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Children with special health care needs (SHCN) due to a chronic health condition perform more poorly at school compared to their classmates. There is still little knowledge on the causal pathways and which factors could be targeted by interventions. We, therefore, investigated school absenteeism in children with SHCN compared to their peers. This study was based on data from the German population-based prospective cohort study ikidS (German for: I will start school). Children with SHCN were identified by the Children with Special Health Care Needs screener that captures five consequences of physical or mental chronic health conditions: (1) use or need of prescription medication, (2) above average use or need of medical, mental health, or educational services, (3) functional limitations compared with others of the same age, (4) use or need of specialized therapies, and (5) treatment or counseling for emotional, behavioral, or developmental problems. School absenteeism was defined as days absent from school due to illness during first grade and was reported by classroom teachers. Associations between SHCN consequences and school absenteeism were investigated by negative binomial regression models. Effect estimates were adjusted for confounding variables identified by a causal framework and directed acyclic graphs. 1,921 children (mean age at follow-up 7.3 years, standard deviation 0.3; 49% females) were included; of these, 14% had SHCN. Compared to their classmates, children with SHCN had more days absent (adjusted rate ratio: 1.37; 95% confidence interval 1.16, 1.62). The effect was strongest among children with i) functional limitations, ii) treatment or counseling for emotional, behavioral, or developmental problems, and iii) those who experienced two or more SHCN consequences. Children with SHCN have higher school absenteeism, which could-at least partly-explain their poorer school performance and lower educational attainment. SHCN-specific targeted interventions may reduce the adverse effects of SHCN on educational outcomes in children.

Background While there is increasing interest in identifying pregnancies at risk for adverse outcome, existing prediction models have not adequately assessed population-based risks, and have been based on conventional regression methods. The objective of the current study was to identify predictors of fetal growth abnormalities using logistic regression and machine learning methods, and compare diagnostic properties in a population-based sample of infants. Methods Data for 30,705 singleton infants born between 2009 and 2014 to mothers resident in Nova Scotia, Canada was obtained from the Nova Scotia Atlee Perinatal Database. Primary outcomes were small (SGA) and large for gestational age (LGA). Maternal characteristics pre-pregnancy and at 26 weeks were studied as predictors. Logistic regression and select machine learning methods were used to build the models, stratified by parity. Area under the curve was used to compare the models; relative importance of predictors was compared qualitatively. Results 7.9% and 13.5% of infants were SGA and LGA, respectively; 48.6% of births were to primiparous women and 51.4% were to multiparous women. Prediction of SGA and LGA was poor to fair (area under the curve 60–75%) and improved with increasing parity and pregnancy information. Smoking, previous low birthweight infant, and gestational weight gain were important predictors for SGA; pre-pregnancy body mass index, gestational weight gain, and previous macrosomic infant were the strongest predictors for LGA. Conclusions The machine learning methods used in this study did not offer any advantage over logistic regression in the prediction of fetal growth abnormalities. Prediction accuracy for SGA and LGA based on maternal information is poor for primiparous women and fair for multiparous women.

Prediction of small (SGA) and large for gestational age (LGA) using routinely collected antenatal data remains suboptimal, particularly among nulliparous women. In this study, models for SGA (< 10 th percentile) and LGA (> 90 th percentile) were developed by combining grandmaternal pregnancy-related information and maternal birth characteristics (“G0 predictors”) with maternal clinical factors available at 26 weeks’ gestation (“G1 predictors”). The study used a cohort of first-born, singleton births to nulliparous women in Nova Scotia, Canada (1981–2011), and their mothers, from the Nova Scotia Atlee Perinatal Database. Models using G0 predictors, G1 predictors, and their combination were developed with Super Learner, an ensemble machine learning algorithm, and internally validated using nested cross-validation. Discrimination was assessed via the area under the receiver operating characteristic curve (AUC-ROC) and the precision-recall curve (AUC-PR); calibration was also evaluated. Among 9,097 grandmother-mother-infant triads, 902 (9.9%) infants were SGA and 891 (9.8%) were LGA. Including G0 predictors improved discrimination compared to G1-only models (AUC-ROC 0.69 vs. 0.66 for SGA and 0.71 vs. 0.66 for LGA; AUC-PR: 0.21 vs. 0.18 for SGA and 0.22 vs. 0.18 for LGA). Models fitted using both sets of predictors were well calibrated. While incorporating intergenerational information modestly improved prediction, overall predictive performance remains poor.

