Search

In many jurisdictions, routine medical care was reduced in response to the COVID-19 pandemic. The objective of this study was to determine whether the frequency of on-time routine childhood vaccinations among children age 0-2 years was lower following the COVID-19 declaration of emergency in Ontario, Canada, on March 17, 2020, compared to prior to the pandemic.We conducted a longitudinal cohort study of healthy children aged 0-2 years participating in the TARGet Kids! primary care research network in Toronto, Canada. A logistic mixed effects regression model was used to determine odds ratios (ORs) for delayed vaccination ( 30 days vs. ≤ 30 days from the recommended date) before and after the COVID-19 declaration of emergency, adjusted for confounding variables. A Cox proportional hazards model was used to explore the relationship between the declaration of emergency and time to vaccination.Among 1277 children, the proportion of on-time vaccinations was 81.8% prior to the COVID-19 declaration of emergency and 62.1% after (p 0.001). The odds of delayed vaccination increased (odds ratio = 3.77, 95% CI: 2.86-4.96), and the hazard of administration of recommended vaccinations decreased after the declaration of emergency (hazard ratio = 0.75, 95% CI: 0.60-0.92). The median vaccination delay time was 5 days (95% CI: 4-5 days) prior to the declaration of emergency and 17 days (95% CI: 12-22 days) after.The frequency of on-time routine childhood vaccinations was lower during the first wave of the COVID-19 pandemic. Sustained delays in routine vaccinations may lead to an increase in rates of vaccine-preventable diseases.RéSUMé: OBJECTIFS: Dans plusieurs juridictions, les soins médicaux systématiques étaient réduits à cause de la pandémie de COVID-19. L’objectif de cette étude était de déterminer si la fréquence de donner les vaccinations systématiques aux enfants de l’âge de 0 à 2 ans était réduite en conséquence de la déclaration d’urgence de COVID-19 en Ontario, Canada dès le 17 mars 2020, comparer avec la fréquence avant la pandémie. MéTHODES: Nous avons mené une étude de cohorte longitudinale des enfants en bonne santé âgés de 0 à 2 ans qui participent dans le réseau de recherche en soins primaires TARGet Kids! à Toronto, Canada. Un modèle de régression logistique à effets mixtes était utilisé pour déterminer le rapport de cotes (RC) pour les vaccinations retardées ( 30 jours c. ≤ 30 jours de la date recommandée) et était équilibré pour les variables confondantes. Le modèle à risques proportionnels de Cox était utilisé pour examiner le lien entre la déclaration d’urgence et le temps jusqu’à la vaccination. RéSULTATS: Parmi 1 277 enfants, la proportion de vaccination à l’heure était 81,8 % avant la déclaration d’urgence de COVID-19 et 62,1 % après (p 0,001). La possibilité de vaccination retardée était augmentée (RC = 3,77; IC95% : 2,86–4,96), et le taux d’administration recommandé pour les vaccinations était réduit après la déclaration d’urgence (ratio de hasard = 0,75; IC95% : 0,60–0,92). Le médian temps de retard pour les vaccinations était 5 jours (IC95% : 4–5 jours) avant la déclaration d’urgence et 17 jours (IC95% : 12–22 jours) après. CONCLUSION: La fréquence de vaccinations systématiques aux enfants à l’heure était inférieure pendant la première vague de la pandémie COVID-19. Des retards soutenus pour recevoir les vaccinations systématiques peuvent entrainer une augmentation des taux de maladies évitables par la vaccination.

Background The effect of being born late preterm (34-36 weeks gestation) on cardiometabolic outcomes across the life course is unclear. Objectives To systematically review the association between being born late preterm (spontaneous or indicated), compared to the term and cardiometabolic outcomes in children and adults. Data sources EMBASE(Ovid), MEDLINE(Ovid), CINAHL. Study selection and data extraction Observational studies up to July 2021 were included. Study characteristics, gestational age, cardiometabolic outcomes, risk ratios (RRs), odds ratios (ORs), hazard ratios (HRs), mean differences and 95% confidence intervals (CIs) were extracted. Synthesis We pooled converted RRs using random-effects meta-analyses for diabetes, hypertension, ischemic heart disease (IHD) and body mass index (BMI) with subgroups for children and adults. The risk of bias was assessed using the Newcastle-Ottawa scale and certainty of the evidence was assessed using the grading of recommendations, assessment, development and evaluation (GRADE) approach. Results Forty-one studies were included (41,203,468 total participants; median: 5.0% late preterm). Late preterm birth was associated with increased diabetes (RR 1.24, 95% CI 1.17, 1.32; nine studies; n = 6,056,511; incidence 0.9%; I2 51%; low certainty) and hypertension (RR 1.21, 95% CI 1.13, 1.30; 11 studies; n = 3,983,141; incidence 3.4%; I2 64%; low certainty) in children and adults combined. Late preterm birth was associated with decreased BMI z-scores in children (standard mean difference -0.38; 95% CI -0.67, -0.09; five studies; n = 32,602; proportion late preterm 8.3%; I2 96%; very low certainty). There was insufficient evidence that late preterm birth was associated with increased IHD risk in adults (HR 1.20, 95% CI 0.89, 1.62; four studies; n = 2,706,806; incidence 0.3%; I2 87%; very low certainty). Conclusions Late preterm birth was associated with an increased risk of diabetes and hypertension. The certainty of the evidence was low or very low. Inconsistencies in late preterm and term definitions, confounding variables and outcome age limited the comparability of studies.

Elevated body mass index (BMI) and rapid growth in early childhood are important predictors of obesity risk. The association between maternal preconception BMI and child growth rates is unclear.To assess the association between measured maternal preconception BMI and child age- and sex- standardized WHO BMI z-score (zBMI) growth rates and mean zBMI, in children aged 0-10 years old.A longitudinal cohort study was conducted with children (n = 499) enrolled in The Applied Research Group for Kids (TARGet Kids!) primary care practice-based research cohort. Maternal BMI was measured during the preconception period, defined as the 2 years prior to pregnancy. Repeated measures of child weight and height were obtained between 0 and 10 years of age. Linear mixed models were used to evaluate the association between maternal BMI and child zBMI growth rates and mean zBMI.Maternal preconception BMI was associated with child zBMI growth rate during some growth periods, with the strongest association from age 0 to 4 months; a 5 kg/m2 higher maternal BMI was associated with 0.031 zBMI SD unit/mo higher growth rate (p = 0.004), and 0.186 SD unit higher mean child zBMI (p = 0.0002).Maternal preconception BMI was associated with growth rate and mean zBMI in early childhood. The preconception period may be an important target for health interventions to promote healthy child growth rate and weight outcomes.

BackgroundChildhood obesity is a major public health concern. This study evaluated the independent and joint associations of family-level income, neighbourhood-level income and neighbourhood deprivation, in relation to child obesity.MethodsA cross-sectional study was conducted in children ≤12 years of age from TARGet Kids! primary care network (Greater Toronto Area, 2013–2019). Parent-reported family income was compared with median neighbourhood income and neighbourhood deprivation measured using the Ontario Marginalization Index. Children’s height and weight were measured and body mass index (BMI) z-scores (zBMI) were calculated. ORs and 95% CIs were estimated for the three exposure variables separately using multilevel multinomial logistic regression models with zBMI categories as the outcome, adjusting in model 1 for age, sex, ethnicity and number of family members and in model 2 adding family income. A joint measure was derived combining income and deprivation measures.ResultsA total of 5962 children were included. Low family income (Q1 vs Q5: OR=4.69, 95% CI 2.65 to 8.29), low neighbourhood income (Q1 vs Q5: OR=2.18, 95% CI 1.33 to 3.58) and high neighbourhood deprivation (Q1 vs Q5: OR=2.45, 95% CI 1.52 to 3.95) were each associated with increased OR of child obesity. However, after adjustment for family income, the association for both neighbourhood income (OR=1.39, 95% CI 0.82 to 2.34) and deprivation (OR=1.56, 95% CI 0.94 to 2.58) and obesity was attenuated. Children from low-income families living in low-income or high deprivation neighbourhoods had higher OR of obesity.ConclusionChild obesity was independently associated with low family-level income and a joint measure suggests that neighbourhood also matters. Socioeconomic inequalities at both individual and neighbourhood levels should be addressed in childhood obesity interventions.

