Can adult polygenic scores improve prediction of body mass index in childhood?

BACKGROUND/OBJECTIVES: Modelling genetic pre-disposition may identify children at risk of obesity. However, most polygenic scores (PGSs) have been derived in adults, and lack validation during childhood. This study compared the utility of existing large-scale adult-derived PGSs to predict common anthropometric traits (body mass index (BMI), waist circumference, and body fat) in children and adults, and examined whether childhood BMI prediction could be improved by combining PGSs and non-genetic factors (maternal and earlier child BMI). SUBJECTS/METHODS: Participants (n = 1365 children, and n = 2094 adults made up of their parents) were drawn from the Longitudinal Study of Australian Children. Children were weighed and measured every two years from 0-1 to 12-13 years, and adults were measured or self-reported measurements were obtained concurrently (average analysed). Participants were genotyped from blood or oral samples, and PGSs were derived based on published genome-wide association studies. We used linear regression to compare the relative utility of these PGSs to predict their respective traits at different ages. RESULTS: BMI PGSs explained up to 12% of child BMI z-score variance in 10-13 year olds, compared with up to 15% in adults. PGSs for waist circumference and body fat explained less variance (up to 8%). An interaction between BMI PGSs and puberty (p = 0.001-0.002) suggests the effect of some variants may differ across the life course. Individual BMI measures across childhood predicted 10-60% of the variance in BMI at 12-13 years, and maternal BMI and BMI PGS each added 1-9% above this. CONCLUSION: Adult-derived PGSs for BMI, particularly those derived by modelling between-variant interactions, may be useful for predicting BMI during adolescence with similar accuracy to that obtained in adulthood. The level of precision presented here to predict BMI during childhood may be relevant to public health, but is likely to be less useful for individual clinical purposes.

Household income and maternal education in early childhood and risk of overweight and obesity in late childhood: Findings from seven birth cohort studies in six high-income countries.

BACKGROUND/OBJECTIVES: This study analysed the relationship between early childhood socioeconomic status (SES) measured by maternal education and household income and the subsequent development of childhood overweight and obesity. SUBJECTS/METHODS: Data from seven population-representative prospective child cohorts in six high-income countries: United Kingdom, Australia, the Netherlands, Canada (one national cohort and one from the province of Quebec), USA, Sweden. Children were included at birth or within the first 2 years of life. Pooled estimates relate to a total of N = 26,565 included children. Overweight and obesity were defined using International Obesity Task Force (IOTF) cut-offs and measured in late childhood (8-11 years). Risk ratios (RRs) and pooled risk estimates were adjusted for potential confounders (maternal age, ethnicity, child sex). Slope Indexes of Inequality (SII) were estimated to quantify absolute inequality for maternal education and household income. RESULTS: Prevalence ranged from 15.0% overweight and 2.4% obese in the Swedish cohort to 37.6% overweight and 15.8% obese in the US cohort. Overall, across cohorts, social gradients were observed for risk of obesity for both low maternal education (pooled RR: 2.99, 95% CI: 2.07, 4.31) and low household income (pooled RR: 2.69, 95% CI: 1.68, 4.30); between-cohort heterogeneity ranged from negligible to moderate (p: 0.300 to < 0.001). The association between RRs of obesity by income was lowest in Sweden than in other cohorts. CONCLUSIONS: There was a social gradient by maternal education on the risk of childhood obesity in all included cohorts. The SES associations measured by income were more heterogeneous and differed between Sweden versus the other national cohorts; these findings may be attributable to policy differences, including preschool policies, maternity leave, a ban on advertising to children, and universal free school meals.

Synthesizing Core Outcome Sets for outcomes research in cohort studies: a systematic review.

