Stability of neurodevelopmental trajectories in moderately late and early preterm children born 15 years apart.

BACKGROUND: Neurodevelopmental trajectories of preterm children may have changed due to changes in care and in society. We aimed to compare neurodevelopmental trajectories in early and moderately late preterm children, measured using the Developmental (D)-score, in two cohorts born 15 years apart. METHODS: We included early preterm and moderately late preterm children from two Dutch cohorts (LOLLIPOP, 2002-2003 and ePREM, 2016-2017). ePREM counterparts were matched to LOLLIPOP participants by gestational age and sex. D-score trajectories were summarized by a multilevel model with random intercepts and random slopes, and multigroup analyses were used to test if the intercepts and slopes differed across cohorts. RESULTS: We included 1686 preterm children (1071 moderately late preterm, 615 early preterm) from LOLLIPOP, and matched these with 1686 ePREM counterparts. The neurodevelopmental trajectories of the two cohorts were mostly similar. For early preterm children, we found no statistically significant differences. For moderately late preterm children, both the intercept (43.0 vs. 42.3, p < 0.001) and slope (23.5 vs. 23.9, p = 0.002) showed some, but only clinically minor, differences. CONCLUSION: Developmental trajectories, measured using the D-score, in the first four years of life are comparable and stable across a period of 15 years for both early and moderately late preterm children. IMPACT: Neurodevelopmental trajectories are similar for early and moderately late preterm children born 15 years apart and thus seem quite stable in time. The validated Developmental score visualizes these trajectories based on developmental milestone attainment Because of its stability over time, the Developmental score trajectory may aid clinicians in neurodevelopmental assessment of preterm children as this simplifies monitoring and interpretation, similar to a growth chart.

Impute-then-exclude versus exclude-then-impute: Lessons when imputing a variable used both in cohort creation and as an independent variable in the analysis model.

We examined the setting in which a variable that is subject to missingness is used both as an inclusion/exclusion criterion for creating the analytic sample and subsequently as the primary exposure in the analysis model that is of scientific interest. An example is cancer stage, where patients with stage IV cancer are often excluded from the analytic sample, and cancer stage (I to III) is an exposure variable in the analysis model. We considered two analytic strategies. The first strategy, referred to as "exclude-then-impute," excludes subjects for whom the observed value of the target variable is equal to the specified value and then uses multiple imputation to complete the data in the resultant sample. The second strategy, referred to as "impute-then-exclude," first uses multiple imputation to complete the data and then excludes subjects based on the observed or filled-in values in the completed samples. Monte Carlo simulations were used to compare five methods (one based on "exclude-then-impute" and four based on "impute-then-exclude") along with the use of a complete case analysis. We considered both missing completely at random and missing at random missing data mechanisms. We found that an impute-then-exclude strategy using substantive model compatible fully conditional specification tended to have superior performance across 72 different scenarios. We illustrated the application of these methods using empirical data on patients hospitalized with heart failure when heart failure subtype was used for cohort creation (excluding subjects with heart failure with preserved ejection fraction) and was also an exposure in the analysis model.

Changes in neonatal morbidity, neonatal care practices, and length of hospital stay of surviving infants born very preterm in the Netherlands in the 1980s and in the 2000s: a comparison analysis with identical characteristics definitions.