BACKGROUND International guidelines recommend children aged 9 months to 2 years consume whole (3.25%) fat cow's milk, and children older than age 2 years consume reduced (0.1-2%) fat cow's milk to prevent obesity. The objective of this study was to evaluate the longitudinal relationship between cow's milk fat (0.1-3.25%) intake and body mass index z-score (zBMI) in childhood. We hypothesized that higher cow's milk fat intake was associated with lower zBMI. METHODS A prospective cohort study of children aged 9 months to 8 years was conducted through the TARGet Kids! primary care research network. The exposure was cow's milk fat consumption (skim (0.1%), 1%, 2%, whole (3.25%)), measured by parental report. The outcome was zBMI. Height and weight were measured by trained research assistants and zBMI was determined according to WHO growth standards. A linear mixed effects model and logistic generalized estimating equations were used to determine the longitudinal association between cow's milk fat intake and child zBMI. RESULTS Among children aged 9 months to 8 years (N = 7467; 4699 of whom had repeated measures), each 1% increase in cow's milk fat consumed was associated with a 0.05 lower zBMI score (95% CI -0.07 to -0.03, p

Introduction:The authors aimed to examine the association between meeting the integrative movement behavior guidelines (physical activity, screen viewing, and sleep) and cardiometabolic risk (CMR) factors in young children.Methods:In this cross-sectional study, physical activity, screen viewing, and sleep were assessed using parent-reported data. The 24-Hour Movement Guidelines for the Early Years (0–4 y) were defined as 180 minutes of physical activity/day (of which ≥60 min should be moderate-to-vigorous intensity), ≤1 hour of screen viewing/day, and 10 to 13 hours of sleep/night. Waist circumference, glucose, high-density lipoprotein cholesterol, triglycerides, and systolic blood pressure were measured in a clinical setting by trained staff. A total CMR score and individual CMR factors served as primary and secondary outcomes, respectively.Results:Of the 767 participants (3–4 y), 26.4% met none of the guideline’s recommendations, whereas 41.3%, 33.1%, and 10.6% of the sample met 1, 2, or all 3 recommendations, respectively. The number of recommendations met was not associated with the total CMR score or individual CMR factors (P > .05), with the exceptions of high-density lipoprotein (odds ratio = 1.61; 95% confidence interval, 1.11 to 2.33;P = .01).Conclusion:Meeting the 24-Hour Movement Guidelines in early childhood was not associated with overall CMR, but was associated with favorable cholesterol outcomes.

Emotional problems such as anxiety and low mood have been associated with sleep problems in children. The study's objectives were to 1) assess the association between sleep duration and internalizing symptoms (anxiety and low mood) in children aged 5-12 years (y), and 2) evaluate whether insufficient sleep according to the National Sleep Foundation (NSF) guidelines is associated with internalizing symptoms.A cross-sectional study of N =796 children aged 5-12y, recruited from primary care physicians' offices in Toronto, Canada was conducted through the TARGet Kids! research network. Using linear regression, we investigated 1) the cross-sectional association between parent reported 24-hour sleep duration (hours) and parent reported symptoms using the Strengths and Difficulties Questionnaire (SDQ), controlling for child age, sex, family income, maternal education, family composition, and standardized body-mass index (zBMI). The analysis was repeated using insufficient sleep per NSF guideline as the independent variable.Sleep duration was inversely associated with internalizing symptoms, B estimate = -0.33 (95%CI -0.57, -0.07), p=0.012. Twenty-eight (14%) children aged 5 y, and 36 (6%) of those aged 6-12y, experienced insufficient sleep. There was a trend toward association between insufficient sleep and internalizing symptoms, B estimate = 0.64 (-0.09, 1.38), p=0.086.The relationship between insufficient sleep and internalizing symptoms among children requires further elucidation. Children who show internalizing symptoms may benefit from interventions supporting sleep.Les problèmes émotionnels comme l’anxiété et l’humeur sombre ont été associés à des problèmes de sommeil chez les enfants. Les objectifs de la présente étude étaient de 1) évaluer l‘association entre la durée du sommeil et les symptômes d’internalisation (anxiété et humeur sombre) chez les enfants de 5 à 12 ans (a), et 2) évaluer si le sommeil insuffisant selon les lignes directrices de la Fondation nationale du sommeil (FNS) est associé aux symptômes internalisants.Une étude transversale de N =796 enfants de 5 à 12 ans recrutés dans les bureaux de médecins de soins de première ligne à Toronto, Canada, a été menée dans le réseau de recherche TARGet Kids! À l’aide de la régression linéaire, nous avons investigué 1) l’association transversale entre la durée du sommeil (en heures) sur 24 heures rapportée par les parents et les symptômes rapportés par les parents à l’aide du questionnaire des forces et difficultés (QFD), en contrôlant pour l’âge de l’enfant, le sexe, le revenu familial, l’éducation maternelle, la composition de la famille et l’indice de masse corporelle normalisé (IMCn). L’analyse a été répétée avec le sommeil insuffisant selon les lignes directrices de la (FNS) comme variable indépendante.La durée du sommeil était inversement associée à des symptômes d’internalisation, estimation B = −0,33 (IC à 95 % −0,57 à-0,07), p = 0,012. Vingt-huit (14 %) enfants âgés de 5 ans, et 36 (6 %) de ceux âgés de 6 à 12 ans avaient un sommeil insuffisant. Il y avait une tendance à l’association entre le sommeil insuffisant et les symptômes d’internalisation; estimation B = 0,64 (−0,09, 1,38), p = 0,086.La relation entre le sommeil insuffisant et les symptômes d’internalisation chez les enfants nécessite des éclaircissements. Les enfants souffrant de symptômes d’internalisation peuvent bénéficier d’interventions favorisant le sommeil.

To investigate whether social determinants of health (SDOH) are predictive of adherence to public health preventive measures and to describe changes in adherence over time among parents and children.A longitudinal study was conducted in children aged 0-10 years and their parents through the TARGet Kids! COVID-19 Study in the Greater Toronto Area, Canada (April-July 2020). This study included 335 parents (2108 observations) and 416 children (2632 observations). Parents completed weekly questionnaires on health, family functioning, socio-demographics, and public health practices. The outcome was adherence to public health preventive measures measured separately for parents and children. Marginal log-binomial models were fitted using repeated measures of the outcome and predictors.Unemployment (RR 0.67, 95% CI: 0.47, 0.97), apartment living (RR 0.72, 95% CI: 0.53, 0.99), and essential worker in the household (RR 0.74, 95% CI: 0.55, 1.00) were associated with decreased likelihood of adherence among parents; however, no associations were observed for other SDOH, including family income and ethnicity. Furthermore, there was no strong evidence that SDOH were associated with child adherence. The mean number of days/week that parents and children adhered at the start of the study was 6.45 (SD = 0.93) and 6.59 (SD = 0.86), respectively, and this decreased to 5.80 (SD = 1.12) and 5.84 (SD = 1.23) by study end. Children consistently had greater adherence than parents.SDOH were predictive of adherence to public health preventive measures among parents but less so in children among our sample of relatively affluent urban families. Adherence was high among parents and children but decreased over time. Equitable approaches to support the implementation of public health guidelines may improve adherence.RéSUMé: OBJECTIFS: Voir si les déterminants sociaux de la santé (DSS) sont des prédicteurs de conformité aux mesures de prévention sanitaire et décrire l’évolution de la conformité des parents et des enfants au fil du temps. MéTHODE: Nous avons mené une étude longitudinale auprès d’enfants de 0 à 10 ans et de leurs parents dans le cadre de l’étude sur la COVID-19 menée par le groupe de recherche TARGet Kids! dans la région du Grand Toronto, au Canada (avril à juillet 2020). L’étude incluait 335 parents (2 108 observations) et 416 enfants (2 632 observations). Les parents ont rempli un questionnaire hebdomadaire sur la santé, le fonctionnement familial, le profil sociodémographique et les pratiques sanitaires. Le résultat était la conformité aux mesures de prévention sanitaire, mesurée séparément pour les parents et les enfants. Des modèles log-binomiaux marginaux ont été ajustés à l’aide de mesures répétées du résultat et des prédicteurs. RéSULTATS: Le chômage (RR 0,67, IC de 95 % : 0,47, 0,97), la vie en appartement (RR 0,72, IC de 95 % : 0,53, 0,99) et la présence d’un travailleur essentiel dans le ménage (RR 0,74, IC de 95 % : 0,55, 1,00) étaient associés à une probabilité réduite de conformité chez les parents; par contre, aucune association n’a été observée pour les autres DSS, dont le revenu familial et l’ethnicité. Il n’y avait pas non plus d’indications convaincantes d’une association entre les DSS et la conformité chez les enfants. Le nombre moyen de jours/semaine où parents et enfants s’étaient conformés aux mesures de prévention sanitaire au début de l’étude était de 6,45 (S = 0,93) et de 6,59 (S = 0,86), respectivement; ce nombre a diminué pour atteindre 5,80 (S = 1,12) et 5,84 (S = 1,23) à la fin de l’étude. La conformité des enfants était uniformément supérieure à celle des parents. CONCLUSION: Dans notre échantillon de familles urbaines relativement aisées, les DSS étaient des prédicteurs de conformité aux mesures de prévention sanitaire chez les parents, mais dans une moindre mesure chez les enfants. La conformité était élevée chez les parents comme chez les enfants, mais elle a diminué avec le temps. Des stratégies équitables d’appui à l’application des directives sanitaires pourraient améliorer le respect de ces directives.

