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Abstract Background The primary aim of this study was to determine if screen use in early childhood is associated with overall vulnerability in school readiness at ages 4 to 6 years, as measured by the Early Development Instrument (EDI). Secondary aims were to: (1) determine if screen use was associated with individual EDI domains scores, and (2) examine the association between screen use and EDI domains scores among a subgroup of high screen users. Methods This prospective cohort study was carried out using data from young children participating in a large primary care practice-based research network in Canada. Logistic regression analyses were run to investigate the association between screen use and overall vulnerability in school readiness. Separate linear regression models examined the relationships between children’s daily screen use and each separate continuous EDI domain. Results A total of 876 Canadian participants participated in this study. Adjusted logistic regression revealed an association between increased screen use and increased vulnerability in school readiness (p = 0.05). Results from adjusted linear regression demonstrated an association between higher screen use and reduced language and cognitive development domain scores (p = 0.004). Among high screen users, adjusted linear regression models revealed associations between increased screen use and reduced language and cognitive development (p = 0.004) and communication skills and general knowledge domain scores (p = 0.042). Conclusions Screen use in early childhood is associated with increased vulnerability in developmental readiness for school, with increased risk for poorer language and cognitive development in kindergarten, especially among high users.

Abstract Background Sodium is an essential nutrient; however, excess dietary sodium is associated with increased blood pressure levels. The 2004 Canadian Community Health Survey – Nutrition (CCHS 2.2) concluded that most Canadians exceeded the Tolerable Upper Intake Level (UL) of 2300 mg/day. The 2015 CCHS indicated that Canadians were still consuming above the UL. To assess population sodium intakes, a Sodium AnaLysis Tool (SALT) was developed. Methods We used data from CCHS 2.2 (2004) to group foods into types (e.g., popcorn, crackers) and general categories (e.g., snack foods) which formed the SALT questions. Portion sizes and sodium values were calculated for SALT questions. Over a one-month period, one hundred participants completed three, 24-h recalls (at beginning, middle, and end) and two SALT (SALT 1 & SALT 2) tools (at beginning and end). To assess both validity and reliability, statistical tests including Bland-Altman (B-A) plots, paired t-tests, differences between means, and correlations were conducted. The mean of the 3,24-h recalls (m24HR) was used for validation. Results Validity testing between SALT 2 and the m24HR yielded variable results. A B-A plot between SALT 2 and m24HR depicted a small bias of 7 mg/day of sodium. The sodium intake for m24HR (2742 ± 980 mg/day) (mean ± standard deviation) versus SALT 2 (2735 ± 1174 mg/day) was not significantly different (p = 0.960). Pearson’s correlation between methods, although significant (p = 0.02) was poor (r = 0.202; de-attenuated r = 0.400). There was a fair, significant agreement (κ = 0.236, p = 0.02) for the classification of sodium intake into two categories (above or below the UL). Test-retest reliability results were also variable. There was moderate, significant agreement (κ = 0.488, p = 0.001) for classification of sodium intake into two categories between SALT 1 and SALT 2 , a significant correlation (Pearson’s r = 0.785, p