BACKGROUND: Life course studies are designed to "collect once, use multiple times" for observational and, increasingly, interventional research. Core Outcome Sets (COS) are minimum sets developed for clinical trials by multi-stakeholder consensus methodologies. We aimed to synthesize published COS that might guide outcomes selection for early life cohorts with an interventional focus. METHODS: We searched PubMed, Medline, COMET, and CROWN for COS published before January 2021 relevant to four life stages (pregnancy, newborns, children <8 years, and parents (adults aged 18-50 years)). We synthesized core outcomes into overarching constructs. RESULTS: From 46 COS we synthesized 414 core outcomes into 118 constructs. "Quality of life", "adverse events", "medication use", "hospitalization", and "mortality" were consistent across all stages. For pregnancy, common constructs included "preterm birth", "delivery mode", "pre-eclampsia", "gestational weight gain", "gestational diabetes", and "hemorrhage"; for newborns, "birthweight", "small for gestational age", "neurological damage", and "morbidity" and "infection/sepsis"; for pediatrics, "pain", "gastrointestinal morbidity", "growth/weight", "breastfeeding", "feeding problems", "hearing", "neurodevelopmental morbidity", and "social development"; and for adults, "disease burden", "mental health", "neurological function/stroke", and "cardiovascular health/morbidity". CONCLUSION: This COS synthesis generated outcome constructs that are of high value to stakeholders (participants, health providers, services), relevant to life course research, and could position cohorts for trial capabilities. IMPACT: We synthesized existing Core Outcome Sets as a transparent methodology that could prioritize outcomes for lifecourse cohorts with an interventional focus. "Quality of life", "adverse events", "medication use", "hospitalization", and "mortality" are important outcomes across pregnancy, newborns, childhood, and early-to-mid-adulthood (the age range relevant to parents). Other common outcomes (such as "birthweight", "cognitive function/ability", "psychological health") are also highly relevant to lifecourse research. This synthesis could assist new early life cohorts to pre-select outcomes that are of high value to stakeholders (participants, health providers, services), are relevant to lifecourse research, and could position them for future trials and interventional capability.

Diet quality trajectories and cardiovascular phenotypes/metabolic syndrome risk by 11-12 years.

OBJECTIVE: To investigate associations between early-life diet trajectories and preclinical cardiovascular phenotypes and metabolic risk by age 12 years. METHODS: Participants were 1861 children (51% male) from the Longitudinal Study of Australian Children. At five biennial waves from 2-3 to 10-11 years: Every 2 years from 2006 to 2014, diet quality scores were collected from brief 24-h parent/self-reported dietary recalls and then classified using group-based trajectory modeling as 'never healthy' (7%), 'becoming less healthy' (17%), 'moderately healthy' (21%), and 'always healthy' (56%). At 11-12 years: During children's physical health Child Health CheckPoint (2015-2016), we measured cardiovascular functional (resting heart rate, blood pressure, pulse wave velocity, carotid elasticity/distensibility) and structural (carotid intima-media thickness, retinal microvasculature) phenotypes, and metabolic risk score (composite of body mass index z-score, systolic blood pressure, high-density lipoproteins cholesterol, triglycerides, and glucose). Associations were estimated using linear regression models (n = 1100-1800) adjusted for age, sex, and socioeconomic position. RESULTS: Compared to 'always healthy', the 'never healthy' trajectory had higher resting heart rate (2.6 bpm, 95% CI 0.4, 4.7) and metabolic risk score (0.23, 95% CI 0.01, 0.45), and lower arterial elasticity (-0.3% per 10 mmHg, 95% CI -0.6, -0.1) and distensibility (-1.2%, 95% CI -1.9, -0.5) (all effect sizes 0.3-0.4). Heart rate, distensibility, and diastolic blood pressure were progressively poorer for less healthy diet trajectories (linear trends p ≤ 0.02). Effects for systolic blood pressure, pulse wave velocity, and structural phenotypes were less evident. CONCLUSIONS: Children following the least healthy diet trajectory had poorer functional cardiovascular phenotypes and metabolic syndrome risk, including higher resting heart rate, one of the strongest precursors of all-cause mortality. Structural phenotypes were not associated with diet trajectories, suggesting the window to prevent permanent changes remains open to at least late childhood.

Maximizing Participant Engagement, Participation, and Retention in Cohort Studies Using Digital Methods: Rapid Review to Inform the Next Generation of Very Large Birth Cohorts.