Background Most studies on children evaluate longitudinal growth as an important health indicator. Different methods have been used to detect growth patterns across childhood, but with no comparison between them to evaluate result consistency. We explored the variation in growth patterns as detected by different clustering and latent class modelling techniques. Moreover, we investigated how the characteristics/features (e.g. slope, tempo, velocity) of longitudinal growth influence pattern detection. Methods We studied 1134 children from The Applied Research Group for Kids cohort with longitudinal-growth measurements [height, weight, body mass index (BMI)] available from birth until 12 years of age. Growth patterns were identified by latent class mixed models (LCMM) and time-series clustering (TSC) using various algorithms and distance measures. Time-invariant features were extracted from all growth measures. A random forest classifier was used to predict the identified growth patterns for each growth measure using the extracted features. Results Overall, 72 TSC configurations were tested. For BMI, we identified three growth patterns by both TSC and LCMM. The clustering agreement was 58% between LCMM and TS clusters, whereas it varied between 30.8% and 93.3% within the TSC configurations. The extracted features (n = 67) predicted the identified patterns for each growth measure with accuracy of 82%–89%. Specific feature categories were identified as the most important predictors for patterns of all tested growth measures. Conclusion Growth-pattern detection is affected by the method employed. This can impact on comparisons across different populations or associations between growth patterns and health outcomes. Growth features can be reliably used as predictors of growth patterns.

Background While bariatric surgery has proven to be effective to achieve significant weight loss and short-term improvements in both physical and mental (HRQoL), little is known about the factors associated with long-term decline in mental HRQoL after bariatric surgery. Objective To examine differences in physical and mental HRQoL trajectories in a bariatric patient population 3 years after bariatric surgery and examine associated sociodemographic, weight, and mental health factors. Setting A Canadian academic bariatric care center. Methods A group-based trajectory model was used to examine physical and mental HRQoL trajectories 3 years after bariatric surgery. In a prospective cohort bariatric sample (n = 2270), demographic factors, body mass index, binge eating symptoms, anxiety symptoms (Generalized Anxiety Disorder-7), depressive symptoms (Patient Health Questionnaire-9), and physical and mental HRQoL (Short-form health survey-36 (SF-36)), were measured at baseline, 6 months, 1, 2, and 3 years respectively. The effect of time-varying covariates (body mass index, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7) were investigated to examine effects on physical and mental HRQoL trajectories. Results Five distinct trajectories described changes in (n = 1939 of 2270) individuals’ physical HRQoL outcomes (SF-36–physical health component summary score) and five other trajectories described changes in mental HRQoL (SF-36–mental health component summary score) outcomes from baseline to 3 years postsurgery. The group-based distribution for the 5 physical HRQoL trajectories were as follows: (1) low baseline-stable low (5.8%); (2) low baseline-moderate rise (12%); (3) low baseline-stable high (41.1%); (4) high baseline-stable high (33.2%); and (5) moderate baseline-decline (7.9%). The 5 mental HRQoL trajectories were as follows: (1) low baseline-slow decline (10%); (2) low baseline-stable high (25%); (3) high baseline-unstable rise (12%); (4) high baseline-stable high (48.9%); and (5) high baseline-transient decline (4.1%). Compared with physical HRQoL, mental HRQoL trajectories were not associated with changes in body mass index, yet strongly correlated with changes in binge eating symptoms, Generalized Anxiety Disorder-7, and Patient Health Questionnaire measures at all time points. Conclusion This study demonstrates distinct patterns in physical and mental HRQoL trajectories after bariatric surgery. The decline in mental HRQoL trajectories was more heterogeneous and associated with several psychosocial predictors that may be useful to guide risk prediction of long-term physical and mental HRQoL outcomes postbariatric surgery.

Background Group‐based trajectory modeling has been applied to identify distinct trajectories of growth across the life course. Objectives of this study were to describe the methodological approaches for group‐based modeling of growth across the life course and to summarize outcomes across studies. Methods A scoping review with a systematic search of Medline, EMBASE, CINAL, and Web of Science was conducted. Studies that used a group‐based procedure to identify trajectories on any statistical software were included. Data were extracted on trajectory methodology, measures of growth, and association with outcomes. Results A total of 59 studies were included, and most were published from 2013 to 2020. Body mass index was the most common measure of growth (n = 43). The median number of identified trajectories was 4 (range: 2–9). PROC TRAJ in SAS was used by 33 studies, other procedures used include TRAJ in STATA, lcmm in R, and Mplus. Most studies evaluated associations between growth trajectories and chronic disease outcomes (n = 22). Conclusions Group‐based trajectory modeling of growth in adults is emerging in epidemiologic research, with four distinct trajectories observed somewhat consistently from all studies. Understanding life course growth trajectories may provide further insight for population health interventions.

OBJECTIVE This study examined the relative impact of breastfeeding duration and timing of solids introduction on BMI z score (BMIz) trajectory in early childhood. METHODS This study conducted secondary analyses of data from the Melbourne Infant Feeding, Activity and Nutrition Trial (InFANT) Program (N = 542), a prospective cohort study with data collected at birth and 3, 9, 18, 42, and 60 months. Linear spline multilevel models were performed. RESULTS Differential growth rates were observed from birth to 3 months and from 9 to 18 months by breastfeeding duration (≥ 6 vs.

The primary objective of this study was to examine the relationships between vegetarian diet and growth, micronutrient stores, and serum lipids among healthy children. Secondary objectives included exploring whether cow's milk consumption or age modified these relationships.A longitudinal cohort study of children aged 6 months to 8 years who participated in the TARGet Kids! cohort study. Linear mixed-effect modeling was used to evaluate the relationships between vegetarian diet and BMI z-score (zBMI), height-for-age z-score, serum ferritin, 25-hydroxyvitamin D, and serum lipids. Generalized estimating equation modeling was used to explore weight status categories. Possible effect modification by age and cow's milk consumption was examined.A total of 8907 children, including 248 vegetarian at baseline, participated. Mean age at baseline was 2.2 years (SD 1.5). There was no evidence of an association between vegetarian diet and zBMI, height-for-age z-score, serum ferritin, 25-hydroxyvitamin D, or serum lipids. Children with vegetarian diet had higher odds of underweight (zBMI-2) (odds ratio 1.87, 95% confidence interval 1.19 to 2.96; P = .007) but no association with overweight or obesity was found. Cow's milk consumption was associated with higher nonhigh-density lipoprotein cholesterol (P = .03), total cholesterol (P = .04), and low-density lipoprotein cholesterol (P = .02) among children with vegetarian diet. However, children with and without vegetarian diet who consumed the recommended 2 cups of cow's milk per day had similar serum lipids.Evidence of clinically meaningful differences in growth or biochemical measures of nutrition for children with vegetarian diet was not found. However, vegetarian diet was associated with higher odds of underweight.

