ABSTRACT
Tracking trajectories of body size in children provides insight into chronic disease risk. One measure of pediatric body size is body mass index (BMI), a function of height and weight. Errors in measuring height or weight may lead to incorrect assessment of BMI. Yet childhood measures of height and weight extracted from electronic medical records often include values which seem biologically implausible in the context of a growth trajectory. Removing biologically implausible values reduces noise in the data, and thus increases the ease of modeling associations between exposures and childhood BMI trajectories, or between childhood BMI trajectories and subsequent health conditions. We developed open-source algorithms (available on github) for detecting and removing biologically implausible values in pediatric trajectories of height and weight. A Monte Carlo simulation experiment compared the sensitivity, specificity and speed of our algorithms to three published algorithms. The comparator algorithms were selected because they used trajectory information, had open-source code, and had published verification studies. Simulation inputs were derived from longitudinal epidemiological cohorts. Our algorithms had higher specificity, with similar sensitivity and speed, when compared to the three published algorithms. The results suggest that our algorithms should be adopted for cleaning longitudinal pediatric growth data.
Subject(s)
Algorithms , Body Mass Index , Humans , Child , Longitudinal Studies , Body Height , Female , Electronic Health Records , Male , Body Weight , Child, Preschool , Monte Carlo Method , Adolescent , InfantABSTRACT
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.
Subject(s)
Cardiovascular Diseases , Randomized Controlled Trials as Topic , Humans , Cardiovascular Diseases/prevention & controlABSTRACT
Using data from a longitudinal cohort of children, we examined whether epigenetic age acceleration (EAA) was associated with pubertal growth and whether these associations were mediated by adiposity. We examined associations between EAA at approximately 10 years of age with pubertal growth metrics, including age at peak height velocity (PHV), PHV, and sex steroid levels and whether these associations were mediated by measures of adiposity including body mass index (BMI) and MRI-assessed visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Children (n = 135) with accelerated EAA had higher PHV (ß 0.018, p = 0.0008) although the effect size was small. The association between EAA and age at PHV was not significant (ß - 0.0022, p = 0.067). Although EAA was associated with higher BMI (ß 0.16, p = 0.0041), VAT (ß 0.50, p = 0.037), and SAT (ß 3.47, p = 0.0076), BMI and VAT did not mediate associations between EAA and PHV, while SAT explained 8.4% of the association. Boys with higher EAA had lower total testosterone (ß - 12.03, p = 0.0014), but associations between EAA and other sex steroids were not significant, and EAA was not associated with sex steroid levels in girls. We conclude that EAA did not have strong associations with either age at onset of puberty or pubertal growth speed, although associations with growth speed were statistically significant. Studies with larger sample sizes are needed to confirm this pattern of associations.
Subject(s)
Obesity , Puberty , Male , Child , Female , Humans , Body Mass Index , Testosterone , Epigenesis, GeneticABSTRACT
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.
Subject(s)
Diabetes Mellitus, Type 1 , Diabetes Mellitus, Type 2 , Child , Adolescent , Humans , Young Adult , Adult , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 1/complications , Ethnicity , Cross-Sectional Studies , Prospective StudiesABSTRACT
BACKGROUND: Infant feeding patterns have been linked with obesity risk in childhood, but associations with precise measures of body fat distribution are unclear. OBJECTIVE: We examined associations of infant feeding practices with abdominal fat and hepatic fat trajectories in childhood. METHODS: This study included 356 children in the Healthy Start Study, a prospective prebirth cohort in Colorado. Infant feeding practices were assessed by postnatal interviews and categorized as any human milk <6 mo compared with ≥6 mo; complementary foods introduced ≤4 mo compared with >4 mo; soda introduced ≤18 mo compared with >18 mo. Abdominal subcutaneous (SAT) and visceral adipose tissue (VAT) areas and hepatic fat (%) were assessed by magnetic resonance imaging in early and middle childhood (median 5 and 9 y old, respectively). We examined associations of infant feeding with adiposity trajectories across childhood using linear mixed models. RESULTS: In the sample of children, 67% consumed human milk ≥6 mo, 75% were introduced to complementary foods at >4 mo, and 81% were introduced to soda at >18 mo. We did not find any associations between duration of any human milk consumption and childhood adiposity trajectories. Early introduction to complementary foods (≤4 mo) was associated with faster rates of change for SAT and VAT during childhood (Slope [95% CI]: 15.1 [10.7,19.4] cm2/y for SAT; 2.5 [1.9,2.9] cm2/y for VAT), compared with introduction at >4 mo (5.5 [3.0,8.0] cm2/y and 1.6 [1.3,1.9] cm2/y, respectively). Similarly, early introduction to soda (≤18 mo) was associated with faster rates of change for all 3 outcomes during childhood (Slope [95% CI]: 20.6 [15.0,26.1] cm2/y for SAT, 2.7 [2.0,3.3] cm2/y for VAT, 0.3 [0.1,0.5] %/year for hepatic fat) compared with delayed introduction (5.4 [2.8,8.0] cm2/y, 1.7 [1.3, 2.0] cm2/y, -0.1 [-0.2,0.0] %/y, respectively). CONCLUSIONS: The timing of introduction and quality of complementary foods in infancy was associated with rates of abdominal and hepatic fat accrual during childhood. Experimental studies are needed to assess underlying mechanisms.
