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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 < .001) and increased waist circumference score (β = 2.39, 95% CI 1.92; 2.86, P < .001) compared to the stable low group., Conclusions: Rapid growth during early childhood is associated with increased CMR in preschool children, largely driven by larger waist circumference., (© 2020 World Obesity Federation.)

Objectives: To examine the association between body mass index (BMI) and iron deficiency in early childhood, while considering the influence of low-grade systemic inflammation., Study Design: Healthy children ages 1-3 years were included in a cross-sectional analysis. Age- and sex-standardized World Health Organization BMI z score (zBMI) was calculated using height/length and weight measurements; iron status was assessed by serum ferritin; inflammation was assessed by C-reactive protein (CRP). Children with CRP ≥10 mg/L were excluded because this may indicate acute systemic inflammation. Adjusted multivariable regression analyses were used to investigate the association between zBMI and both serum ferritin (µg/L), and iron deficiency (serum ferritin <12 µg/L). We performed prespecified subgroup analyses according to CRP level (normal [≤1.0 mg/L] and low-grade inflammation [>1.0 mg/L to <10.0 mg/L])., Results: Of 1607 children included, 20% were categorized as with zBMI >1, 13% had iron deficiency, and 18% had low-grade inflammation. Higher zBMI was associated with lower serum ferritin (-1.51 µg/L, 95% CI -2.23, -0.76, P < .0001) and increased odds of iron deficiency (OR 1.28, 95% CI 1.10, 1.50, P = .002). Though there was no interaction between zBMI and CRP for the adjusted linear regression model (P = .79) or logistic regression model (P = .43), children with low-grade inflammation had a higher serum ferritin (P < .0001)., Conclusions: Higher zBMI is associated with increased risk for iron deficiency in children between 1 and 3 years, and should be considered as a risk factor in targeted screening. Further research is needed to better understand the relationship between serum ferritin and CRP for children in all weight categories., Trial Registration: ClinicalTrials.gov: NCT01869530., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Objective: To evaluate the misclassification resulting from the use of body mass index (BMI) cut-points defined by rounded percentiles instead of Z-scores in early childhood. Using data from the TARGet Kids primary care network we conducted a cross-sectional study among 5836 children < 6 years of age. The World Health Organization growth standards were used to calculate BMI-for-age Z-scores. BMI Z-score cut-points of < - 2.0, > 1.0, > 2.0, > 3.0 are recommended to define wasted, at risk of overweight, overweight and obese. However, rounded percentiles of the 3rd, 85th, 97th, and 99.9th are commonly used. Misclassification was calculated comparing the frequency distributions for BMI categories defined by rounded percentiles and Z-score cut-points., Results: Using rounded percentiles, the proportion of children who were wasted, at risk of overweight, overweight, and obese was 4.2, 12.5, 4.3 and 0.8%, whereas the distribution using Z-scores was: 3.6, 13.8, 3.4 and 1.0%, respectively. Overall, 117 (2%) children were misclassified when using percentiles instead of Z-scores; however, 13% (33/245) of children who were wasted and 14% (8/57) of children who were obese were misclassified. Misclassification of child growth results from the use of cut-points defined by rounded percentiles instead of Z-scores and limits comparability between studies. Trial registration Clinicaltrials.gov NCT01869530 June 5, 2013.

Background: Fortified cow milk is a material contributor of vitamin D and dietary fat in children. Recommendations for children >2 y of age advise reduced milk-fat consumption to reduce childhood obesity, yet the relation between lower milk fat, vitamin D stores, and body mass index (BMI) is unclear., Objectives: The primary objective was to explore the association between milk-fat percentage and both BMI z score (zBMI) and venous 25-hydroxyvitamin D [25(OH)D]; the secondary objective was to assess whether milk volume consumed modified this relation., Design: This was a cross-sectional analysis. Healthy urban children aged 12-72 mo were recruited from 9 primary health care practices within The Applied Research Group for Kids (TARGet Kids!) research group in Toronto, Canada. We used adjusted bivariate linear regression to examine the relation between milk-fat percentage and child 25(OH)D and zBMI concurrently. Effect modification by milk volume consumed on the evaluated relations was explored with the use of an interaction term in the statistical model., Results: Among the 2745 included children there was a positive association between milk-fat percentage and 25(OH)D (P = 0.006) and a negative association between milk-fat percentage and zBMI (P < 0.0001). Participants who drank whole milk had a 5.4-nmol/L (95% CI: 4.32, 6.54) higher median 25(OH)D concentration and a 0.72 lower (95% CI: 0.68, 0.76) zBMI score than children who drank 1% milk. Milk volume consumed modified the effect of milk-fat percentage on 25(OH)D (P = 0.003) but not on zBMI (P = 0.77)., Conclusions: Whole milk consumption among healthy young children was associated with higher vitamin D stores and lower BMI. Longitudinal and interventional studies are needed to confirm these findings. TARGet Kids! was registered at clinicaltrials.gov as NCT01869530., (© 2016 American Society for Nutrition.)