ObjectivesChildren from low-income households are at an increased risk of social, behavioural and physical health problems. Prior studies have generally relied on dichotomous outcome measures. However, inequities may exist along the range of outcome distribution. Our objective was to examine differences in distribution of three child health outcomes by income categories (high vs low): body mass index (BMI), behaviour difficulties and development.Design and settingThis was a cross-sectional study using data from a primary care-based research network with sites in three Canadian cities, and 15 practices enrolling participants.Participants, independent variable and outcomesThe independent variable was annual household income, dichotomised at the median income for Toronto (ResultsWe included data from 1628 (zBMI), 649 (SDQ) and 1405 (ITC) children. Children with lower family income had a higher risk distribution for all outcomes. For all outcomes, thecounterfactual distribution, which represented the distribution of children with lower-income who were assigned the predictor profile of the higher-income group, was more favourable than their observed distributions.ConclusionComparing the distributions of child health outcomes and understanding different risk profiles for children from higher-income and lower-income groups can offer a deeper understanding of inequities in child health outcomes. These methods may offer an approach that can be implemented in larger datasets to inform future interventions.

Background Family history is a significant risk factor for bipolar disorders (BD), but the magnitude of risk varies considerably between individuals within and across families. Accurate risk estimation may increase motivation to reduce modifiable risk exposures and identify individuals appropriate for monitoring over the peak risk period. Our objective was to develop and independently replicate an individual risk calculator for bipolar spectrum disorders among the offspring of BD parents using data collected in routine clinical practice. Methods Data from the longitudinal Canadian High-Risk Offspring cohort study collected from 1996 to 2020 informed the development of a 5 and 10-year risk calculator using parametric time-to-event models with a cure fraction and a generalized gamma distribution. The calculator was then externally validated using data from the Lausanne–Geneva High-Risk Offspring cohort study collected from 1996 to 2020. A time-varying C-index by age in years was used to estimate the probability that the model correctly classified risk. Bias corrected estimates and 95% confidence limits were derived using a jackknife resampling approach. Findings The primary outcome was age of onset of a major mood disorder. The risk calculator was most accurate at classifying risk in mid to late adolescence in the Canadian cohort (n = 285), and a similar pattern was replicated in the Swiss cohort (n = 128). Specifically, the time-varying C-index indicated that there was approximately a 70% chance that the model would correctly predict which of two 15-year-olds would be more likely to develop the outcome in the future. External validation within a smaller Swiss cohort showed mixed results. Interpretation Findings suggest that this model may be a useful clinical tool in routine practice for improved individualized risk estimation of bipolar spectrum disorders among the adolescent offspring of a BD parent; however, risk estimation in younger high-risk offspring is less accurate, perhaps reflecting the evolving nature of psychopathology in early childhood. Based on external validation with a Swiss cohort, the risk calculator may not be as predictive in more heterogenous high-risk populations. Funding The Canadian High-Risk Study has been funded by consecutive operating grants from the Canadian Institutes for Health Research, currently CIHR PJT Grant 152796 he Lausanne-Geneva high-risk study was and is supported by five grants from the Swiss National Foundation (#3200–040,677, #32003B-105,969, #32003B-118,326, #3200–049,746 and #3200–061,974), three grants from the Swiss National Foundation for the National Centres of Competence in Research project “The Synaptic Bases of Mental Diseases” (#125,759, #158,776, and #51NF40 – 185,897), and a grant from GlaxoSmithKline Clinical Genetics.

Background Bipolar disorder onset peaks over early adulthood and confirmed family history is a robust risk factor. However, penetrance within families varies and most children of bipolar parents will not develop the illness. Individualized risk prediction would be helpful for identifying those young people most at risk and to inform targeted intervention. Using prospectively collected data from the Canadian Flourish High-risk Offspring cohort study available in routine practice, we explored the use of a neural network, known as the Partial Logistic Artificial Neural Network (PLANN) to predict the time to diagnosis of major mood disorders in 1, 3 and 5-year intervals. Results Overall, for predictive performance, PLANN outperformed the more traditional discrete survival model for 3-year and 5-year predictions. PLANN was better able to discriminate or rank individuals based on their risk of developing a major mood disorder, better able to predict the probability of developing a major mood disorder and better able to identify individuals who would be diagnosed in future time intervals. The average AUC achieved by PLANN for 5-year prediction was 0.74, which indicates good discrimination. Conclusions This evaluation of PLANN is a useful step in the investigation of using neural networks as tools in the prediction of mood disorders in at-risk individuals and the potential that neural networks have in this field. Future research is needed to replicate these findings in a separate high-risk offspring sample.

Bipolar disorder is highly heritable and typically onsets in late adolescence or early adulthood. Evidence suggests that immune activation may be a mediating pathway between genetic predisposition and onset of mood disorders. Building on a prior study of mRNA and protein levels in high-risk offspring published in this Journal, we conducted a preliminary examination of methylation profiles in candidate immune genes from a subsample of well-characterized emergent adult (mean 20 years) offspring of bipolar parents from the Canadian Flourish high-risk cohort. Models were adjusted for variable age at DNA collection, sex and antidepressant and mood stabilizer use. On cross-sectional analysis, there was evidence of higher methylation rates for BDNF-1 in high-risk offspring affected (n = 27) and unaffected (n = 23) for mood disorder compared to controls (n = 24) and higher methylation rates in affected high-risk offspring for NR3C1 compared to controls. Longitudinal analyses (25 to 34 months) provided evidence of steeper decline in methylation rates in controls (n = 24) for NR3C1 compared to affected (n = 15) and unaffected (n = 11) high-risk offspring and for BDNF-2 compared to affected high-risk. There was insufficient evidence that changes in any of the candidate gene methylation rates were associated with illness recurrence in high-risk offspring. While preliminary, findings suggest that longitudinal investigation of epigenetic markers in well-characterized high-risk individuals over the peak period of risk may be informative to understand the emergence of bipolar disorder. Electronic supplementary material The online version of this article (10.1186/s40345-019-0152-1) contains supplementary material, which is available to authorized users.

Nutrition in early childhood is important for healthy growth and development. Achieving school readiness is considered one of the most important developmental milestones for young children.The purpose of this study is to determine if nutritional risk in early childhood is associated with school readiness in kindergarten.A prospective cohort study was conducted through The Applied Research Group for Kids (TARGet Kids!) primary care research network in Toronto, Canada, 2015-2020. Nutritional risk was measured (18 mo to 5 y) using validated parent-completed questionnaires called Nutrition Screening for Toddlers and Preschoolers (NutriSTEP). High nutritional risk was categorized as scores ≥21. School readiness was measured using the validated teacher-completed Early Developmental Instrument (EDI), which measures 5 developmental domains in kindergarten (2 y of schooling, ages 4-6 y, before they enter grade 1). Vulnerability indicates scores lower than a population-based cutoff at the 10th percentile on at least 1 domain. Multiple logistic and linear regression models were conducted adjusting for relevant confounders.The study included 896 children: 53% were male, 9% had high nutritional risk, and 17% were vulnerable on the EDI. A 1-SD increase in NutriSTEP total score was associated with 1.54 times increased odds of being vulnerable on the EDI among children in year 2 of kindergarten (P = 0.001). High nutritional risk cutoff was associated with 4.28 times increased odds of being vulnerable on the EDI among children in year 2 of kindergarten (P 0.001). NutriSTEP total score and high nutritional risk were associated with lower scores on all 5 EDI domains, with the strongest association observed for the domains of language and cognitive development and communication skills and general knowledge.Higher nutritional risk in early childhood is associated with lower school readiness in year 2 of kindergarten. Nutritional interventions early in life may offer opportunities to enhance school readiness. This trial was registered www.clinicaltrials.gov as NCT01869530.