Maternal pre-conception obesity is a strong risk factor for childhood overweight. However, prenatal mechanisms and their effects in susceptible gestational periods that contribute to this risk are not well understood. We aimed to assess the impact of late-pregnancy dysglycemia in obese pregnancies with negative testing for gestational diabetes mellitus (GDM) on long-term mother-child outcomes. The prospective cohort study Programming of Enhanced Adiposity Risk in Childhood-Early Screening (PEACHES) (n = 1,671) enrolled obese and normal weight mothers from August 2010 to December 2015 with trimester-specific data on glucose metabolism including GDM status at the end of the second trimester and maternal glycated hemoglobin (HbA1c) at delivery as a marker for late-pregnancy dysglycemia (HbA1c ≥ 5.7% [39 mmol/mol]). We assessed offspring short- and long-term outcomes up to 4 years, and maternal glucose metabolism 3.5 years postpartum. Multivariable linear and log-binomial regression with effects presented as mean increments (Δ) or relative risks (RRs) with 95% confidence intervals (CIs) were used to examine the association between late-pregnancy dysglycemia and outcomes. Linear mixed-effects models were used to study the longitudinal development of offspring body mass index (BMI) z-scores. The contribution of late-pregnancy dysglycemia to the association between maternal pre-conception obesity and offspring BMI was estimated using mediation analysis. In all, 898 mother-child pairs were included in this unplanned interim analysis. Among obese mothers with negative testing for GDM (n = 448), those with late-pregnancy dysglycemia (n = 135, 30.1%) had higher proportions of excessive total gestational weight gain (GWG), excessive third-trimester GWG, and offspring with large-for-gestational-age birth weight than those without. Besides higher birth weight (Δ 192 g, 95% CI 100-284) and cord-blood C-peptide concentration (Δ 0.10 ng/ml, 95% CI 0.02-0.17), offspring of these women had greater weight gain during early childhood (Δ BMI z-score per year 0.18, 95% CI 0.06-0.30, n = 262) and higher BMI z-score at 4 years (Δ 0.58, 95% CI 0.18-0.99, n = 43) than offspring of the obese, GDM-negative mothers with normal HbA1c values at delivery. Late-pregnancy dysglycemia in GDM-negative mothers accounted for about one-quarter of the association of maternal obesity with offspring BMI at age 4 years (n = 151). In contrast, childhood BMI z-scores were not affected by a diagnosis of GDM in obese pregnancies (GDM-positive: 0.58, 95% CI 0.36-0.79, versus GDM-negative: 0.62, 95% CI 0.44-0.79). One mechanism triggering late-pregnancy dysglycemia in obese, GDM-negative mothers was related to excessive third-trimester weight gain (RR 1.72, 95% CI 1.12-2.65). Furthermore, in the maternal population, we found a 4-fold (RR 4.01, 95% CI 1.97-8.17) increased risk of future prediabetes or diabetes if obese, GDM-negative women had a high versus normal HbA1c at delivery (absolute risk: 43.2% versus 10.5%). There is a potential for misclassification bias as the predominantly used GDM test procedure changed over the enrollment period. Further studies are required to validate the findings and elucidate the possible third-trimester factors contributing to future mother-child health status. Findings from this interim analysis suggest that offspring of obese mothers treated because of a diagnosis of GDM appeared to have a better BMI outcome in childhood than those of obese mothers who-following negative GDM testing-remained untreated in the last trimester and developed dysglycemia. Late-pregnancy dysglycemia related to uncontrolled weight gain may contribute to the development of child overweight and maternal diabetes. Our data suggest that negative GDM testing in obese pregnancies is not an \"all-clear signal\" and should not lead to reduced attention and risk awareness of physicians and obese women. Effective strategies are needed to maintain third-trimester glycemic and weight gain control among otherwise healthy obese pregnant women.