BACKGROUND: Many current research needs can only be addressed using very large cohorts. In such studies, traditional one-on-one phone, face-to-face, or paper-based engagement may not be feasible. The only realistic mechanism for maintaining engagement and participation at this scale is via digital methods. Given the substantial investment being made into very large birth cohort studies, evidence for optimal methods of participant engagement, participation, and retention over sustained periods without in-person contact from researchers is paramount. OBJECTIVE: This study aims to provide an overview of systematic reviews and meta-analyses evaluating alternative strategies for maximizing participant engagement and retention rates in large-scale studies using digital methods. METHODS: We used a rapid review method by searching PubMed and Ovid MEDLINE databases from January 2012 to December 2019. Studies evaluating at least 1 e-engagement, participation, or retention strategy were eligible. Articles were screened for relevance based on preset inclusion and exclusion criteria. The methodological quality of the included reviews was assessed using the AMSTAR-2 (Assessing the Methodological Quality of Systematic Reviews 2) measurement tool, and a narrative synthesis of the data was conducted. RESULTS: The literature search yielded 19 eligible reviews. Overall, 63% (n=12) of these reviews reported on the effectiveness of e-engagement or participation promotion strategies. These evaluations were generally not conducted within very large observational digital cohorts. Most of the contributing reviews included multipurpose cohort studies (with both observational and interventional elements) conducted in clinical and research settings. Email or SMS text message reminders, SMS text messages or voice notifications, and incentives were the most commonly used design features to engage and retain participants. For parental outcomes, engagement-facilitation interventions influenced uptake and behavior change, including video feedback, goal setting, and intensive human facilitation and support. Participant-stated preferences for content included new knowledge, reminders, solutions, and suggestions about health issues presented in a clear, short, and personalized way. Perinatal and postpartum women valued self-monitoring and personalized feedback. Digital reminders and multiple SMS text messages were specific strategies that were found to increase adherence to medication and clinic attendance, respectively. CONCLUSIONS: This review adds to the growing literature evaluating methods to optimize engagement and participation that may apply to large-scale studies using digital methods; it is promising that most e-engagement and participation promotion strategies appear to be effective. However, these reviews canvassed relatively few strategies, suggesting that few alternative strategies have been experimentally evaluated. The reviews also revealed a dearth of experimental evidence generated within very large observational digital cohort studies, which may reflect the small number of such studies worldwide. Thus, very large studies may need to proactively build in experimental opportunities to test engagement and retention approaches to enhance the success of their own and other large digital contact studies.

Child and adult snack food intake in response to manipulated pre-packaged snack item quantity/variety and snack box size: a population-based randomized trial.

OBJECTIVES: Snacks contribute to overconsumption of energy-dense foods and thence obesity. Previous studies in this area are limited by self-reported data and small samples. In a large population-based cohort of parent-child dyads, we investigated how modification of pre-packaged snack food, i.e. (a) item quantity and variety, and (b) dishware (boxed container) size affected intake. METHODS: Design: Randomized trial nested within the cross-sectional Child Health CheckPoint of the Longitudinal Study of Australian Children, clustered by day of visit. SAMPLE: 1299 11-12 year olds, 1274 parents. EXPOSURE: 2 × 2 manipulation of snack box container size and item quantity/variety: (1) small box, few items, (2) large box, few items, (3) small box, more items, (4) large box, more items. PROCEDURE: Participants received a snack box during a 15 min break within their 3.5 h visit; any snacks remaining were weighed. OUTCOMES: Consumed quantity (grams) and energy intake (kilojoules). ANALYSES: Unadjusted linear regression. RESULTS: Children who were offered a greater quantity and variety of snack items consumed considerably more energy and a slightly higher food mass (main effect for energy intake: 349 kJ, 95% CI 282-416, standardized mean difference (effect size) 0.66; main effect for mass: 10 g, 95% CI 3-17, effect size 0.17). In contrast, manipulating box size had little effect on child consumption, and neither box size nor quantity/variety of items consistently affected adults' consumption. CONCLUSION: In children, reducing the number and variety of snack food items available may be a more fruitful intervention than focusing on container or dishware size. Effects observed among adults were small, although we could not exclude social desirability bias in adults aware of observation.

Bidirectional associations between diet and body composition measures from 2 to 15 years: Longitudinal Study of Australian Children.

This study investigates how dietary patterns and scores are associated with subsequent BMI and waist:height ratio (WHtR), and how BMI and WHtR are associated with subsequent dietary patterns or scores, from 2-3 to 10-11 and 4-5 to 14-15 years of age. In the Longitudinal Study of Australian Children, height, weight and waist circumference were measured biennially in children, yielding BMI z-score and WHtR. Parents, latterly children, reported frequency of child consumption of 12-16 food/drink items during the previous 24 h. At each wave, we empirically derived dietary patterns using factor analyses, and dietary scores based on the 2013 Australian Dietary Guidelines. We used structural-equation modelling to investigate cross-lagged associations (n 1972-2882) between diet and body composition measures in univariable and multivariable analyses. Dietary scores/patterns did not consistently predict WHtR and BMI z-score in the next wave, nor did BMI z-score and WHtR consistently predict diet in the next wave. The few associations seen were weak and often in the opposite direction to that hypothesised. The largest effect, associated with each standard deviation increase in BMI in wave 5 of the K cohort (age 12-13 years), was a 0·06 standard deviation estimated mean increase in dietary score (higher quality diet) in the subsequent wave (95 % CI 0·02, 0·11, P=0·003). Associations between dietary patterns/scores and body composition were not strongly evident in either direction. Better quantitative childhood dietary tools feasible for large-scale administration are needed to quantify how dietary patterns, energy intake and anthropometry co-develop.

Parental health behaviour predictors of childhood and adolescent dietary trajectories.