Objective:To determine if nutritional risk in early childhood is associated with parent-reported school concerns.Design:A prospective cohort study conducted through the TARGet Kids! primary care research network (2011–2018). Nutritional risk was measured between 18 months and 5 years of age using validated parent-completed NutriSTEP® questionnaires with eating behaviour and dietary intake subscores (0 = lowest and 68 = highest total nutritional risk score). Parent-reported school concerns were measured at school age (4–10 years of age) and included: speech and language; learning; attention; behaviour; social relationships; physical coordination; fine motor coordination and self-help skills and independence. The primary outcome was any parent-reported school concerns, and individual school concerns were used as secondary outcomes. Multiple logistic regression models were conducted adjusting for clinically relevant confounders to assess the relationship between nutritional risk and school concerns.Setting:Toronto, Canada.Participants:Children aged 18 months to 10 years.Results:The study included 3655 children, 52 % were male, mean NutriSTEP® score was 14·4 (sd 6·4). Each 1 sd increase in NutriSTEP® total score was associated with a 1·18 times increased odds of school concerns (adj OR: 1·18, 95 % CI 1·07, 1·28, P = 0·0004), and high nutritional risk was associated with a 1·42 times increased odds of school concerns (adj OR: 1·42, 95 % CI 1·13, 1·78, P = 0·002).Conclusions:Nutritional risk in early childhood was associated with school concerns. Nutritional interventions in early childhood may reveal opportunities to enhance school outcomes.

Objective To evaluate the relationship between the timing of infant cereal introduction between 4 and 6 months of age and growth and dietary intake in later childhood. Study design A longitudinal cohort study was conducted among healthy children 0-10 years of age participating in The Applied Research Group for Kids cohort study between June 2008 and August 2019 in Toronto, Canada. Results Of 8943 children included, the mean (SD) age of infant cereal introduction was 5.7 (2.1) months. In the primary analysis, children who were introduced to infant cereal at 4 vs 6 months had 0.17 greater body mass index z score (95% CI 0.06-0.28; P = .002) and greater odds of obesity (OR 1.82; 95% CI 1.18-2.80; P = .006) at 10 years of age. In the secondary analysis, children who were introduced to infant cereal at 4 vs 6 months had 0.09 greater height-for-age z score (95% CI 0.04-0.15; P = .002) at 1 year of age, an association that was not observed at 5 or 10 years of age. Children who were introduced to infant cereal at 4 vs 6 months had greater nutrition risk which was primarily determined by a less-favorable eating behavior score at 18 months to 5 years of age (0.18 units higher; 95% CI 0.07-0.29; P = .001). Conclusions Introduction of infant cereal at 4 vs 6 months was associated with greater body mass index z score, greater odds of obesity, similar height-for-age z score, and less favorable eating behavior. These findings support recommendations for introducing solid food around 6 months of age.

The primary objective was to determine the association between public health preventive measures and children's outdoor time, sleep duration, and screen time during COVID-19.A cohort study using repeated measures of exposures and outcomes was conducted in healthy children (0 to 10 years) through The Applied Research Group for Kids (TARGet Kids!) COVID-19 Study of Children and Families in Toronto, Canada, between April 14 and July 15, 2020. Parents were asked to complete questionnaires about adherence to public health measures and children's health behaviours. The primary exposure was the average number of days that children practiced public health preventive measures per week. The three outcomes were children's outdoor time, total screen time, and sleep duration during COVID-19. Linear mixed-effects models were fitted using repeated measures of primary exposure and outcomes.This study included 554 observations from 265 children. The mean age of participants was 5.5 years, 47.5% were female and 71.6% had mothers of European ethnicity. Public health preventive measures were associated with shorter outdoor time (-17.2; 95% CI -22.07, -12.40; p0.001) and longer total screen time (11.3; 95% CI 3.88, 18.79; p = 0.003) during COVID-19. The association with outdoor time was stronger in younger children (5 years), and the associations with total screen time were stronger in females and in older children (≥5 years).Public health preventive measures during COVID-19 were associated with a negative impact on the health behaviours of Canadian children living in a large metropolitan area.RéSUMé: OBJECTIF: L’objectif principal était de déterminer la relation entre les mesures préventives de la santé publique et le temps passé en plein air, la durée du sommeil ainsi que le temps passé devant l’écran par les enfants pendant COVID-19. MéTHODES: Une étude de cohorte utilisant des mesures répétées des expositions et des effets a été menée chez des enfants en bonne santé (0 à 10 ans) par l’entremise de l’Étude COVID-19 sur les Enfants et Familles du Groupe de Recherche Appliquée pour les Enfants (TARGet Kids!) à Toronto, au Canada, entre le 14 avril et le 15 juillet 2020. Les parents ont été invités à remplir des questionnaires sur adhésion aux mesures préventives de la santé publique et les comportements de santé des enfants. La principale exposition était le nombre moyen de jours par semaine durant lesquels les enfants pratiquaient des mesures préventives de la santé publique. Les trois effets étaient le temps passé en plein air par les enfants, le temps total passé devant l’écran et la durée du sommeil pendant le COVID-19. Des modèles linéaires à effets mixtes ont été ajustés en utilisant des mesures répétées d’exposition primaire et des effets. RéSULTATS: Cette étude comprend 554 observations sur 265 enfants. L’âge moyen des participants était de 5,5 ans, 47,5 % étaient des femmes et 71,6 % avaient des mères d’origine européenne. Les mesures préventives de la santé publique ont été associées à un temps passé en plein air plus court (-17,2 ; IC 95% -22,07, -12,40; p0,001) et à un temps total devant l’écran plus long (11,3 ; IC 95% 3,88, 18,79; p = 0,003) pendant la COVID-19. La relation avec le temps passé en plein air était plus importante chez les jeunes enfants (5 ans), et les relations avec le temps total passé devant l’écran étaient plus importantes chez les enfants de sexe féminin et les enfants plus âgés (≥5 ans). CONCLUSION: Les mesures préventives de la santé publique prises lors de COVID-19 ont été associées à un impact négatif sur les comportements de santé des enfants canadiens vivant dans une grande région métropolitaine.

Background: Family history is a significant risk factor for bipolar disorders (BD), but the magnitude of risk varies considerably between individuals within and across families. Accurate risk estimation may increase motivation to reduce modifiable risk exposures and identify individuals appropriate for monitoring over the peak risk period. Our objective was to develop and independently replicate an individual risk calculator for major mood disorders among the offspring of BD parents using data collected in routine clinical practice. Methods: The longitudinal Canadian High-Risk Offspring cohort study was used to develop a 5 and 10-year risk calculator using parametric time-to-event models with a cure fraction and a generalized gamma distribution. The calculator was then externally validated using data from the Lausanne–Geneva High-Risk Offspring cohort study. A Time-varying C-index by age in years was used to estimate the probability that the model correctly classified risk. Bias corrected estimates and 95% confidence limits were derived using a jackknife resampling approach. Outcomes: The primary outcome was age of onset of a major mood disorder. The risk calculator was most accurate at classifying risk in mid to late adolescence in the Canadian cohort, and a similar pattern was replicated in the Swiss cohort. Specifically, the time-varying C-index indicated that there was approximately a 70% chance that the model would correctly predict which of two 15-year-olds would be more likely to develop a bipolar spectrum mood disorder in the future. Interpretation: Findings suggest that this model may be a useful clinical tool in routine practice for improved individualized risk estimation of bipolar spectrum disorders among the adolescent and offspring of a BD parent; however, accurate risk estimation in younger high-risk children is less precise reflecting the evolving nature of psychopathology at this early developmental stage. Funding: Funding: The Canadian High-Risk Study has been funded by consecutive operating grants from the Canadian Institutes for Health Research, currently CIHR PJT Grant 152976 The Lausanne-Geneva high-risk study was and is supported by five grants from the Swiss National Foundation (#3200-040677, #32003B-105969, #32003B-118326, #3200-049746 and #3200-061974), three grants from the Swiss National Foundation for the National Centres of Competence in Research project “The Synaptic Bases of Mental Diseases” (#125759, #158776, and #51NF40 – 185897), and a grant from GlaxoSmithKline Clinical Genetics. The funders had no involvement in any aspect of this study. Declaration of Interest: MISSING Ethical Approval: The two studies have been approved by respective research ethics boards at each site: the Ottawa Independent Research Ethics Board (Pro00011514), the Queens University Health Sciences and Affiliated Teaching Hospitals Research Ethics Board (PSIY-561-17) and the Ethics Committee for Clinical Research of the Canton de Vaud.