Objectives: To determine the agreement between weight-for-length and BMI-for-age in children 0 to <2 years by using research-collected data, examine factors that may affect agreement, and determine if agreement differs between research- and routinely collected data., Methods: Cross-sectional data on healthy, term-born children (n = 1632) aged 0 to <2 years attending the TARGet Kids! practice-based research network in Toronto, Canada (December 2008-October 2014) were collected. Multiple visits for each child were included. Length (cm) and weight (kg) measurements were obtained by trained research assistants during research visits, and by nonresearch staff during all other visits. BMI-for-age z-scores were compared with weight-for-length z-scores (the criterion measure)., Results: The correlation between weight-for-length and BMI-for-age was strong (r = 0.986, P < .0001) and Bland-Altman plots revealed good agreement (difference = -0.08, SD = 0.20, P = .91). A small proportion (6.3%) of observations were misclassified and most misclassifications occurred near the percentile cutoffs. There were no differences by age and sex. Agreement was similar between research- and routinely collected data (r = 0.99, P < .001; mean difference -0.84, SD = 0.20, P = .67)., Conclusions: Weight-for-length and BMI-for-age demonstrated high agreement with low misclassification. BMI-for-age may be an appropriate indicator of growth in the first 2 years of life and has the potential to be used from birth to adulthood. Additional investigation is needed to determine if BMI-for-age in children <2 years is associated with future health outcomes., (Copyright © 2016 by the American Academy of Pediatrics.)

Background: Obesity has its origins in early childhood; however, there is limited evidence of the association between anthropometric indicators and cardiometabolic risk factors in young children. Our aim was to evaluate the associations between body mass index (BMI) and waist circumference (WC) in relation to cardiometabolic risk factors and to explore the clustering of these factors., Methods: A cross-sectional study was conducted in children aged 1-5 years through TARGet Kids! (n = 2917). Logistic regression was used to evaluate associations between BMI and WC z-scores and individual traditional and possible non-traditional cardiometabolic risk factors. The underlying clustering of these measures was evaluated using principal components analysis (PCA)., Results: Child obesity (BMI z-score >2) was associated with high (>90th percentile) leptin [odds ratio (OR) 8.15, 95% confidence interval (CI) 4.56, 14.58] and insulin (OR = 1.76; 95% CI 1.05, 2.94). WC z-score >1 was associated with high insulin (OR 1.59, 95% CI 1.11, 2.28), leptin (OR 5.48, 95% CI 3.48, 8.63) and 25-hydroxyvitamin D < 75 nmol/L (OR 1.39, 95% CI 1.08, 1.79). BMI and WC were not associated with other traditional cardiometabolic risk factors, including non-High Density Lipoprotein (HDL) cholesterol, and glucose. Among children 3-5 years (n = 1035) the PCA of traditional risk factors identified three components: adiposity/blood pressure, metabolic, and lipids. The inclusion of non-traditional risk factors identified four additional components but contributed minimally to the total variation explained., Conclusions: Anthropometric indicators are associated with selected cardiometabolic risk factors in early childhood, although the clustering of risk factors suggests that adiposity is only one distinct component of cardiometabolic risk. The measurement of other risk factors beyond BMI and WC may be important in defining cardiometabolic risk in early childhood., (© 2015 John Wiley & Sons Ltd.)

Objective: To determine if an intervention for preschool-aged children in primary care is effective in reducing screen time, meals in front of the television, and BMI., Methods: A randomized controlled trial was conducted at a primary care pediatric group practice in Toronto, Canada. Three-year-old children and their parents were randomly assigned to receive a short behavioral counseling intervention on strategies to decrease screen time. The primary outcome 1 year later was parent reported screen time. Secondary outcomes included television in the child's bedroom, number of meals in front of the television, and BMI., Results: In the intention-to-treat analysis at 1 year, there were no significant differences in mean total weekday minutes of screen time (60, interquartile range [IQR]: 35-120 vs 65, IQR: 35-120; P = .68) or mean total weekend day minutes of screen time (80, IQR: 45-130 vs 90, IQR: 60-120; P = .33) between the intervention and control group. Adjusting for baseline BMI, there was a reduction in the number of weekday meals in front of the television (1.6 ± 1.0 vs 1.9 ± 1.2; P = .03) but no differences in BMI or number of televisions in the bedroom., Conclusions: This pragmatic trial was not effective in reducing screen time or BMI but was effective in reducing meals in front of the screen. Short interventions focused solely on reducing screen time implemented in the primary care practice setting may not be effective in this age group.