Introduction. Les fournisseurs de soins primaires ont un rôle à jouer dans l’acquisition de saines habitudes alimentaires, en particulier au cours des premières années de vie. Cette étude porte sur la faisabilité de l’intégration de NutriSTEP® – un outil valide de dépistage des risques nutritionnels en 17 points chez les tout‑petits et les enfants d’âge préscolaire – au dossier médical électronique (DME) dans les établissements de soins primaires de l’Ontario (Canada), afin d’éclairer la prise de décisions en matière de soins primaires et la surveillance en santé publique. Méthodologie. Cinq établissements de soins primaires ont intégré, au moyen d’un questionnaire normalisé, le programme de dépistage NutriSTEP au DME. Afin de comprendre les expériences vécues par les professionnels en la matière et d’évaluer les facteurs associés à la réussite de l’implantation de NutriSTEP, nous avons mené des entrevues semi‑dirigées de nature qualitative auprès des fournisseurs de soins primaires connaissant le mieux les détails de sa mise en oeuvre dans leur établissement. Nous avons évalué la qualité des données extraites des DME en déterminant le nombre de questionnaires de dépistage NutriSTEP dûment remplis et avons consigné les mesures de croissance des enfants. Résultats. Les établissements de soins primaires ont mis en oeuvre le questionnaire de dépistage NutriSTEP dans le cadre de diverses rencontres cliniques périodiques, avec des processus de collecte de données variables selon l’établissement. Des données de dépistage NutriSTEP valides ont été recueillies dans les DME de 80 % des établissements de soins primaires. Dans près de 90 % de ces dossiers, le questionnaire avait été entièrement rempli et 70 % des dossiers comportaient à la fois un questionnaire de dépistage NutriSTEP valide complet et des mesures de croissance valides. Conclusion. Il est possible d’intégrer NutriSTEP dans les établissements de soins primaires sous la forme d’un questionnaire normalisé dans le DME, même si, dans notre étude, la façon dont NutriSTEP avait été mis en oeuvre variait selon les établissements. L’utilisation, dans le cadre d’un système de surveillance global du poids santé des enfants, du questionnaire de dépistage NutriSTEP intégré au DME mérite d’être étudiée davantage.

Introduction: Primary care providers have a role to play in supporting the development of healthy eating habits, particularly in a child’s early years. This study examined the feasibility of implementing the NutriSTEP® screen—a 17-item nutrition risk screening tool validated for use with both toddler and preschooler populations—integrated with an electronic medical record (EMR) in primary care practices in Ontario, Canada, to inform primary care decision-making and public health surveillance. Methods: Five primary care practices implemented the NutriSTEP screen as a standardized form into their EMRs. To understand practitioners’ experiences with delivery and assess factors associated with successful implementation, we conducted semi-structured qualitative interviews with primary care providers who were most knowledgeable about NutriSTEP implementation at their site. We assessed the quality of the extracted patient EMR data by determining the number of fully completed NutriSTEP screens and documented growth measurements of children. Results: Primary care practices implemented the NutriSTEP screen as part of a variety of routine clinical contacts; specific data collection processes varied by site. Valid NutriSTEP screen data were captured in the EMRs of 80% of primary care practices. Approximately 90% of records had valid NutriSTEP screen completions and 70% of records had both valid NutriSTEP screen completions and valid growth measurements. Conclusion: Integration of NutriSTEP as a standardized EMR form is feasible in primary care practices, although implementation varied in our study. The application of EMR-integrated NutriSTEP screening as part of a comprehensive childhood healthy weights surveillance system warrants further exploration.

Introduction School readiness is a multidimensional construct that includes cognitive, behavioural and emotional aspects of a child’s development. School readiness is strongly associated with a child’s future school success and well-being. The Early Development Instrument (EDI) is a reliable and valid teacher-completed tool for assessing school readiness in children at kindergarten age. A substantial knowledge gap exists in understanding how early child growth, health behaviours, nutrition, cardiometabolic risk and development impact school readiness. The primary objective was to determine if growth patterns, measured by body mass index trajectories in healthy children aged 0–5 years, are associated with school readiness at ages 4–6 years (kindergarten age). Secondary objectives were to determine if other health trajectories, including health behaviours, nutrition, cardiometabolic risk and development, are associated with school readiness at ages 4–6 years. This paper presents the Fit for School Study protocol.Methods and analysis This is an ongoing prospective cohort study. Parents of children enrolled in the The Applied Health Research Group for Kids (TARGet Kids!) practice-based research network are invited to participate in the Fit for School Study. Child growth, health behaviours, nutrition, cardiometabolic risk and development data are collected annually at health supervision visits and linked to EDI data collected by schools. The primary and secondary analyses will use a two-stage process: (1) latent class growth models will be used to first determine trajectory groups, and (2) generalised linear mixed models will be used to examine the relationship between exposures and EDI results.Ethics and dissemination The research ethics boards at The Hospital for Sick Children, Unity Health Toronto and McMaster University approved this study, and research ethics approval was obtained from each school board with a student participating in the study. The findings will be presented locally, nationally and internationally and will be published in peer-reviewed journals.Trial registration number NCT01869530.