Background: Few studies have published mediation analyses to quantify the role concurrent BMI plays in the relationship between growth and cardiometabolic risk (CMR) outcomes. Methods: We used data...

Highlights • No evidence of an association between children’s parental-reported screen time and total cardiometabolic risk score. • Weak association between increased screen time and reduced HDL cholesterol in children. • No sex or age interactions detected between parental-reported screen time and cardiometabolic risk., Screen use has become a pervasive behaviour among children and has been linked to adverse health outcomes. The objective of this study was to examine the association between screen time and a comprehensive total cardiometabolic risk (CMR) score in school-aged children (7–12-years), as well as individual CMR factors. In this longitudinal study, screen time was measured over time (average duration of follow-up was 17.4 months) via parent-report. Anthropometric measurements, blood pressure, and biospecimens were collected over time and used to calculate CMR score [sum of age and sex standardized z-scores of systolic blood pressure (SBP), glucose, log-triglycerides, waist circumference (WC), and negative high-density lipoprotein cholesterol (HDL-c)/square-root of 5]. Generalized estimating equations (GEE) were used to examine the association between screen time and total CMR score as well as individual CMR factors. A total of 567 children with repeated measures were included. There was no evidence of an association between parent-reported child screen time and total CMR score (adjusted β = −0.01, 95% CI [−0.03, 0.005], 0.16). Screen time was inversely associated HDL-c (adjusted β = −0.008, 95% CI [−0.011, −0.005], p = 0.016), but there was no evidence that the other CMR components were associated with screen time. Among children 7–12 years, there was no evidence of an association between parent-reported child screen time and total CMR, but increased screen time was associated with slightly lower HDL-c. Research is needed to understand screen-related contextual factors which may be related to CMR factors.

Background Vegetarian diets are becoming increasingly popular among Canadians, yet few studies have evaluated the relationship between a vegetarian diet and childhood growth and nutritional status. Since vegetarian diets can be less energy dense and may have lower micronutrient content, we hypothesized that a vegetarian diet may affect childhood growth including lower adiposity and height, as well as lower micronutrient stores. Objectives The primary objective of this study was to evaluate the relationship between vegetarian diet and growth, including adiposity and height among healthy children 6 months to 10 years of age. Secondary objectives included the examination of the relationship between vegetarian diet and iron and vitamin D stores. We also explored whether cow’s milk intake or age modified the associations between vegetarian diet and growth, and micronutrient stores. Design/Methods This was a prospective cohort study of healthy children age 6 months to 10 years. The primary exposure was vegetarian diet measured by parent report. The primary outcome was BMI z-score. Secondary outcomes included height-for-age z-score, serum ferritin, and serum 25-hydroxyvitamin D. Anthropometric measures and venous blood samples were collected at health supervision visits by trained research assistants. Linear mixed effect modelling was used to determine the association between vegetarian diet, growth, and micronutrient stores. Results A total of 8912 children (n = 248 vegetarian) participated. In the adjusted models there was no evidence of an association between vegetarian diet and BMI z-score (p = 0.605, 95% CI: -0.06, 0.10), height-for-age z-score (p 0.057, 95% CI: -0.16, 0.002), serum ferritin (p = 0.768, 95% CI: -3.84, 2.84), or 25-hydroxyvitamin D (p = 0.204, 95% CI: -2.14, 0.46). The relationship between vegetarian diet and serum 25-hydroxyvitamin D was modified by child age. Volume of cow’s milk intake did not modify the relationships between vegetarian diet and BMI z-score, height-for-age z-score, serum ferritin, or 25-hydroxyvitamin D. In a secondary analysis, we examined adiposity through weight status categories and found children with a vegetarian diet had higher odds of being underweight (BMI z-score Conclusion In this prospective cohort study, evidence of an association between vegetarian diet and lower BMI z-score, height-for-age z-score, and micronutrient stores was not found. Our results suggest children with vegetarian diets had higher odds of being underweight. Future research is needed to evaluate dietary factors and patterns of children following vegetarian diets, especially those with an underweight weight status.

Background Income related inequities in child health are well-established, with children from lower income households showing increased risk of obesity, behavior problems, and delayed development. To facilitate clinical diagnosis, outcomes are conventionally measured in dichotomous terms. However, inequities may exist along the entire range of distribution, with implications for population health. Objectives Our primary objective was to examine differences in the distribution of three measures of child health by income: body mass index (BMI), behavior difficulties and development. Design/Methods This was a cross sectional study of children enrolled in a primary care practice-based research cohort. Our study included generally healthy children recruited from age 0-5 years. Dependent variables were 1) BMI z-score (zBMI) at 5 years; 2) behavior: total score on the Strengths and Difficulties Questionnaire (SDQ), measured at 3-5 years; 3) development: total score on the Infant Toddler Checklist (ITC), measured at 18-24 months. Independent variable was parent-reported annual household income (< $100,000 vs ≥ $100000). We then used distributional decomposition, which uses mathematical re-weighting to construct a counterfactual distribution that describes the distribution of the lower income group based on the predictor profile (child age, sex, birthweight, prematurity, breastfeeding duration; maternal age, education, immigration status, ethnicity) of the higher income group. Results Our study samples consisted of 1649 (zBMI), 764 (SDQ) and 761 (ITC) children. Mean BMI z-score was 0.16, median total difficulties score was 7, median ITC score was 48. Comparing distributions graphically (Figure 1), children with low income have a higher risk distribution for all outcomes; for example, children with low income were more likely to have BMI z-scores in the underweight and obese ranges. For each outcome, the counterfactual curve lower income children with the predictor profile of their higher income counterparts reduced inequities somewhat, particularly in the normal or low risk range, but not in the high-risk range. However, there were notable unexplained portions of inequity remaining. Conclusion In a cohort of generally healthy children, we found evidence of meaningful income-related inequities in the distribution of child zBMI, behavior difficulties, and development. Population health interventions aiming to mitigate these inequities by addressing common predictors may improve outcomes in the normal range; however targeted clinical interventions are likely required for those in the high-risk range.

ObjectivesWhile studies exist on the association between screen time and cardiometabolic risk among adolescents, research examining the effect of screen time on cardiometabolic risk in young children is lacking. The primary objective of this study was to examine the association between daily screen time and cardiometabolic risk (CMR) [sum of age- and sex-standardized z-scores of systolic blood pressure (SBP), glucose, log-triglycerides, waist circumference (WC), and negative high-density lipoprotein (HDL) cholesterol divided by the square root of five] in young children. Secondary objectives included examining individual CMR risk factors, including waist-to-height ratio and non high-density lipoprotein (non-HDL) cholesterol, as well as the individual cut-offs of these risk factors. Additional analyses include examining the association between screen time and CMR by handheld/non-handheld devices.MethodsA study was conducted among young children 3 to 6 years from the TARGet Kids! practice-based research network in Toronto and Montreal, Canada. Children with one or more measures of screen time and CMR were included in this study. Generalized estimating equation (GEE) multivariable linear regressions and multivariable logistic regressions, using published cut-offs, were conducted to evaluate these associations.ResultsData from 1317 children [mean age 52 months (SD = 13.36), 44.34% female] were included for analyses. There was no evidence of associations between screen time and total CMR score or individual risk factors (p > 0.05) after adjusting for confounders. A statistically significant, but small association between daily screen time and non-HDL cholesterol was found (B = 0.046; CI = [0.017 to 0.075];p = 0.002.ConclusionsThough no relationship was reported between daily screen time and the majority of CMR factors in early childhood, there was an association between daily screen time and non-HDL cholesterol. As the relationship between daily screen time and CMR factors may not be apparent in early childhood, studies to evaluate longer-term cardiometabolic effects of screen time are needed. Although there is an evidence-based rationale to reduce screen time in early childhood, prevention of cardiometabolic risk may not be the primary driver.