OBJECTIVE: To determine which parental health behaviours early in childhood most strongly predict whole-of-childhood dietary trajectories. DESIGN: Population-based Longitudinal Study of Australian Children (LSAC, waves 1-6; 2004-2014). Exposures were parents' fruit/vegetable consumption, alcohol, smoking and physical activity at child age 0-1 years (B Cohort) or 4-5 years (K Cohort). Outcomes, from repeated biennial short diet diaries, were group-based trajectories of (i) dietary scores and empirically derived patterns of (ii) healthful and (iii) unhealthful foods consumed, spanning ages 2-3 to 10-11 years (B Cohort) and 4-5 to 14-15 years (K Cohort). We investigated associations of baseline parental health behaviours with child dietary trajectories using multinomial logistic regression. SETTING: Australian homes. SUBJECTS: Of children, 4443 (87·0 %) from the B Cohort and 4620 (92·7 %) from the K Cohort were included in all trajectories. Multivariable analyses included 2719 to 2905 children and both parents. RESULTS: Children whose primary caregiver reported the lowest fruit/vegetable consumption had markedly higher odds of belonging to the least healthy score and pattern trajectories (K Cohort: OR=8·7, 95 % CI 5·0, 15·1 and OR=8·4, 95 % CI 4·8, 14·7, respectively); associations were weaker (K Cohort: OR=2·3, 95 % CI 1·0, 5·2) for the unhealthiest pattern trajectory. Secondary caregiver fruit/vegetable associations were smaller and inconsistent. Parental alcohol, smoking and physical activity were not predictive in multivariable analyses. Results were largely replicated for the B Cohort. CONCLUSIONS: Low primary caregiver fruit/vegetable consumption increased nearly ninefold the odds of children being in the lowest intake of healthy, but only weakly predicted unhealthy, food trajectories. Healthy and unhealthy food intake may have different determinants.

Health-care costs of underweight, overweight and obesity: Australian population-based study.

AIM: Child health varies with body mass index (BMI), but it is unknown by what age or how much this attracts additional population health-care costs. We aimed to determine the (1) cross-sectional relationships between BMI and costs across the first decade of life and (2) in longitudinal analyses, whether costs increase with duration of underweight or obesity. PARTICIPANTS: Baby (n = 4230) and Kindergarten (n = 4543) cohorts in the nationally representative Longitudinal Study of Australian Children. OUTCOME: Medicare Benefits Scheme (including all general practitioner plus a large proportion of paediatrician visits) plus prescription medication costs to federal government from birth to sixth (Baby cohort) and fourth to tenth (Kindergarten cohort) birthdays. PREDICTOR: biennial BMI measurements over the same period. RESULTS: Among Australian children under 10 years of age, 5-6% were underweight, 11-18% overweight and 5-6% obese. Excess costs with low and high BMI became evident from age 4-5 years, with normal weight accruing the least, obesity the most, and underweight and overweight intermediate costs. Relative to overall between-child variation, these excess costs per child were very modest, with a maximum of $94 per year at age 4-5 years. Nonetheless, this projects to a substantial cost to government of approximately $13 million per annum for all Australian children aged less than 10 years. CONCLUSIONS: Substantial excess population costs provide further economic justification for promoting healthy body weight. However, obese children's low individual excess health-care costs mean that effective treatments are likely to increase short-term costs to the public health purse during childhood.

The challenges of real-world implementation of web-based shared care software: the HopSCOTCH Shared-Care Obesity Trial in Children.

BACKGROUND: E-health initiatives hold promise to improve shared-care models of health care. In 2008-2011 we developed and trialled web-based software to facilitate a randomised trial of a shared-care approach for childhood obesity involving General Practitioners (GPs) working with tertiary specialists. We describe the software's development, implementation and evaluation, and make recommendations for future e-health initiatives. The web-based software was designed with the goals of allowing both GPs and specialists to communicate and review patient progress; integrating with existing GP software; and supporting GPs to deliver the structured intervention. Specifically, we aimed to highlight the challenges inherent in this process, and report on the extent to which the software ultimately met its implementation and user aims. METHODS: The study was conducted at the Royal Children's Hospital and 22 general practices across Melbourne, Australia. Participants comprised 30 GPs delivering the shared-care intervention. Outcomes included the following. (1) GPs' pre-specified software requirements: transcribed from two focus groups and analysed for themes using content analysis. (2) Software implementation and performance based on the experience of the research team and GPs. (3) GP users' evaluation collected via questionnaire. (4) Software usage collected via GP questionnaire and qualified through visual inspection of the software meta-data. RESULTS: Software implementation posed difficult and at times disabling technological barriers (e.g. out-dated hardware, poor internet connections). The software's speed and inability to seamlessly link with day-to-day software was a source of considerable frustration. Overall, GPs rated software usability as poor, although most (68%) felt that the structure and functionality of the software was useful. Recommendations for future e-health initiatives include thorough scoping of IT systems and server speed, testing across diverse environments, automated pre-requisite checks and upgrades of processors/memory where necessary, and user-created usernames and passwords. CONCLUSIONS: GPs are willing to embrace novel technologies to support their practice. However, implementation remains challenging mainly for technical reasons, and this precludes further evaluation of potential user-specific barriers. These findings could inform future e-health ventures into shared-care, and highlight the need for an appropriate infrastructure. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN126080000553.