Body mass index (BMI) is commonly used to assess a child's weight status but it does not provide information about the distribution of body fat. Since the disease risks associated with obesity are related to the amount and distribution of body fat, measures that assess visceral or subcutaneous fat, such as waist circumference (WC), waist-to-height ratio (WHtR), or skinfolds thickness may be more suitable. The objective of this study was to develop percentile curves for BMI, WC, WHtR, and sum of 5 skinfolds (SF5) in a representative sample of Canadian children and youth. The analysis used data from 4115 children and adolescents between 6 and 19 years of age that participated in the Canadian Health Measures Survey Cycles 1 (2007/2009) and 2 (2009/2011). BMI, WC, WHtR, and SF5 were measured using standardized procedures. Age- and sex-specific centiles were calculated using the LMS method and the percentiles that intersect the adult cutpoints for BMI, WC, and WHtR at age 18 years were determined. Percentile curves for all measures showed an upward shift compared to curves from the pre-obesity epidemic era. The adult cutoffs for overweight and obesity corresponded to the 72nd and 91st percentile, respectively, for both sexes. The current study has presented for the first time percentile curves for BMI, WC, WHtR, and SF5 in a representative sample of Canadian children and youth. The percentile curves presented are meant to be descriptive rather than prescriptive as associations with cardiovascular disease markers or outcomes were not assessed.

Background In 2005, we reported on the success of Comprehensive School Health (CSH) in improving diets, activity levels, and body weights. The successful program was recognized as a \"best practice\" and has inspired the development of the Alberta Project Promoting active Living and healthy Eating (APPLE) Schools. The project includes 10 schools, most of which are located in socioeconomically disadvantaged areas. The present study examines the effectiveness of a CSH program adopted from a \"best practice\" example in another setting by evaluating temporal changes in diets, activity levels and body weight. Methods In 2008 and 2010, we surveyed grade 5 students from approximately 150 randomly selected schools from the Canadian province of Alberta and students from 10 APPLE Schools. Students completed the Harvard Youth/Adolescent Food Frequency Questionnaire, questions on physical activity, and had their height and weight measured. Multilevel regression methods were used to analyze changes in diets, activity levels, and body weight between 2008 and 2010. Results In 2010 relative to 2008, students attending APPLE Schools were eating more fruits and vegetables, consuming fewer calories, were more physically active and were less likely obese. These changes contrasted changes observed among students elsewhere in the province. Conclusions These findings provide evidence on the effectiveness of CSH in improving health behaviors. They show that an example of \"best practice\" may lead to success in another setting. Herewith the study provides the evidence that investments for broader program implementation based on \"best practice\" are justified.

The objective of the current study was to determine the proportion of adverse perinatal outcomes that could be potentially prevented if maternal obesity were to be reduced or eliminated (population attributable risk fractions, PARF); and the number needed to treat (NNT) of overweight or obese women to prevent one case of adverse perinatal outcome. Data from the Atlee Perinatal Database on 66,689 singleton infants born in Nova Scotia, Canada, between 2004 and 2014, and their mothers were used. Multivariable-adjusted PARFs and NNTs of maternal pre-pregnancy weight status were determined for various perinatal outcomes under three scenarios: If all overweight and obese women were to i) become normal weight before pregnancy; ii) shift down one weight class; or iii) lose 10% of their body weight, significant relative reductions would be seen for gestational diabetes mellitus (GDM, 57/33/15%), hypertensive disorders of pregnancy (HDP, 26/16/6%), caesarean section (CS, 18/10/3%), and large for gestational age births (LGA, 24/14/3%). The NNT were lowest for the outcomes GDM, induction of labour, CS, and LGA, where they ranged from 13 to 73. The study suggests that a substantial proportion of adverse perinatal outcomes may be preventable through reductions in maternal pre-pregnancy weight.