Subject(s)
Adiposity , Pediatric Obesity , Infant , Humans , Child , Prospective Studies , Longitudinal Studies , Abdominal Fat , Pediatric Obesity/epidemiology , Pediatric Obesity/etiology , Pediatric Obesity/pathology , Intra-Abdominal Fat , Feeding BehaviorABSTRACT
BACKGROUND: Prenatal exposures to certain poly- and perfluoroalkyl substances (PFAS) are associated with reduced humoral responses to some childhood immunizations. OBJECTIVE: We estimated associations between prenatal PFAS exposure and child antibody titers for measles, mumps, rubella (MMR), and varicella after immunization. METHODS: We measured serum antibody titers of 145 children (4-8 y old) enrolled in the Healthy Start cohort in Colorado, whose mothers had PFAS quantified mid-pregnancy (2009-2014). We used linear and logistic regression models to assess the relationship between five PFAS detected in >65% of mothers and continuous or non-high-censored ("low") antibody titers and quantile g-computation to evaluate the overall effect of the PFAS mixture. RESULTS: Median concentrations of individual PFAS were at or below the median reported among females in the United States. After receiving two vaccine doses, seropositive levels of antibodies were detected among most (93%-100%) children. Each log-unit increase in perfluorononanoate was associated with 2.09 [95% confidence interval (CI): 1.13, 3.87] times higher odds of a low measles titer, and each log-unit increase in perfluorooctanoate was associated with 2.46 (95% CI: 1.28, 4.75) times higher odds of a low mumps titer. Odds ratios for all other PFAS were elevated, but CIs included the null. Each quartile increase in the PFAS mixture was associated with 1.35 (95% CI: 0.80, 2.26) times higher odds of a low measles titer and 1.44 (95% CI: 0.78, 2.64) times higher odds of a low mumps titer. No significant associations were observed between PFAS and varicella or rubella antibodies. In stratified analyses, associations were negative among female children, except for perfluorohexane sulfonate and varicella, whereas they were positive among males. DISCUSSION: Some prenatal PFAS were associated with lower antibody titers among fully immunized children. The potential for immunotoxic effects of PFAS requires further investigation in a larger study, because exposure is ubiquitous globally. https://doi.org/10.1289/EHP12863.
Subject(s)
Chickenpox , Fluorocarbons , Measles , Mumps , Prenatal Exposure Delayed Effects , Rubella , Vaccines , Child , Male , Pregnancy , Female , Humans , Child, Preschool , Chickenpox/epidemiology , Mumps/epidemiology , Prenatal Exposure Delayed Effects/epidemiology , Rubella/epidemiologyABSTRACT
BACKGROUND: Effortful control, or the regulation of thoughts and behaviour, is a potential target for preventing childhood obesity. OBJECTIVES: To assess effortful control in infancy through late childhood as a predictor of repeated measures of body mass index (BMI) from infancy through adolescence, and to examine whether sex moderates the associations. METHODS: Maternal report of offspring effortful control and measurements of child BMI were obtained at 7 and 8 time points respectively from 191 gestational parent/child dyads from infancy through adolescence. General linear mixed models were used. RESULTS: Effortful control at 6 months predicted BMI trajectories from infancy through adolescence, F(5,338) = 2.75, p = 0.03. Further, when effortful control at other timepoints were included in the model, they added no additional explanatory value. Sex moderated the association between 6-month effortful control and BMI, F(4, 338) = 2.59, p = 0.03, with poorer infant effortful control predicting higher BMI in early childhood for girls, and more rapid increases in BMI in early adolescence for boys. CONCLUSIONS: Effortful control in infancy was associated with BMI over time. Specifically, poor effortful control during infancy was associated with higher BMI in childhood and adolescence. These findings support the argument that infancy may be a sensitive window for the development of later obesity.