Social gradients in ADHD by household income and maternal education exposure during early childhood: Findings from birth cohort studies across six countries.

OBJECTIVE: This study aimed to examine social gradients in ADHD during late childhood (age 9-11 years) using absolute and relative relationships with socioeconomic status exposure (household income, maternal education) during early childhood (<5 years) in seven cohorts from six industrialised countries (UK, Australia, Canada, The Netherlands, USA, Sweden). METHODS: Secondary analyses were conducted for each birth cohort. Risk ratios, pooled risk estimates, and absolute inequality, measured by the Slope Index of Inequality (SII), were estimated to quantify social gradients in ADHD during late childhood by household income and maternal education measured during early childhood. Estimates were adjusted for child sex, mother age at birth, mother ethnicity, and multiple births. FINDINGS: All cohorts demonstrated social gradients by household income and maternal education in early childhood, except for maternal education in Quebec. Pooled risk estimates, relating to 44,925 children, yielded expected gradients (income: low 1.83(CI 1.38,2.41), middle 1.42(1.13,1.79), high (reference); maternal education: low 2.13(1.39,3.25), middle 1.42(1.13,1.79)). Estimates of absolute inequality using SII showed that the largest differences in ADHD prevalence between the highest and lowest levels of maternal education were observed in Australia (4% lower) and Sweden (3% lower); for household income, the largest differences were observed in Quebec (6% lower) and Canada (all provinces: 5% lower). CONCLUSION: Findings indicate that children in families with high household income or maternal education are less likely to have ADHD at age 9-11. Absolute inequality, in combination with relative inequality, provides a more complete account of the socioeconomic status and ADHD relationship in different high-income countries. While the study design precludes causal inference, the linear relation between early childhood social circumstances and later ADHD suggests a potential role for policies that promote high levels of education, especially among women, and adequate levels of household income over children's early years in reducing risk of later ADHD.

Sleep problems, internalizing and externalizing symptoms, and domains of health-related quality of life: bidirectional associations from early childhood to early adolescence.

STUDY OBJECTIVES: To examine longitudinal, bidirectional associations among behavioral sleep problems, internalizing and externalizing symptoms, and domains of health-related quality of life (HRQoL) from early childhood to adolescence in a population sample of Australian children. METHOD: Data were drawn from the Longitudinal Study of Australian Children, a national prospective cohort study with 4983 children participating in the Kindergarten cohort. Data were collected when children were aged 4-5, 6-7, 8-9, 10-11, and 12-13 years. At each study wave, the primary parent (97% mothers) reported on behavioral child sleep problems, internalizing and externalizing symptoms, and HRQoL domains (psychosocial and physical). Cross-lagged structural equation models were used to evaluate bidirectional associations. RESULTS: At nearly every age, behavioral sleep problems were associated with worse subsequent psychosocial and physical HRQoL. Despite bidirectional associations between mental health and HRQoL at many waves, HRQoL domains more strongly predicted later internalizing symptoms, while externalizing symptoms more strongly predicted later HRQoL. Many of the bidirectional associations among sleep, mental health, and HRQoL were found earlier in childhood. CONCLUSIONS: Behavioral sleep problems may forecast later HRQoL psychosocial and physical impairments. Attending to both sleep problems and HRQoL could prevent the progression of internalizing conditions, while a focus on externalizing concerns could prevent the worsening of these symptoms, sleep problems, and HRQoL, particularly during the transition to school.

Trimethylamine N-oxide (TMAO) Is not Associated with Cardiometabolic Phenotypes and Inflammatory Markers in Children and Adults.