Children with chronic illness perform poorer at school, and school well-being (SWB) may mediate this association. We investigated the association between chronic illness and three domains of SWB in children in first grade. Data from a German population-based prospective cohort study were used. Children with chronic illness were identified their preschool health examination and follow-up parent surveys during first grade. Children were grouped as either (i) having current special health care needs (SHCN), (ii) having at least one physician diagnosis of a chronic illness but no current SHCN, or (iii) being healthy. SWB was assessed at the end of first grade and measured by the Questionnaire for the Assessment of Emotional and Social School Experiences of First and Second Grade Primary School Children. Based on SWB theory and previous frameworks, the following subscales were used: School-Related Self-Concept, Social Integration, and Joy of Learning. The sum score for each subscale was converted into area-transformed T-values (mean 50 and standard deviation 10). Associations between chronic illness groups and SWB subscales were investigated by multivariable linear regression models. Effect estimates were adjusted for potential confounding variables and standardized mean differences (SMD) were calculated. Of the 1,490 children included, 15% had current SHCN and 37% had a physician diagnosis of a chronic illness but no current SHCN. Compared to healthy children, children with SHCN had lower scores for the School-Related Self-Concept and the Joy of Learning subscale (SMD -0.18 for both) but not for the Social Integration subscale. In contrast, children with a chronic condition but no SHCN had lower scores only for the Social Integration subscale (SMD -0.12). Primary school students with a chronic illness with or without SHCN have lower SWB in some domains compared to their healthy peers. SWB may be a mediator in the association between chronic illness and poor school performance.

ObjectiveChildren with special healthcare needs (SHCN) due to a chronic health condition perform more poorly at school compared with their classmates. We aimed to estimate the effects of past, current, transient, emerging and persistent SHCN on school performance in primary school children.MethodsData from the German population-based prospective cohort study ikidS were used. The children withSHCN screener was administered before school entry (T1) and at the end of first (T2) and third grade (T3). Grades for German, maths and science (range: 1 (Very Good) to 6 (Failure)) were obtained at the end of third grade (age 8–9 years), and an average grade was calculated. Associations between the timing of SHCN and average grade were estimated by mixed linear regression models adjusted for potential confounding variables.Results751 children were included, and 21% had ever SHCN. Children with ever SHCN had poorer school performance than children with never SHCN (adjusted mean difference in average grade [95% CI]: 0.17 [0.06; 0.28]). SHCN in the third year were associated with a poorer average grade (0.29 [0.16; 0.41]) compared with healthy children. Only emerging (0.31 [0.15; 0.48]) and persistent (0.25 [0.07; 0.43]) SHCN were associated with average grade.ConclusionsThis study demonstrates the negative effect of current, emerging and persistent SHCN on academic performance in primary school children. Consequently, students should be regularly assessed for SHCN during school age. Timely interventions may help reduce the adverse effects of chronic health conditions on academic achievements in childhood.

To examine whether eating while watching television poses a risk for poor nutrition and excess body weight over and above that of time spent watching television. We analysed data of grade 5 students participating in a comprehensive population-based survey in the Canadian province of Nova Scotia. This survey included the Harvard's Youth Food Frequency Questionnaire, students' height and weight measurements, and a parent survey. We applied multivariable linear and logistic random effects models to quantify the associations of watching television and eating while watching television with diet quality and body weight. The province of Nova Scotia, Canada. Grade 5 students (n 4966). Eating supper while watching television negatively affected the consumption of fruits and vegetables and overall diet quality. More frequent supper while watching television was associated with more soft drink consumption, a higher percentage energy intake from sugar out of total energy from carbohydrate, a higher percentage energy intake from fat, and a higher percentage energy intake from snack food. These associations appeared independent of time children spent watching television. Both watching television and eating while watching television were positively and independently associated with overweight. Our observations suggest that both sedentary behaviours from time spent watching television as well as poor nutrition as a result of eating while watching television contribute to overweight in children. They justify current health promotion targeting time spent watching television and call for promotion of family meals as a means to avoid eating in front of the television.