Background: Accelerated postnatal growth is an important predictor for obesity risk. It is unknown whether early-life obesity-related risk factors affect body mass index (BMI) growth rates during distinct growth periods from early infancy through preschool years. Objective: We examined whether breastfeeding duration, maternal BMI, and birth weight are associated with growth trajectories of age- and sex-standardized WHO BMI z scores (zBMIs) in young children. Design: Children (n = 5905) in The Applied Research Group for Kids (TARGet Kids!) prospective cohort study underwent repeated measures of weight and length or height from birth to 10 y of age. Piecewise linear mixed models were used to determine whether zBMI growth rates differ for each risk factor during periods of growth between birth and 1, 3, 18, 36, and 72 mo of age. Results: Children who were breastfed <6 mo compared with >6 mo showed a higher growth rate between 1-3 and 3-18 mo, resulting in higher standardized BMIs (zBMIs) of +0.24, +0.12, and +0.19 at 18, 36, and 72 mo, respectively. Maternal BMI (in kg/m²) ≥30 compared with <30 resulted in higher growth rates between 1-3 and 36-72 mo and higher zBMIs of +0.22, +0.14, +0.18, and +0.41 at 3, 18, 36, and 72 mo, respectively. Infants weighing <2.5 kg at birth (compared with 2.5-4 kg) experienced higher growth rates between 1-3 and 3-18 mo but had lower zBMIs at all time points (zBMI: -1.45 to -0.21). Infants weighing ≥4 kg at birth (compared with 2.5-4 kg) had significantly lower growth rates in the first 3 mo but higher zBMIs at all time points (zBMI: +1.16 to +0.27). Conclusion: Differences in zBMI growth rates by breastfeeding duration, maternal BMI, and birth weight are seen in early infancy and contribute to differences in zBMI, which persist into midchildhood. [ABSTRACT FROM AUTHOR]

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Background: Measuring body mass index (BMI) has been proposed as a method of screening for preventive primary care and population surveillance of childhood obesity. However, the accuracy of routinely collected measurements has been questioned. The purpose of this study was to assess the reliability of height, length and weight measurements collected during well-child visits in primary care relative to trained research personnel.Methods: A cross-sectional study of measurement reliability was conducted in community pediatric and family medicine primary care practices. Each participating child, ages 0 to 18 years, was measured four consecutive times; twice by a primary care team member (e.g. nurses, practice personnel) and twice by a trained research assistant. Inter- and intra-observer reliability was calculated using the technical error of measurement (TEM), relative TEM (%TEM), and a coefficient of reliability (R).Results: Six trained research assistants and 16 primary care team members performed measurements in three practices. All %TEM values for intra-observer reliability of length, height, and weight were classified as 'acceptable' (< 2%; range 0.19% to 0.70%). Inter-observer reliability was also classified as 'acceptable' (< 2%; range 0.36% to 1.03%) for all measurements. Coefficients of reliability (R) were all > 99% for both intra- and inter-observer reliability. Length measurements in children < 2 years had the highest measurement error. There were some significant differences in length intra-observer reliability between observers.Conclusion: There was agreement between routine measurements and research measurements although there were some differences in length measurement reliability between practice staff and research assistants. These results provide justification for using routinely collected data from selected primary care practices for secondary purposes such as BMI population surveillance and research. [ABSTRACT FROM AUTHOR]

Background: Previous literature reports inconsistent associations between obesity and mental health. The objective of this study was to determine the association between weight status and mental health service utilization in Ontario children and youth. Methods: A cross-sectional study of children 0 to 18 years, identified using primary care electronic medical records from the EMRPC database in Ontario, Canada was conducted. Height and weight data were extracted to calculate BMI and linked to administrative data on mental health related outpatient visits, emergency department visits, and hospitalizations. Multivariable logistic regression models were performed. Results: A total of 50,565 children were included. Overall, 2.2% were underweight, 70.4% had a normal weight, 18.3% were overweight, 6.9% had obesity and 2.2% had severe obesity. 28.2% of all children had at least one mental health visit. Multivariable analyses showed children with overweight, obesity, and severe obesity were 1.11 (95% CI 1.05-1.17), 1.18 (95% CI 1.08-1.27) and 1.39 (95% CI 1.22-1.59) times more likely to have an outpatient mental health visit compared to children with normal weight. Conclusion: Increased weight status was associated with mental health related outpatient visits and emergency department visits. This study may inform policy makers' planning of mental health resources for children with obesity and severe obesity. [ABSTRACT FROM AUTHOR]