 3 years. METHODS: We followed 630 mother-child pairs enrolled in the Healthy Start cohort through age 3 years. Maternal urinary cotinine was measured at ~ 27 weeks gestation. Neonatal body composition was measured using air displacement plethysmography. Child weight and length/height were abstracted from medical records. Linear regression models examined the association between cotinine categories (no exposure, secondhand smoke, active smoking) with weight, fat mass, fat-free mass, and percent fat mass at birth. A mixed-effects regression model estimated the association between cotinine categories and BMI. RESULTS: Compared to unexposed offspring, birth weight was significantly lower among offspring born to active smokers (-343-g; 95% CI: -473, -213), but not among offspring of women exposed to secondhand smoke (-47-g; 95% CI: -130, 36). There was no significant difference in the rate of BMI growth over time between offspring of active and secondhand smokers (p = 0.58). Therefore, our final model included a single growth rate parameter for the combined exposure groups of active and secondhand smokers. The rate of BMI growth for the combined exposed group was significantly more rapid (0.27 kg/m2 per year; 95% CI: 0.05, 0.69; p < 0.01) than the unexposed. CONCLUSIONS: Offspring prenatally exposed to maternal active or secondhand smoking experience rapid and similar BMI growth in the first three years of life. Given the long-term consequences of rapid weight gain in early childhood, it is important to encourage pregnant women to quit smoking and limit their exposure to secondhand smoke.

Improving the diagnostic accuracy of a stratified screening strategy by identifying the optimal risk cutoff.

BACKGROUND: The American Cancer Society (ACS) suggests using a stratified strategy for breast cancer screening. The strategy includes assessing risk of breast cancer, screening women at high risk with both MRI and mammography, and screening women at low risk with mammography alone. The ACS chose their cutoff for high risk using expert consensus. METHODS: We propose instead an analytic approach that maximizes the diagnostic accuracy (AUC/ROC) of a risk-based stratified screening strategy in a population. The inputs are the joint distribution of screening test scores, and the odds of disease, for the given risk score. Using the approach for breast cancer screening, we estimated the optimal risk cutoff for two different risk models: the Breast Cancer Screening Consortium (BCSC) model and a hypothetical model with much better discriminatory accuracy. Data on mammography and MRI test score distributions were drawn from the Magnetic Resonance Imaging Screening Study Group. RESULTS: A risk model with an excellent discriminatory accuracy (c-statistic [Formula: see text]) yielded a reasonable cutoff where only about 20% of women had dual screening. However, the BCSC risk model (c-statistic [Formula: see text]) lacked the discriminatory accuracy to differentiate between women who needed dual screening, and women who needed only mammography. CONCLUSION: Our research provides a general approach to optimize the diagnostic accuracy of a stratified screening strategy in a population, and to assess whether risk models are sufficiently accurate to guide stratified screening. For breast cancer, most risk models lack enough discriminatory accuracy to make stratified screening a reasonable recommendation.