BACKGROUND: Trimethylamine N-oxide (TMAO) is a diet- and microbiome-derived metabolite and a proposed biomarker of adverse cardiometabolic outcomes. TMAO studies have mainly been conducted in individuals with cardiometabolic disease, and studies in population-derived samples are limited. OBJECTIVE: We aimed to investigate the associations between plasma TMAO concentrations and its precursors [carnitine, choline, betaine, and dimethylglycine (DMG)] with metabolic syndrome (MetS) scores, preclinical cardiovascular phenotypes, and inflammatory biomarkers (i.e. high-sensitivity C-reactive protein and serum glycoprotein acetyls) in a population-derived cohort of children and their parents. METHODS: The concentrations of TMAO and its precursors were quantified using UHPLC coupled with tandem MS (UHPLC/MS-MS) in 1166 children (mean age 11 y ± 0.5 y, 51% female) and 1324 adults (44 y ± 5.1 y, 87% female) participating in The Growing Up in Australia's Child Health CheckPoint Study. We developed multivariable fractional polynomial models to analyze associations between TMAO, its precursors, MetS (adjusted for sex and age), and cardiovascular phenotypes (adjusted for sex, age, BMI, household income, and the urinary albumin to creatinine ratio). Pearson's correlations were computed to identify associations between TMAO, its precursors, and inflammatory biomarkers. RESULTS: The concentrations of TMAO precursors, but not TMAO itself, were associated with MetS, cardiovascular phenotypes, and inflammatory biomarkers in children and adults. CONCLUSIONS: TMAO precursors, but not TMAO itself, were associated with adverse cardiometabolic and inflammatory phenotypes in children and adults. TMAO precursor concentrations may better reflect cardiovascular health and inflammatory status within the wider population. Replication in other population settings and mechanistic studies are warranted.

Population epidemiology and concordance for plasma amino acids and precursors in 11-12-year-old children and their parents.

Amino acid (AA) concentrations are influenced by both exogenous (e.g. diet, lifestyle) and endogenous factors (e.g. genetic, transcriptomic, epigenetic, and metabolomic). Fasting plasma AA profiles in adulthood are predictive of diabetes risk over periods of up to 12 years. Data on AA profiles in cross-generational cohorts, including individuals from shared gene-environment settings are scarce, but would allow the identification of the contribution of heritable and environmental factors characterising the levels of circulating AAs. This study aimed to investigate parent-child (familial dyad) concordance, absolute differences between generations- (children versus adults), age- (in adults: 28-71 years), and sex-dependent differences in plasma AA concentrations. Plasma AA concentrations were measured by UHPLC/MS-MS in 1166 children [mean (SD) age 11 (0.5) years, 51% female] and 1324 of their parents [44 (5.1) years, 87% female]. AA concentrations were variably concordant between parents and their children (5-41% of variability explained). Most AA concentrations were higher in adults than children, except for the non-essential AAs arginine, aspartic acid, glutamine, hydroxy-proline, proline, and serine. Male adults and children typically had higher AA concentrations than females. The exceptions were alanine, glutamine, glycine, hydroxy-proline, serine, and threonine in girls; and glycine and serine in women. Age, sex, and shared familial factors are important determinants of plasma AA concentrations.

Plasma Trimethylamine N-Oxide and Its Precursors: Population Epidemiology, Parent-Child Concordance, and Associations with Reported Dietary Intake in 11- to 12-Year-Old Children and Their Parents.

BACKGROUND: Trimethylamine N-oxide (TMAO) is a microbiome- and diet-derived metabolite implicated in adverse cardiovascular outcomes. To date, studies of plasma TMAO concentrations have largely focused on individuals with metabolic disease. As such, data on TMAO concentrations in population settings and parent-child dyads are lacking. OBJECTIVES: This study aimed to investigate parent-child concordance, age, and sex effects on plasma concentrations of TMAO and its precursors [l-carnitine, choline, betaine, and dimethylglycine (DMG)]. Associations between concentrations of TMAO and its precursors and self-reported dietary intakes of animal protein (i.e., red meat, meat products, chicken, fish, milk products, and cheese) and fast-food meals were also investigated. METHODS: A total of 1166 children (mean ± SD age: 11 ± 0.5 y, 51% female) and 1324 parents (mean ± SD age: 44 ± 5.1 y, 87% female) had a biomedical assessment as part of Growing Up in Australia's Child Health Checkpoint. Plasma TMAO and precursor concentrations were quantified using ultra-high-pressure LC coupled with tandem MS. RESULTS: Familial dyads significantly contributed to plasma TMAO and precursor concentrations (P < 0.0001), explaining 37% of variance for TMAO concentrations. Least-square mean ± SE plasma TMAO was lower in children (0.79 ± 0.02 µM on the log-scale) than in adults (1.22 ± 0.02 µM). By contrast, children's betaine (40.30 ± 0.34 µM) and DMG concentrations (1.02 ± 0.01 µM on the log-scale) were higher than adults' betaine (37.50 ± 0.32 µM) and DMG concentrations (0.80 ± 0.01 µM) (P < 0.0001). Mean values of all metabolites, except adult TMAO, were higher in males than in females (P < 0.001). Greater reported intake of red meat and fish was associated with higher TMAO concentrations in both children [estimates (95% CIs) for red meat: 0.06 (0.01, 0.10); fish: 0.11 (0.06, 0.17)] and adults [red meat: 0.13 (0.08, 0.17); meat products: 0.07 (0.03, 0.12); and fish: 0.09 (0.04, 0.14)]. CONCLUSIONS: Age, sex, and shared family factors, including diet, contribute to variation in plasma concentrations of TMAO and its precursors.