International guidelines recommend children aged 9 months to 2 years consume whole (3.25%) fat cow's milk, and children older than age 2 years consume reduced (0.1-2%) fat cow's milk to prevent obesity. The objective of this study was to evaluate the longitudinal relationship between cow's milk fat (0.1-3.25%) intake and body mass index z-score (zBMI) in childhood. We hypothesized that higher cow's milk fat intake was associated with lower zBMI.A prospective cohort study of children aged 9 months to 8 years was conducted through the TARGet Kids! primary care research network. The exposure was cow's milk fat consumption (skim (0.1%), 1%, 2%, whole (3.25%)), measured by parental report. The outcome was zBMI. Height and weight were measured by trained research assistants and zBMI was determined according to WHO growth standards. A linear mixed effects model and logistic generalized estimating equations were used to determine the longitudinal association between cow's milk fat intake and child zBMI.Among children aged 9 months to 8 years (N = 7467; 4699 of whom had repeated measures), each 1% increase in cow's milk fat consumed was associated with a 0.05 lower zBMI score (95% CI -0.07 to -0.03, p 0.0001) after adjustment for covariates including volume of milk consumed. Compared to children who consumed reduced fat (0.1-2%) milk, there was evidence that children who consumed whole milk had 16% lower odds of overweight (OR = 0.84, 95% CI 0.77 to 0.91, p 0.0001) and 18% lower odds of obesity (OR = 0.82, 95% CI 0.68 to 1.00, p = 0.047).Guidelines for reduced fat instead of whole cow's milk during childhood may not be effective in preventing overweight or obesity.

BACKGROUND Rapid growth is associated with increased cardiometabolic risk (CMR) in adolescence and adulthood. Little is known about whether the association between rapid growth and increased CMR originates in early childhood. OBJECTIVES To identify age and sex standardized body mass index (zBMI) trajectories and to examine the association between zBMI trajectories and CMR outcomes in children 0 to 60 months. STUDY DESIGN A longitudinal cohort study was conducted through The Applied Research Group for Kids (TARGet Kids!) in Toronto, Canada. Participants had repeated measures of weight and length or height performed from birth to 60 months of age. Latent class mixed modelling was used to identify the zBMI trajectories. Linear regressions were performed to determine the association between zBMI trajectories and the primary outcome, a CMR score, quantified as the sum of age- and sex- standardized waist circumference, systolic blood pressure, glucose, log-triglycerides and negative high-density lipoprotein cholesterol (HDL-C), divided by √5. Secondary outcomes were the individual components of the CMR formula as well as diastolic blood pressure and non-HDL-C. RESULTS Four BMI trajectories were identified among the 1166 children. After adjusting for all covariates, children in the rapidly accelerating trajectory had increased total CMR score (β = 1.38, 95% CI 0.77; 1.99, P

With increasing recognition of mental health’s importance for overall health, public health professionals are seeking to better understand early risk factors for mental illness. A majority of mental health problems emerge during childhood; there is evidence of a particular association between increased childhood growth and poorer mental health. The current study sought to determine the association between growth trajectories during infancy and early childhood (birth to age 5) and mental health (behavioural and emotional difficulties) in early- to mid-childhood (age 3 to 8). The study was conducted among a subset (n=665) of participants from The Applied Research Group for Kids (TARGet Kids!), an ongoing longitudinal cohort study. Five growth trajectories were determined via repeated measures of age- and sex-standardized body mass index (BMI). Mental health was assessed using the Strengths & Difficulties Questionnaire (SDQ) total difficulties, externalizing problems, and internalizing problems scores. The sociodemographic and health characteristics of the sample were described by mental health status (per the SDQ). The sociodemographic and health characteristics of the sample were described by mental health status (per the SDQ). Regression analyses were run to determine the association between growth trajectories and SDQ scores. There was no statistically significant association between increased growth (“rapidly accelerating” trajectory) and SDQ total difficulties (b=1.49[-3.82,6.81],p=0.58), externalizing problems (b=0.31[-3.29,3.91],p=0.86), or internalizing problems (b=1.18[-1.73,4.09],p=0.43). There was a significant association between decelerating growth and increased internalizing problems (b=0.69[0.07,1.31],p=0.03). Current results do not support an association between increased growth and poorer mental health overall in early- to mid-childhood; however, a pattern of decelerating growth may be associated with more internalizing problems. Understanding early risk factors for poor mental health may allow public health researchers to develop targeted interventions and ultimately improve mental health outcomes across the lifespan. Implications and future directions will be discussed.

Background: Student demand for mental health support is straining university resources, yet there is limited information about the scope of need and determinants. Therefore, our objective was to longitudinally examine the importance of potentially modifiable psychosocial and lifestyle factors for mental health and school-related outcomes. Methods: Canadian undergraduates were invited to complete electronic surveys at entry and completion of first year. The baseline survey measured important distal and proximal risk factors and the follow-up survey assessed mental health and well-being. Surveys were linked to academic grades. Multivariable models of proximal risk factors and mental health and school-related outcomes were fit and adjusted for confounders. Outcomes: In a representative sample of 1,530 students, over one-third screened positive for clinically significant depressive and anxiety symptoms at entry, increasing to 36% and 39% respectively at completion of first year. Over the school year, 14% of students reported suicidal thoughts and 1.5% suicide attempts. There was evidence of persistence and overlap in mental health outcomes. Modifiable psychosocial and lifestyle risk factors at entry were associated with positive screens for all mental health outcomes at completion of first year, while anxiety and depressive symptoms were associated with lower grades and school well-being. Interpretation: A substantial proportion of first year university students experience clinically significant mental health symptoms that are negatively associated with academic performance and school well-being. A research-informed comprehensive mental health strategy that includes a whole university approach and development of effective prevention initiatives seems justified. Funding Statement: The U-Flourish Student Well-Being and Academic Success study is funded by an operating grant from the Canadian Institutes of Health Research. Declaration of Interests: All authors confirm that they have no financial or personal conflict of interest to disclose in relationship to this manuscript. Ethics Approval Statement: Ethics approval for this study was received from the Queen’s University and Affiliated Teaching Hospitals Research Ethics Board (HSREB PSIY-609-18).

IMPORTANCE: Atopic dermatitis may be associated with short stature and obesity in children, but most previous studies have been either small or cross-sectional. OBJECTIVE: To evaluate the association between atopic dermatitis and height, body mass index (BMI; calculated as weight in kilograms divided by height in meters squared), and weight throughout childhood. DESIGN, SETTING, AND PARTICIPANTS: TARGet Kids! (The Applied Research Group for Kids) is an ongoing prospective longitudinal cohort study that collects data at routine physician visits throughout childhood. In this cohort, children aged 5 or younger were followed up into adolescence at regular physician visits at general pediatric and family practices in Toronto, Canada, from June 2008 to February 2021. EXPOSURE: Parental report of atopic dermatitis. MAIN OUTCOMES AND MEASURES: Primary outcomes were length-for-age and BMI-for-age z scores. The secondary outcome was weight-for-age z score. Linear mixed effects models were used to estimate associations between atopic dermatitis and each outcome. In secondary analyses, interaction terms were included between atopic dermatitis and age. RESULTS: A total of 10 611 children were included in the analysis, with mean (SD) baseline age of 23 (20) months; 5070 (47.8%) participants were female. Participants were followed for a median (range) of 28.5 (0.0-158.0) months. A total of 1834 (17.3%) children had atopic dermatitis during follow-up. Atopic dermatitis was associated with lower length-for-age z score (−0.13; 95% CI, −0.17 to −0.09; P