Subject(s)
Pediatric Obesity , Child , Child, Preschool , Male , Female , Humans , Infant , Adolescent , Body Mass Index , Pediatric Obesity/epidemiology , Pediatric Obesity/prevention & control , Family , Linear Models , Research DesignABSTRACT
CONTEXT: Previous studies have shown that exposure to maternal gestational diabetes mellitus (GDM) is associated with increased offspring body mass index (BMI) and risk for overweight or obesity. OBJECTIVE: This study aimed to explore differences in BMI trajectories among youth exposed or not exposed to maternal GDM and understand whether these associations differ across life stages. METHODS: Data from 403 mother/child dyads (76 exposed; 327 not exposed) participating in the longitudinal Exploring Perinatal Outcomes among Children (EPOCH) study in Colorado were used. Participants who had 2 or more longitudinal height measurements from 27 months to a maximum of 19 years were included in the analysis. Life stages were defined using puberty related timepoints: early childhood (27 months to pre-adolescent dip [PAD, average age 5.5 years]), middle childhood (from PAD to age at peak height velocity [APHV, average age 12.2 years]), and adolescence (from APHV to 19 years). Separate general linear mixed models, stratified by life stage, were used to assess associations between GDM exposure and offspring BMI. RESULTS: There was not a significant association between exposure to GDM and BMI trajectories during early childhood (P = .27). In middle childhood, participants exposed to GDM had higher BMI trajectories compared to those not exposed (males: P = .005, females: P = .002) and adolescent (P = .02) periods. CONCLUSION: Our study indicates that children who are exposed to GDM may experience higher BMI trajectories during middle childhood and adolescence, but not during early childhood. These data suggest that efforts to prevent childhood obesity among those exposed in utero to maternal GDM should start before pubertal onset.
Subject(s)
Diabetes, Gestational , Pediatric Obesity , Pregnancy , Male , Female , Child , Adolescent , Humans , Child, Preschool , Diabetes, Gestational/epidemiology , Body Mass Index , Risk Factors , Pediatric Obesity/epidemiology , Pediatric Obesity/etiology , Prospective StudiesABSTRACT
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.
Subject(s)
Obesity, Maternal , Pediatric Obesity , Infant , Child , Humans , Female , Pregnancy , Child, Preschool , Infant, Newborn , Body Mass Index , Pediatric Obesity/epidemiology , Pediatric Obesity/etiology , Obesity, Maternal/epidemiology , Weight Gain , Mothers , Body Composition , Birth WeightABSTRACT
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.
Subject(s)
Diabetes Mellitus, Type 1 , Vascular Stiffness , Adolescent , Humans , Young Adult , Black or African American , Diabetes Mellitus, Type 1/diagnosis , Ethnicity , Pulse Wave Analysis , White , Hispanic or LatinoABSTRACT
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.