BACKGROUND: This study evaluates changes in the neonatal morbidity, the neonatal care practices, and the length of hospital stay of surviving very preterm (VP) infants born in the Netherlands in the 1980s and in the 2000s; a period over which historical improvements were introduced into neonatal care. We, herein, also study whether these changes in neonatal morbidity, neonatal care practices and length of hospital stay are associated with sociodemographic, prenatal, and infant characteristics. METHODS: Two community-based cohorts from 1983 (POPS) and 2002-03 (LOLLIPOP) have provided the perinatal data for our study. The analysis enrolled 1,228 participants born VP (before the 32nd week of gestation) and surviving to 2 years of age without any severe congenital malformation. A rigorous harmonisation protocol ensured a precise comparison of the cohorts by using identical definitions of the perinatal characteristics. RESULTS: In 2003, mothers were older when giving birth, had higher multiple birth rates, and significantly more parents had received higher education. In 2003, less VP infants had severe intraventricular haemorrhage and sepsis and relatively more received continuous positive airway pressure, mechanical ventilation and caffeine therapy than in 1983. Antenatal corticosteroids and surfactant therapy were provided only in 2003. The length of the stay in the neonatal intensive care unit and in hospital had decreased in 2003 by 22 and 11 days, respectively. Differences persisted after adjustment for sociodemographic, prenatal, and infant characteristics. CONCLUSIONS: Neonatal morbidities of the surviving VP infants in this study have not increased, and exhibit improvements for various characteristics in two cohorts born 20 years apart with comparable gestational age and birth weight. Our data suggest that the improvements found are associated with more advanced therapeutic approaches and new national protocols in place, and less so with sociodemographic changes. This analysis provides a basis for further comparative analyses of the health and the development of VP children, particularly with regard to long-term outcomes.

Evaluation and prediction of individual growth trajectories.

BACKGROUND: Conventional growth charts offer limited guidance to track individual growth. AIM: To explore new approaches to improve the evaluation and prediction of individual growth trajectories. SUBJECTS AND METHODS: We generalise the conditional SDS gain to multiple historical measurements, using the Cole correlation model to find correlations at exact ages, the sweep operator to find regression weights and a specified longitudinal reference. We explain the various steps of the methodology and validate and demonstrate the method using empirical data from the SMOCC study with 1985 children measured during ten visits at ages 0-2 years. RESULTS: The method performs according to statistical theory. We apply the method to estimate the referral rates for a given screening policy. We visualise the child's trajectory as an adaptive growth chart featuring two new graphical elements: amplitude (for evaluation) and flag (for prediction). The relevant calculations take about 1 millisecond per child. CONCLUSION: Longitudinal references capture the dynamic nature of child growth. The adaptive growth chart for individual monitoring works with exact ages, corrects for regression to the mean, has a known distribution at any pair of ages and is fast. We recommend the method for evaluating and predicting individual child growth.

The effect of high prevalence of missing data on estimation of the coefficients of a logistic regression model when using multiple imputation.

BACKGROUND: Multiple imputation is frequently used to address missing data when conducting statistical analyses. There is a paucity of research into the performance of multiple imputation when the prevalence of missing data is very high. Our objective was to assess the performance of multiple imputation when estimating a logistic regression model when the prevalence of missing data for predictor variables is very high. METHODS: Monte Carlo simulations were used to examine the performance of multiple imputation when estimating a multivariable logistic regression model. We varied the size of the analysis samples (N = 500, 1,000, 5,000, 10,000, and 25,000) and the prevalence of missing data (5-95% in increments of 5%). RESULTS: In general, multiple imputation performed well across the range of scenarios. The exceptions were in scenarios when the sample size was 500 or 1,000 and the prevalence of missing data was at least 90%. In these scenarios, the estimated standard errors of the log-odds ratios were very large and did not accurately estimate the standard deviation of the sampling distribution of the log-odds ratio. Furthermore, in these settings, estimated confidence intervals tended to be conservative. In all other settings (i.e., sample sizes > 1,000 or when the prevalence of missing data was less than 90%), then multiple imputation allowed for accurate estimation of a logistic regression model. CONCLUSIONS: Multiple imputation can be used in many scenarios with a very high prevalence of missing data.

Birth outcomes between 22 and 26 weeks' gestation in national population-based cohorts from Sweden, England and France.