Body Mass Index From Early to Late Childhood and Cardiometabolic Measurements at 11 to 12 Years.

OBJECTIVES: To examine how overweight and obesity at specific ages and overall BMI growth patterns throughout childhood predict cardiometabolic phenotypes at 11 to 12 years. METHODS: In a population-based sample of 5107 infants, BMI was measured every 2 years between ages 2 to 3 and 10 to 11 years. We identified 5 BMI trajectories using growth curve models. At ages 11 to 12 years, 1811 children completed assessments for metabolic syndrome risk scores, carotid-femoral pulse wave velocity, and carotid intima-media thickness. Multivariable regression models were used to estimate associations, adjusted for potential confounders (eg, age, sex, smoking exposure, and small for gestational age). RESULTS: Overweight and obesity from early childhood onward were strongly associated with higher cardiometabolic risk at 11 to 12 years of age. At age 6 to 7 years, compared with those with a healthy weight, children with overweight had higher metabolic syndrome risk scores by 0.23 SD units (95% confidence interval 0.05 to 0.41) and with obesity by 0.76 SD units (0.51-1.01), with associations almost doubling by age 10 to 11 years. Obese (but not overweight) children had higher outcome pulse wave velocity (0.64-0.73 SD units) from ages 6 to 7 years and slightly higher outcome carotid intima-media thickness (0.20-0.30 SD units) at all ages. Cumulative exposure to high BMI from 2 to 3 years of age carried the greatest cardiometabolic risk, with a gradient of risk across trajectories. CONCLUSIONS: High early-childhood BMI is already silently associated with the development of cardiometabolic risk by 11 to 12 years, highlighting the urgent need for effective action to reduce overweight and obesity in early childhood.

Population health bio-phenotypes in 11-12 year old children and their midlife parents: Growing Up in Australia's Child Health CheckPoint.

In an ambitious undertaking, Growing Up in Australia's Child Health CheckPoint streamlined and implemented wide-ranging population phenotypes and biosamples relevant to non-communicable diseases in nearly 1900 parent-child dyads throughout Australia at child aged 11-12 years. This BMJ Open Special Issue describes the methodology, epidemiology and parent-child concordance of 14 of these phenotypes, spanning cardiovascular, respiratory, bone, kidney, hearing and language, body composition, metabolic profiles, telomere length, sleep, physical activity, snack choice and health-related quality of life. The Special Issue also includes a cohort summary and study methodology paper.

Child Health CheckPoint: cohort summary and methodology of a physical health and biospecimen module for the Longitudinal Study of Australian Children.

OBJECTIVES: 'Growing Up in Australia: The Longitudinal Study of Australian Children' (LSAC) is Australia's only nationally representative children's longitudinal study, focusing on social, economic, physical and cultural impacts on health, learning, social and cognitive development. LSAC's first decade collected wide-ranging repeated psychosocial and administrative data; here, we describe the Child Health CheckPoint, LSAC's dedicated biophysical module. DESIGN, SETTING AND PARTICIPANTS: LSAC recruited a cross-sequential sample of 5107 infants aged 0-1 year and a sample of 4983 children aged 4-5 years in 2004, since completing seven biennial visits. CheckPoint was a cross-sectional wave that travelled Australia in 2015-2016 to reach LSAC's younger cohort at ages 11-12 years between LSAC waves 6 and 7. Parent-child pairs participated in comprehensive assessments at 15 Assessment Centres nationwide or, if unable to attend, a shorter home visit. MEASURES: CheckPoint's intergenerational, multidimensional measures were prioritised to show meaningful variation within normal ranges and capture non-communicable disease (NCD) phenotype precursors. These included anthropometry, physical activity, fitness, time use, vision, hearing, and cardiovascular, respiratory and bone health. Biospecimens included blood, saliva, buccal swabs (also from second parent), urine, hair and toenails. The epidemiology and parent-child concordance of many measures are described in separate papers. RESULTS: 1874 (54% of eligible) parent-child pairs and 1051 second parents participated. Participants' geographical distribution mirrored the broader Australian population; however, mean socioeconomic position and parental education were higher and fewer reported non-English-speaking or Indigenous backgrounds. Application of survey weights partially mitigates that the achieved sample is less population representative than previous waves of LSAC due to non-random attrition. Completeness was uniformly high for phenotypic data (>92% of eligible), biospecimens (74%-97%) and consent (genetic analyses 98%, accessing neonatal blood spots 97%, sharing 96%). CONCLUSIONS: CheckPoint enriches LSAC to study how NCDs develop at the molecular and phenotypic levels before overt disease emerges, and clarify the underlying dimensionality of health in childhood and mid-adulthood.