Subject(s)
Environmental Exposure , Research Design , Humans , Sample Size , Environmental Exposure/adverse effects , Software , Longitudinal StudiesABSTRACT
BACKGROUND: Unhealthy diet, physical inactivity, and social disconnection are important modifiable risk factors for non-communicable and other chronic diseases, which might be alleviated through nature-based community interventions. We tested whether a community gardening intervention could reduce these common health risks in an adult population that is diverse in terms of age, ethnicity, and socioeconomic status. METHODS: In this observer-blind, randomised, controlled trial, we recruited individuals who were on Denver Urban Garden waiting lists for community gardens in Denver and Aurora (CO, USA), aged 18 years or older, and had not gardened in the past 2 years. Participants were randomly assigned (1:1), using a randomised block design in block sizes of two, four, or six, to receive a community garden plot (intervention group) or remain on a waiting list and not garden (control group). Researchers were masked to group allocation. Primary outcomes were diet, physical activity, and anthropometry; secondary outcomes were perceived stress and anxiety. During spring (April to early June, before randomisation; timepoint 1 [T1]), autumn (late August to October; timepoint 2 [T2]), and winter (January to March, after the intervention; timepoint 3 [T3]), participants completed three diet recalls, 7-day accelerometry, surveys, and anthropometry. Analyses were done using the intention-to-treat principle (ie, including all participants randomly assigned to groups, and assessed as randomised). We used mixed models to test time-by-intervention hypotheses at an α level of 0·04, with T2 and T3 intervention effects at an α level of 0·005 (99·5% CI). Due to potential effects of the COVID-19 pandemic on outcomes, we excluded all participant data collected after Feb 1, 2020. This study is registered with ClinicalTrials.gov, NCT03089177, and data collection is now complete. FINDINGS: Between Jan 1, 2017, and June 15, 2019, 493 adults were screened and 291 completed baseline measures and were randomly assigned to the intervention (n=145) or control (n=146) groups. Mean age was 41·5 years (SD 13·5), 238 (82%) of 291 participants were female, 52 (18%) were male, 99 (34%) identified as Hispanic, and 191 (66%) identified as non-Hispanic. 237 (81%) completed measurements before the beginning of the COVID-19 pandemic. One (<1%) participant in the intervention group had an adverse allergic event in the garden. Significant time-by-intervention effects were observed for fibre intake (p=0·034), with mean between-group difference (intervention minus control) at T2 of 1·41 g per day (99·5% CI -2·09 to 4·92), and for moderate-to-vigorous physical activity (p=0·012), with mean between-group difference of 5·80 min per day (99·5% CI -4·44 to 16·05). We found no significant time-by-intervention interactions for combined fruit and vegetable intake, Healthy Eating Index (measured using Healthy Eating Index-2010), sedentary time, BMI, and waist circumference (all p>0·04). Difference score models showed greater reductions between T1 and T2 in perceived stress and anxiety among participants in the intervention group than among those in the control group. INTERPRETATION: Community gardening can provide a nature-based solution, accessible to a diverse population including new gardeners, to improve wellbeing and important behavioural risk factors for non-communicable and chronic diseases. FUNDING: American Cancer Society, University of Colorado Cancer Centre, University of Colorado Boulder, National Institutes of Health, US Department of Agriculture National Institute of Food and Agriculture, Michigan AgBioResearch Hatch projects.
Subject(s)
COVID-19 , Gardening , United States , Adult , Humans , Male , Female , Pandemics , Diet , ExerciseABSTRACT
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.
Subject(s)
Diabetes, Gestational , Insulin Resistance , Prenatal Exposure Delayed Effects , Adiposity , Child , Cohort Studies , Diabetes, Gestational/epidemiology , Epigenesis, Genetic , Female , Humans , Obesity/complications , PregnancyABSTRACT
BACKGROUND: Adiposity is an established risk factor for pediatric nonalcoholic fatty liver disease (NAFLD), but little is known about the influence of body composition patterns earlier in life on NAFLD risk. OBJECTIVES: We aimed to examine associations of body composition at birth and body composition trajectories from birth to early childhood with hepatic fat in early childhood. METHODS: Data were from the longitudinal Healthy Start Study in Colorado. Fat-free mass index (FFMI), fat mass index (FMI), percentage body fat (BF%), and BMI were assessed at birth and/or â¼5 y in >1200 children by air displacement plethysmography and anthropometrics. In a subset (n = 285), hepatic fat was also assessed at â¼5 y by MRI. We used a 2-stage modeling approach: first, we fit body composition trajectories from birth to early childhood using mixed models with participant-specific intercepts and linear slopes (i.e., individual deviations from the population average at birth and rate of change per year, respectively); second, associations of participant-specific trajectory deviations with hepatic fat were assessed by multivariable-adjusted linear regression. RESULTS: Participant-specific intercepts at birth for FFMI, FMI, BF%, and BMI were inversely associated with log-hepatic fat in early childhood in models adjusted for offspring demographics and maternal/prenatal variables [back-transformed ß (95% CI) per 1 SD: 0.93 (0.88, 0.99), 0.94 (0.88, 0.99), 0.94 (0.89, 0.99), and 0.90 (0.85, 0.96), respectively]. Whereas, faster velocities for BF% and BMI from birth to â¼5 y were positively associated with log-hepatic fat [back-transformed ß (95% CI) per 1 SD: 1.08 (1.01, 1.15) and 1.08 (1.02, 1.15), respectively]. These latter associations of BF% and BMI velocities with childhood hepatic fat were attenuated to the null when adjusted for participant-specific intercepts at birth. CONCLUSIONS: Our findings suggest that a smaller birth weight, combined with faster adiposity accretion in the first 5 y, predicts higher hepatic fat in early childhood. Strategies aiming to promote healthy body composition early in life may be critical for pediatric NAFLD prevention.This study was registered voluntarily at clinicaltrials.gov as NCT02273297.