AIM: We investigated the timing of survival differences and effects on morbidity for foetuses alive at maternal admission to hospital delivered at 22 to 26 weeks' gestational age (GA). METHODS: Data from the EXPRESS (Sweden, 2004-07), EPICure-2 (England, 2006) and EPIPAGE-2 (France, 2011) cohorts were harmonised. Survival, stratified by GA, was analysed to 112 days using Kaplan-Meier analyses and Cox regression adjusted for population and pregnancy characteristics; neonatal morbidities, survival to discharge and follow-up and outcomes at 2-3 years of age were compared. RESULTS: Among 769 EXPRESS, 2310 EPICure-2 and 1359 EPIPAGE-2 foetuses, 112-day survival was, respectively, 28.2%, 10.8% and 0.5% at 22-23 weeks' GA; 68.5%, 40.0% and 23.6% at 24 weeks; 80.5%, 64.8% and 56.9% at 25 weeks; and 86.6%, 77.1% and 74.4% at 26 weeks. Deaths were most marked in EPIPAGE-2 before 1 day at 22-23 and 24 weeks GA. At 25 weeks, survival varied before 28 days; differences at 26 weeks were minimal. Cox analyses were consistent with the Kaplan-Meier analyses. Variations in morbidities were not clearly associated with survival. CONCLUSION: Differences in survival and morbidity outcomes for extremely preterm births are evident despite adjustment for background characteristics. No clear relationship was identified between early mortality and later patterns of morbidity.

Strategies for assessing the impact of loss to follow-up on estimates of neurodevelopmental impairment in a very preterm cohort at 2 years of age.

BACKGROUND: Loss to follow-up is a major challenge for very preterm (VPT) cohorts; attrition is associated with social disadvantage and parents with impaired children may participate less in research. We investigated the impact of loss to follow-up on the estimated prevalence of neurodevelopmental impairment in a VPT cohort using different methodological approaches. METHODS: This study includes births < 32 weeks of gestational age (GA) from 4 regions in the UK and Portugal participating in a European birth cohort (N = 1737 survivors). Data on maternal characteristics, pregnancy complications, neonatal outcomes and neighborhood deprivation were collected at baseline. Neurodevelopment was assessed at 2 years of corrected age (CA) using standardized parent-report measures. We applied (1) multiple imputation (MI) and (2) inverse probability weighting (IPW) to estimate the impact of non-response on the prevalence of moderate to severe neurodevelopmental impairment and assessed violations of the missing at random (MAR) assumption using the delta method. RESULTS: 54.2% of children were followed-up. Follow-up was less likely when mothers were younger, multiparous, foreign-born, did not breastfeed and came from deprived areas. The prevalence of neurodevelopmental impairment was 18.4% (95% confidence interval (CI):15.9-21.1) and increased to 20.4% (95%CI: 17.3-23.4) and 20.0% (95%CI:16.9-23.1) for MI and IPW models, respectively. Simulating strong violations of MAR (children with impairments being 50% less likely to be followed-up) raised estimates to 23.6 (95%CI:20.1-27.1) CONCLUSIONS: In a VPT cohort with high loss to follow-up, correcting for attrition yielded modest increased estimates of neurodevelopmental impairment at 2 years CA; estimates were relatively robust to violations of the MAR assumption.

Artifacts annotations in anesthesia blood pressure data by man and machine.

Physiologic data from anesthesia monitors are automatically captured. Yet erroneous data are stored in the process as well. While this is not interfering with clinical care, research can be affected. Researchers should find ways to remove artifacts. The aim of the present study was to compare different artifact annotation strategies, and to assess if a machine learning algorithm is able to accept or reject individual data points. Non-cardiac procedures requiring invasive blood pressure monitoring were eligible. Two trained research assistants observed procedures live for artifacts. The same procedures were also retrospectively annotated for artifacts by a different person. We compared the different ways of artifact identifications and modelled artifacts with three different learning algorithms (lasso restrictive logistic regression, neural network and support vector machine). In 88 surgical procedures including 5711 blood pressure data points, the live observed incidence of artifacts was 2.1% and the retrospective incidence was 2.2%. Comparing retrospective with live annotation revealed a sensitivity of 0.32 and specificity of 0.98. The performance of the learning algorithms which we applied ranged from poor (kappa 0.053) to moderate (kappa 0.651). Manual identification of artifacts yielded different incidences in different situations, which were not comparable. Artifact detection in physiologic data collected during anesthesia could be automated, but the performance of the learning algorithms in the present study remained moderate. Future research should focus on optimization and finding ways to apply them with minimal manual work. The present study underlines the importance of an explicit definition for artifacts in database research.

Artifact Processing Methods Influence on Intraoperative Hypotension Quantification and Outcome Effect Estimates.