Key Points Question What are the associations between different types of electronic screen use and mental health symptoms in Canadian children and youth during the COVID-19 pandemic? Findings In this longitudinal study of 4 cohorts, 2026 children with 6648 observations were included. Compared with children with lower levels of screen use, children with higher levels of screen use had significantly higher levels of mental health symptoms during the COVID-19 pandemic. Meaning These findings suggest that policy intervention, as well as evidence-informed social supports, may be required to promote healthful screen use and mental health in children and youth during the pandemic and beyond., This cohort study examines whether specific forms of electronic screen use were associated with symptoms of depression, anxiety, conduct problems, irritability, hyperactivity, and inattention in children and youth during COVID-19., Importance Longitudinal research on specific forms of electronic screen use and mental health symptoms in children and youth during COVID-19 is minimal. Understanding the association may help develop policies and interventions targeting specific screen activities to promote healthful screen use and mental health in children and youth. Objective To determine whether specific forms of screen use (television [TV] or digital media, video games, electronic learning, and video-chatting time) were associated with symptoms of depression, anxiety, conduct problems, irritability, hyperactivity, and inattention in children and youth during COVID-19. Design, Setting, and Participants A longitudinal cohort study with repeated measures of exposures and outcomes was conducted in children and youth aged 2 to 18 years in Ontario, Canada, between May 2020 and April 2021 across 4 cohorts of children or youth: 2 community cohorts and 2 clinically referred cohorts. Parents were asked to complete repeated questionnaires about their children’s health behaviors and mental health symptoms during COVID-19. Main Outcomes and Measures The exposure variables were children’s daily TV or digital media time, video game time, electronic-learning time, and video-chatting time. The mental health outcomes were parent-reported symptoms of child depression, anxiety, conduct problems and irritability, and hyperactivity/inattention using validated standardized tools. Results This study included 2026 children with 6648 observations. In younger children (mean [SD] age, 5.9 [2.5] years; 275 male participants [51.7%]), higher TV or digital media time was associated with higher levels of conduct problems (age 2-4 years: β, 0.22 [95% CI, 0.10-0.35]; P

Background Socioeconomic status (SES) is a well-established social determinant of child health. When reliable self-report family income is unavailable, area-level measures, such as median neighbourhood income, are commonly used as a proxy. However, median neighbourhood income is not a good proxy for self-report family income. Newer area-level measures, such as the Neighbourhood Equity Score (NES) and the Child and Family Inequities Score (CFIS) are composite scores comprised of indicators of well-being such as income, parental education and physical surroundings. Objectives The primary objective was to evaluate the agreement between self-report family income and three area-level measures: median neighbourhood income, NES, and CFIS. The secondary objective was to examine the association between self-report family income, NES, and CFIS with two health indicators associated with SES: overweight/obesity (BMI z-score>1) and short breastfeeding duration ( Design/Methods We conducted a cross-sectional study using data from a healthy urban Canadian cohort of young children (0-5 years) attending a scheduled health supervision visit in primary care. Parents completed a questionnaire including family income, postal code and breastfeeding duration. Research assistants measured height and weight (to calculate body mass index). Postal code was used to determine each area-level measure. Agreement between self-report family income and area-level measures was evaluated using kappa coefficients. The percentage of families accurately classified by area-level measures compared with self-report family income was calculated. Multivariable logistic regression was used to evaluate the association between self-report family income, NES, and CFIS (quintiles) with the two health indicators (present/absent). Results 5149 children were included (mean age 21 months). Agreement between self-report family income and both NES and CFIS was ‘fair’ (weighted k=0.29 for both), and agreement with median neighbourhood income was ‘poor’ (weighted k=0.09). Accurate classification between self-report family income and the three measures were: median neighbourhood income (5.6%), NES (32.2%), CFIS (32.4%). For children in the lowest vs. highest quintile, the odds (95% CI) of overweight/obesity were: self-report family income OR=2.75 (1.60-4.72), NES OR=2.02 (1.23-3.30), CFIS OR=2.04 (1.25-3.33); and having short breastfeeding duration: self-report family income OR=1.61 (1.32-1.97), NES OR=1.84 (1.50-2.25), CFIS OR=1.84 (1.46-2.31). Conclusion Agreement and accurate classification between self-report family income was strongest for composite area-level measures (NES and CFIS), compared with median neighbourhood income. Both self-report family income and composite area-level measures supported the same conclusion that lower SES was associated with poorer health outcomes. These newer measures may be more appropriate than median neighbourhood income when self-report family income is unavailable.

Summary Objective Identifying how obesity‐related characteristics cluster in populations is important to understand disease risk. Objectives of this study were to identify classes of children based on obesity‐related variables and to evaluate the associations between the identified classes and overweight and obesity. Methods A cross‐sectional study was conducted among children 3–11 years of age (n = 5185) from the TARGet Kids! network (2008–2018). Latent class analysis was used to identify distinct classes of children based on 15 family, metabolic, health behaviours and school‐related variables. Associations between the identified latent classes and overweight and obesity were estimated using multinomial logistic regression. Results Six classes were identified: Class 1: ‘Family and health risk behaviours’ (20%), Class 2: ‘Metabolic risk’ (7%), Class 3: ‘High risk’ (6%), Class 4: ‘High triglycerides’ (21%), Class 5: ‘Health risk behaviours and developmental concern’ (22%), and Class 6: ‘Healthy’ (24%). Children in Classes 1–5 had increased odds of both overweight and obesity compared with ‘Healthy’ class. Class 3 'High risk' was most strongly associated with child overweight (odds ratio [OR] 1.9, 95% confidence interval [CI] 1.2, 3.2) and obesity (OR 3.3, 95% CI 1.7, 6.7). Conclusions Distinct classes of children identified based on obesity‐related characteristics were all associated with increased obesity; however, the magnitude of risk varied depending on number of at‐risk characteristics. Understanding the clustering of obesity characteristics in children may inform precision public health and population prevention interventions.

IntroductionOver 30% of Canadians between the ages of 16 and 24 years attend university. This period of life coincides with the onset of common mental illnesses. Yet, data to inform university-based mental health prevention and early intervention initiatives are limited. The U-Flourish longitudinal study based out of Queen’s University, Canada and involving Oxford University in the UK, is a student informed study funded by the Canadian Institute for Health Research Strategy for Patient Oriented Research (CIHR-SPOR). The primary goal of U-Flourish research is to examine the contribution of risk and resiliency factors to outcomes of well-being and academic success in first year students transitioning to university.Methods and analysisThe study is a longitudinal survey of all first-year undergraduate students entering Queen’s University in the fall term of 2018 (and will launch at Oxford University in fall of 2019). In accordance with the CIHR-SPOR definitions, students represent the target population (ie, patient equivalent). Student peer health educators were recruited to inform the design, content and implementation of the study. Baseline surveys of Queen’s first year students were completed in the fall of 2018, and follow-up surveys at the end of first year in the spring of 2019. Extensive student-led engagement campaigns were used to maximise participation rates. The baseline survey included measures of personal factors, family factors, environmental factors, psychological and emotional health, and lifestyle factors. Main outcomes include self-reported indicators of mental health at follow-up and mental health service access, as well as objective measures of academic success through linkage to university administrative and academic databases. A combination of mixed effects regression techniques will be employed to determine associations between baseline predictive factors and mental health and academic outcomes.Ethics and disseminationEthical approval was obtained by the Health Sciences and Affiliated Teaching Hospitals Research Ethics Board (HSREB) (#6023126) at Queen’s University. Findings will be disseminated through international and national peer-reviewed scientific articles and other channels including student-driven support and advocacy groups, newsletters and social media.

BACKGROUND: Television viewing during mealtime has been associated with elevated BMI in children. Recently, there has been an increase in the use of mobile media devices; however, the association between overall media use during mealtime and markers of cardiometabolic risk (CMR) remains unknown. OBJECTIVES: To examine mealtime media use in children and its association with non-HDL cholesterol levels and other CMR outcomes, including BMI z-score (zBMI), total cholesterol, HDL cholesterol, triglycerides, glucose and insulin. DESIGN/METHODS: A cross-sectional analysis using repeated measures was conducted on n=2,117 (total observations=2,911) healthy children age 1–13 years participating in a practice-based research network from 2013–2018. To account for repeated measures, multivariable linear regression with generalized estimating equations was used to examine the association between weekly mealtime media use and non-HDL cholesterol as well as secondary CMR outcomes. Individual age groups (0.05). CONCLUSION: While mealtime media use was not associated with non-HDL cholesterol, it may be associated with unfavourable lipid profiles through effects on HDL cholesterol in children ≥5y. Motivations for mealtime media use may differ among pre-school and school-aged children, which may therefore contribute to the differing direction of associations observed in our study. Further research examining the context in which mealtime media is used is warranted.