Subject(s)
Non-alcoholic Fatty Liver Disease , Anthropometry , Birth Weight , Body Composition , Body Mass Index , Child, Preschool , Female , Humans , Infant , Infant, Newborn , Obesity , Plethysmography , PregnancyABSTRACT
The objective of the study was to investigate whether adverse and benevolent childhood experiences were associated with trajectories of sleep quality throughout pregnancy. The study was conducted at obstetrics and gynecology clinics in the Rocky Mountain region of the USA. The participants of the study were pregnant individuals (N = 164). Sleep quality was measured with the Pittsburgh Sleep Quality Index at three gestational time points, and adverse childhood experiences (ACEs) and benevolent childhood experiences (BCEs) were assessed once. Multilevel models were conducted to examine the trajectory of sleep quality across gestation in relation to ACEs and BCEs. Sleep quality was similar in early to mid-pregnancy, with a worsening of sleep quality late in pregnancy, following a quadratic trajectory. Higher levels of ACEs predicted poorer prenatal sleep quality (b = 0.36, SE = 0.13, p = .004) throughout pregnancy, while higher levels of BCEs predicted better sleep quality (b = -0.60, SE = 0.17, p < .001) throughout pregnancy. Examination of ACEs subtypes revealed that childhood maltreatment predicted poor sleep quality (b = 0.66, SE = 0.18, p < .001), while childhood household dysfunction was not significantly associated (b = 0.33, SE = 0.21, p = .11). Associations remained after covarying for socioeconomic status and current stressful life events. Both adverse and benevolent childhood experiences predict sleep health during pregnancy. Prevention and intervention strategies targeting resilience and sleep quality during pregnancy should be implemented to promote prenatal health and well-being.
ABSTRACT
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.
Subject(s)
Mental Recall , Nutrition Assessment , Diet , Diet Records , Eating , Energy Intake , Humans , Photography , Reproducibility of ResultsABSTRACT
OBJECTIVE: Adiposity, particularly visceral adipose tissue (VAT), predicts adverse cardiovascular risk factor profiles in children as well as adults. Although endogenous sex steroids likely influence VAT in adults, such an association has not been established in youth. The association between childhood and adolescent sex steroids with adiposity, specifically VAT, was examined before and after adjustment for other hormone changes. METHODS: These analyses examined longitudinal associations between sex steroids (testosterone, estradiol, dehydroepiandrosterone [DHEA]) and magnetic resonance imaging assessments of VAT in 418 children, 49% of whom were non-White, at approximately 10 years old at Visit 1 (V1) and 17 years old at Visit 2 (V2). Linear mixed effects models adjusted for maternal education, household income, child caloric intake, physical activity, fasting insulin and leptin, and hepatic fat fraction. Differences in associations by race and pubertal stage were also assessed. RESULTS: At V1, mean body mass index (BMI) for boys was 19.1 (4.7) kg/m2 and for girls was 18.5 (4.1) kg/m2. At V2, mean BMI for boys was 23.7 (5.5) kg/m2 and for girls was 23.6 (5.7) kg/m2. For each ng/dl (0.035 nmol/L) increase in testosterone at V1, there was a 0.25 cm2 increase in concurrent and future VAT in non-White (p = 0.04) but not White girls (p = 0.78). Higher levels of testosterone and DHEA at V1 were associated with greater concurrent and future VAT at V2. These associations were consistent regardless of pubertal stage. In boys, higher testosterone predicted higher future VAT but lower concurrent VAT. Estradiol and DHEA did not predict future VAT in boys. In girls, DHEA predicted future subcutaneous adipose tissue (SAT), and no sex steroids predicted future SAT in boys. CONCLUSIONS: Testosterone levels predict VAT in boys and girls, and DHEA predicts VAT in girls, even after adjustment for other hormone changes.
