INTERGROWTH-21st Project international INTER-NDA standards for child development at 2 years of age: an international prospective population-based study.

OBJECTIVES: To describe the construction of the international INTERGROWTH-21st Neurodevelopment Assessment (INTER-NDA) standards for child development at 2 years by reporting the cognitive, language, motor and behaviour outcomes in optimally healthy and nourished children in the INTERGROWTH-21st Project. DESIGN: Population-based cohort study, the INTERGROWTH-21st Project. SETTING: Brazil, India, Italy, Kenya and the UK. PARTICIPANTS: 1181 children prospectively recruited from early fetal life according to the prescriptive WHO approach, and confirmed to be at low risk of adverse perinatal and postnatal outcomes. PRIMARY MEASURES: Scaled INTER-NDA domain scores for cognition, language, fine and gross motor skills and behaviour; vision outcomes measured on the Cardiff tests; attentional problems and emotional reactivity measured on the respective subscales of the preschool Child Behaviour Checklist; and the age of acquisition of the WHO gross motor milestones. RESULTS: Scaled INTER-NDA domain scores are presented as centiles, which were constructed according to the prescriptive WHO approach and excluded children born preterm and those with significant postnatal/neurological morbidity. For all domains, except negative behaviour, higher scores reflect better outcomes and the threshold for normality was defined as ≥10th centile. For the INTER-NDA's cognitive, fine motor, gross motor, language and positive behaviour domains these are ≥38.5, ≥25.7, ≥51.7, ≥17.8 and ≥51.4, respectively. The threshold for normality for the INTER-NDA's negative behaviour domain is ≤50.0, that is, ≤90th centile. At 22-30 months of age, the cohort overlapped with the WHO motor milestone centiles, showed low postnatal morbidity (<10%), and vision outcomes, attentional problems and emotional reactivity scores within the respective normative ranges. CONCLUSIONS: From this large, healthy and well-nourished, international cohort, we have constructed, using the WHO prescriptive methodology, international INTER-NDA standards for child development at 2 years of age. Standards, rather than references, are recommended for population-level screening and the identification of children at risk of adverse outcomes

Assessment of positive parenting programmes in the Autonomous Region of the Basque Country (Spain)

This paper presents the results of a study aimed at identifying and assessing positive parenting programmes and activities carried out in the Autonomous Region of the Basque Country (ARBC), Spain. The study is a development of the III Inter-institutional Family Support Plan (2011), drafted by the Basque Government's Department of Family Policy and Community Development, and its aim is to offer a series of sound criteria for improving existing programmes and ensuring the correct design and implementation of new ones in the future. It analyses 129 programmes and gathers data relative to institutional management and coordination, format, quality of the established aims, adaptation to the theoretical proposal for an Optimal Positive Parenting Curriculum, scientific base, use of the framework of reference for competences, working method, assessment techniques, budgets and publicity, among others. The results highlight the good quality of the programmes' aims and content, and the poor systematic assessment of these same aspects. The study concludes with a series of recommendations for improving the initiatives, integrated into a proposal for a system of indicators to assess and implement positive parenting programmes. (C) 2016 Colegio Oficial de Psicologos de Madrid. Published by Elsevier Espana, S.L.U.This study was funded by the Basque Government Department of Family Policy and Community Development, within the Regional Ministry for Employment and Social Affairs, in 2012

INTERGROWTH-21st Project international INTER-NDA standards for child development at 2 years of age: An international prospective population-based study

Objectives: To describe the construction of the international INTERGROWTH-21st Neurodevelopment Assessment (INTER-NDA) standards for child development at 2 years by reporting the cognitive, language, motor and behaviour outcomes in optimally healthy and nourished children in the INTERGROWTH-21st Project. Design: Population-based cohort study, the INTERGROWTH-21st Project. Setting: Brazil, India, Italy, Kenya and the UK. Participants: 1181 children prospectively recruited from early fetal life according to the prescriptive WHO approach, and confirmed to be at low risk of adverse perinatal and postnatal outcomes. Primary Measures: Scaled INTER-NDA domain scores for cognition, language, fine and gross motor skills and behaviour; vision outcomes measured on the Cardiff tests; attentional problems and emotional reactivity measured on the respective subscales of the preschool Child Behaviour Checklist; and the age of acquisition of the WHO gross motor milestones. Results: Scaled INTER-NDA domain scores are presented as centiles, which were constructed according to the prescriptive WHO approach and excluded children born preterm and those with significant postnatal/neurological morbidity. For all domains, except negative behaviour, higher scores reflect better outcomes and the threshold for normality was defined as ≥10th centile. For the INTER-NDA’s cognitive, fine motor, gross motor, language and positive behaviour domains these are ≥38.5, ≥25.7, ≥51.7, ≥17.8 and ≥51.4, respectively. The threshold for normality for the INTER-NDA’s negative behaviour domain is ≤50.0, that is, ≤90th centile. At 22–30 months of age, the cohort overlapped with the WHO motor milestone centiles, showed low postnatal morbidity ( Conclusions: From this large, healthy and well-nourished, international cohort, we have constructed, using the WHO prescriptive methodology, international INTER-NDA standards for child development at 2 years of age. Standards, rather than references, are recommended for population-level screening and the identification of children at risk of adverse outcomes.</p

Achieving accurate estimates of fetal gestational age and personalised predictions of fetal growth based on data from an international prospective cohort study: a population-based machine learning study

Background Preterm birth is a major global health challenge, the leading cause of death in children under 5 years of age, and a key measure of a population’s general health and nutritional status. Current clinical methods of estimating fetal gestational age are often inaccurate. For example, between 20 and 30 weeks of gestation, the width of the 95% prediction interval around the actual gestational age is estimated to be 18–36 days, even when the best ultrasound estimates are used. The aims of this study are to improve estimates of fetal gestational age and provide personalised predictions of future growth. Methods Using ultrasound-derived, fetal biometric data, we developed a machine learning approach to accurately estimate gestational age. The accuracy of the method is determined by reference to exactly known facts pertaining to each fetus—specifically, intervals between ultrasound visits—rather than the date of the mother’s last menstrual period. The data stem from a sample of healthy, well-nourished participants in a large, multicentre, population-based study, the International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st). The generalisability of the algorithm is shown with data from a different and more heterogeneous population (INTERBIO21st Fetal Study). Findings In the context of two large datasets, we estimated gestational age between 20 and 30 weeks of gestation with 95% confidence to within 3 days, using measurements made in a 10-week window spanning the second and third trimesters. Fetal gestational age can thus be estimated in the 20–30 weeks gestational age window with a prediction interval 3–5 times better than with any previous algorithm. This will enable improved management of individual pregnancies. 6-week forecasts of the growth trajectory for a given fetus are accurate to within 7 days. This will help identify at-risk fetuses more accurately than currently possible. At population level, the higher accuracy is expected to improve fetal growth charts and population health assessments. Interpretation Machine learning can circumvent long-standing limitations in determining fetal gestational age and future growth trajectory, without recourse to often inaccurately known information, such as the date of the mother’s last menstrual period. Using this algorithm in clinical practice could facilitate the management of individual pregnancies and improve population-level health. Upon publication of this study, the algorithm for gestational age estimates will be provided for research purposes free of charge via a web portal