Body composition: population epidemiology and concordance in Australian children aged 11-12 years and their parents.

OBJECTIVES: Overweight and obesity remain at historically high levels, cluster within families and are established risk factors for multiple diseases. We describe the epidemiology and cross-generational concordance of body composition among Australian children aged 11-12 years and their parents. DESIGN: The population-based cross-sectional Child Health CheckPoint study, nested within the Longitudinal Study of Australian Children (LSAC). SETTING: Assessment centres in seven major Australian cities and eight regional cities, or home visits; February 2015-March 2016. PARTICIPANTS: Of all participating CheckPoint families (n=1874), body composition data were available for 1872 children (49% girls) and 1852 parents (mean age 43.7 years; 88% mothers), including 1830 biological parent-child pairs. MEASURES: Height, weight, body mass index (BMI), waist circumference and waist-to-height ratio for all participants; body fat and fat-free mass by four-limb bioimpedence analysis (BIA) at assessment centres, or body fat percentage by two-limb BIA at home visits. Analysis: parent-child concordance was assessed using (i) Pearson's correlation coefficients, and (ii) partial correlation coefficients adjusted for age, sex and socioeconomic disadvantage. Survey weights and methods accounted for LSAC's complex sample design. RESULTS: 20.7% of children were overweight and 6.2% obese, as were 33.5% and 31.6% of parents. Boys and girls showed similar distributions for all body composition measures but, despite similar BMI and waist-to-height ratio, mothers had higher proportions of total and truncal fat than fathers. Parent-child partial correlations were greatest for height (0.37, 95% CI 0.33 to 0.42). Other anthropometric and fat/lean measures showed strikingly similar partial correlations, ranging from 0.25 (95% CI 0.20 to 0.29) for waist circumference to 0.30 (95% CI 0.25 to 0.34) for fat-free percentage. Whole-sample and sex-specific percentile values are provided for all measures. CONCLUSIONS: Excess adiposity remains prevalent in Australian children and parents. Moderate cross-generational concordance across all measures of leanness and adiposity is already evident by late childhood.

Hearing, speech reception, vocabulary and language: population epidemiology and concordance in Australian children aged 11 to 12 years and their parents.

OBJECTIVES: To describe the epidemiology and parent-child concordance of hearing, speech reception, vocabulary and language in Australian parent-child dyads at child age 11 to 12 years. DESIGN: Population-based cross-sectional study (Child Health CheckPoint) nested within the Longitudinal Study of Australian Children. SETTING: Assessment centres in seven Australian cities and eight regional towns or home visits around Australia, February 2015 to March 2016. PARTICIPANTS: Of all participating CheckPoint families (n=1874), 1516 children (50% female) and 1520 parents (87% mothers, mean age 43.8 years) undertook at least one of four measurements of hearing and language. OUTCOME MEASURES: Hearing threshold (better ear mean of 1, 2 and 4 kHz) from pure-tone audiometry, speech reception threshold, receptive vocabulary, expressive and receptive languages using a sentence repetition task. Parent-child concordance was examined using Pearson's correlation coefficients and adjusted linear regression models. Survey weights and methods accounted for Longitudinal Study of Australian Children's complex sampling and stratification. RESULTS: Children had a similar speech reception threshold to parents (children mean -14.3, SD 2.4; parents -14.9, SD 3.2 dB) but better hearing acuity (children 8.3, SD 6.3; parents 13.4, SD 7.0 decibels hearing level). Standardised sentence repetition scores were similar (children 9.8, SD 2.9; parents 9.1, SD 3.3) but, as expected, parents had superior receptive vocabularies. Parent-child correlations were higher for the cognitively-based language measures (vocabulary 0.31, 95% CI 0.26 to 0.36; sentence repetition 0.29, 95% CI 0.24 to 0.34) than the auditory measures (hearing 0.18, 95% CI 0.13 to 0.23; speech reception threshold 0.18, 95% CI 0.13 to 0.22). Mother-child and father-child concordances were similar for all measures. CONCLUSIONS: We provide population reference values for multiple measures spanning auditory and verbal communication systems in children and mid-life adults. Concordance values aligned with previous twin studies and offspring studies in adults, in keeping with polygenic heritability that is modest for audition but around 60% for language by late childhood.