ABSTRACT
OBJECTIVE: The metabolic phenotype of youth-onset type 2 diabetes (T2D) differs from that of adult-onset T2D, but little is known about genetic contributions. We aimed to evaluate the association between a T2D genetic risk score (GRS) and traits related to glucose-insulin homeostasis among healthy youth. RESEARCH DESIGN AND METHODS: We used data from 356 youth (mean age 16.7 years; 50% female) in the Exploring Perinatal Outcomes Among Children (EPOCH) cohort to calculate a standardized weighted GRS based on 271 single nucleotide polymorphisms associated with T2D in adults. We used linear regression to assess associations of the GRS with log-transformed fasting glucose, 2-h glucose, HOMA of insulin resistance (HOMA-IR), oral disposition index, and insulinogenic index adjusted for age, sex, BMI z score, in utero exposure to maternal diabetes, and genetic principal components. We also evaluated effect modification by BMI z score, in utero exposure to maternal diabetes, and ethnicity. RESULTS: Higher weighted GRS was associated with lower oral disposition index (ß = -0.11; 95% CI -0.19, -0.02) and insulinogenic index (ß = -0.08; 95% CI -0.17, -0.001), but not with fasting glucose (ß = 0.01; 95% CI -0.01, 0.02), 2-h glucose (ß = 0.03; 95% CI -0.0004, 0.06), or HOMA-IR (ß = 0.02; 95% CI -0.04, 0.07). BMI z score and in utero exposure to maternal diabetes increased the effect of the GRS on glucose levels. CONCLUSIONS: Our results suggest that T2D genetic risk factors established in adults are relevant to glucose-insulin homeostasis in youth and that maintaining a healthy weight may be particularly important for youth with high genetic risk of T2D.
Subject(s)
Diabetes Mellitus, Type 2 , Insulin Resistance , Adolescent , Blood Glucose , Child , Diabetes Mellitus, Type 2/epidemiology , Diabetes Mellitus, Type 2/genetics , Female , Glucose , Homeostasis , Humans , Insulin , Insulin Resistance/genetics , Male , Phenotype , Pregnancy , Risk FactorsABSTRACT
OBJECTIVES: To explore the longitudinal association of neonatal adiposity (fat mass percentage) with BMI trajectories and childhood overweight and obesity from ages 2 to 6 years. METHODS: We studied 979 children from the Healthy Start cohort. Air displacement plethysmography was used to estimate fat mass percentage. Child weight and recumbent length or standing height were abstracted from medical records. Overweight and obesity were defined as BMI levels ≥85th percentile for age and sex. Mixed-effects models were used to examine the association between neonatal fat mass percentage and BMI trajectories from age 2 to 6 years. We tested for effect modification by sex, race and/or ethnicity, and breastfeeding duration. We estimated the proportion of children classified as overweight or obese at specific levels of neonatal fat mass percentage (mean ± SD). RESULTS: The mean neonatal adiposity level was 9.1% ± 4.0%. Child BMI levels differed by neonatal adiposity. Each SD increase in neonatal adiposity resulted in a 0.12 higher overall BMI level between ages 2 to 6 years (95% confidence interval: 0.03 to 0.20; P < .01), and this association was not modified by offspring sex, race and/or ethnicity, or breastfeeding duration. Increasing neonatal adiposity was associated with an increasing proportion of childhood overweight and obesity by age 5 years (P = .02). CONCLUSIONS: We provide novel evidence that higher neonatal adiposity is significantly associated with higher overall BMI levels and an increased likelihood of overweight or obesity from ages 2 to 6 years. Because various prenatal exposures may specifically influence offspring fat accretion, neonatal adiposity may be a useful surrogate end point for prenatal interventions aimed at reducing future childhood overweight and obesity.