Prediction of growth from an early age: curve matching with the TNO Growth Predictor

Curve matching is a new big data technique to predict an outcome given earlier measurements. Here we apply curve matching to predict the future growth of a specific child, the target child. The method searches in large datasets of longitudinal growth data for other children who are similar to the target child in terms of factors that influence growth. The observed growth curves of these matched children provide valuable insights into the future growth of the target child. The TNO Groeivoorspeller (TNO Growth Predictor) plots the expected growth of the target child, as well as the uncertainty of the prediction. Curve matching is a general technique that can also be used for other health measures. The key requirement is the availability of relevant longitudinal data on the outcome and its determinants

Predictie van groei vanaf jonge leeftijd: ‘curve matching’ met de TNO groeivoorspeller

Curve matching is a new big data technique to predict an outcome given earlier measurements. Here we apply curve matching to predict the future growth of a specific child, the target child. The method searches in large datasets of longitudinal growth data for other children who are similar to the target child in terms of factors that influence growth. The observed growth curves of these matched children provide valuable insights into the future growth of the target child. The TNO Groeivoorspeller (TNO Growth Predictor) plots the expected growth of the target child, as well as the uncertainty of the prediction. Curve matching is a general technique that can also be used for other health measures. The key requirement is the availability of relevant longitudinal data on the outcome and its determinants

Food avoidance in children with adverse food reactions: Influence of anxiety and clinical parameters

BackgroundMany children in the general population avoid food because of self-reported adverse food reactions (AFR). Food avoidance can have negative consequences for well-being and nutritional status. This study aimed to investigate which factors are related to avoidance behavior in children (10-13yr old) from the general population. MethodsQuestionnaires for both mother and child were sent to participants from the Europrevall study: 164 children with self-reported AFR and 170 children without AFRs. Spielberger state anxiety and trait anxiety and clinical parameters, such as severity of the adverse reaction, specific IgE and doctor's diagnosis, were compared between those who have (had) AFR and avoid food (i.e., avoiders) and those who have (had) AFR(s) and do not avoid food (anymore; i.e., non-avoiders). ResultsIn total, 59% of the children with AFRs avoided food, of whom 26% had positive specific immunoglobulin E (sIgE). Child's state anxiety about an AFR was higher in avoiders than in non-avoiders, (p<0.001), whereas child's trait anxiety and maternal state anxiety and trait anxiety were comparable in both groups. Avoiders reported more often severe symptoms (i.e., generalized urticaria, respiratory or cardiovascular symptoms) than non-avoiders, (p=0.03). Food avoidance was not associated with ConclusionFood avoidance is related to child's state anxiety about an adverse food reaction. Food avoidance seems to be independent of a doctor's diagnosis of food allergy and advice on food avoidance

Postnatal parental smoking: an important risk factor for SIDS

Sudden infant death syndrome (SIDS) is the unexpected death of an infant that remains unexplained after a thorough investigation of the circumstances, family history, paediatric investigation and complete autopsy. In Western society, it is the leading cause of post-neonatal death below 1 year of age. In the Netherlands, the SIDS incidence is very low, which offers opportunities to assess the importance of old and new environmental risk factors. For this purpose, cases were collected through pathology departments and the working group on SIDS of the Dutch Paediatrician Foundation. A total of 142 cases were included; these occurred after the parental education on sleeping position (1987), restricted to the international age criteria and had no histological explanation. Age-matched healthy controls (N = 2,841) came from a survey of the Netherlands Paediatric Surveillance Unit, completed between November 2002 and April 2003. A multivariate analysis was performed to determine the risk factors for SIDS, including sleeping position, antenatal maternal smoking, postnatal parental smoking, premature birth, gender, lack of breastfeeding and socio-economic status. Postnatal smoking was identified as an important environmental risk factor for SIDS (OR one parent = 2.5 [1.2, 5.0]; both parents = 5.77 [2.2, 15.5]; maternal = 2.7 [1.0, 6.4]; paternal = 2.4 [1.3, 4.5] ) as was prone sleeping (OR put prone to sleep = 21.5 [10.6, 43.5]; turned prone during sleep = 100 [46, 219]). Premature birth was also significantly associated with SIDS (OR = 2.4 [1.2, 4.8]). Postnatal parental smoking is currently a major environmental risk factor for SIDS in the Netherlands together with the long-established risk of prone sleeping