BACKGROUND: Physiologic data that is automatically collected during anesthesia is widely used for medical record keeping and clinical research. These data contain artifacts, which are not relevant in clinical care, but may influence research results. The aim of this study was to explore the effect of different methods of filtering and processing artifacts in anesthesiology data on study findings in order to demonstrate the importance of proper artifact filtering. METHODS: The authors performed a systematic literature search to identify artifact filtering methods. Subsequently, these methods were applied to the data of anesthesia procedures with invasive blood pressure monitoring. Different hypotension measures were calculated (i.e., presence, duration, maximum deviation below threshold, and area under threshold) across different definitions (i.e., thresholds for mean arterial pressure of 50, 60, 65, 70 mmHg). These were then used to estimate the association with postoperative myocardial injury. RESULTS: After screening 3,585 papers, the authors included 38 papers that reported artifact filtering methods. The authors applied eight of these methods to the data of 2,988 anesthesia procedures. The occurrence of hypotension (defined with a threshold of 50 mmHg) varied from 24% with a median filter of seven measurements to 55% without an artifact filtering method, and between 76 and 90% with a threshold of 65 mmHg. Standardized odds ratios for presence of hypotension ranged from 1.16 (95% CI, 1.07 to 1.26) to 1.24 (1.14 to 1.34) when hypotension was defined with a threshold of 50 mmHg. Similar variations in standardized odds ratios were found when applying methods to other hypotension measures and definitions. CONCLUSIONS: The method of artifact filtering can have substantial effects on estimates of hypotension prevalence. The effect on the association between intraoperative hypotension and postoperative myocardial injury was relatively small. Nevertheless, the authors recommend that researchers carefully consider artifacts handling and report the methodology used.

Patient and anesthesia characteristics of children with low pre-incision blood pressure: A retrospective observational study.

BACKGROUND: Intraoperative blood pressure has been suggested as a key factor for safe pediatric anesthesia. However, there is not much insight into factors that discriminate between children with low and normal pre-incision blood pressure. Our aim was to explore whether children who have a low blood pressure during anesthesia are different than those with normal blood pressure. The focus of the present study was on the pre-incision period. METHODS: This retrospective study included pediatric patients undergoing anesthesia for non-cardiac surgery at a tertiary pediatric university hospital, between 2012 and 2016. We analyzed the association between pre-incision blood pressure and patient- and anesthesia characteristics, comparing low with normal pre-incision blood pressure. This association was further explored with a multivariable linear regression. RESULTS: In total, 20 962 anesthetic cases were included. Pre-incision blood pressure was associated with age (beta -0.04 SD per year), gender (female -0.11), previous surgery (-0.15), preoperative blood pressure (+0.01 per mm Hg), epilepsy (0.12), bronchial hyperactivity (-0.18), emergency surgery (0.10), loco-regional technique (-0.48), artificial airway device (supraglottic airway device instead of tube 0.07), and sevoflurane concentration (0.03 per sevoflurane %). CONCLUSIONS: Children with low pre-incision blood pressure do not differ on clinically relevant factors from children with normal blood pressure. Although the present explorative study shows that pre-incision blood pressure is partly dependent on patient characteristics and partly dependent on anesthetic technique, other unmeasured variables might play a more important role.

Reference chart for knee flexion following total knee arthroplasty: a novel tool for monitoring postoperative recovery.

BACKGROUND: Clinicians and patients lack an evidence-based framework by which to judge individual-level recovery following total knee arthroplasty (TKA) surgery, thus impeding personalized treatment approaches for this elective surgery. Our study aimed to develop and validate a reference chart for monitoring recovery of knee flexion following TKA surgery. METHODS: Retrospective analysis of data collected in routine rehabilitation practice for patients following TKA surgery. Reference charts were constructed using Generalized Additive Models for Location Scale and Shape. Various models were compared using the Schwarz Bayesian Criterion, Mean Squared Error in 5-fold cross validation, and centile coverage (i.e. the percent of observed data represented below specified centiles). The performance of the reference chart was then validated against a test set of patients with later surgical dates, by examining the centile coverage and average bias (i.e. difference between observed and predicted values) in the test dataset. RESULTS: A total of 1173 observations from 327 patients were used to develop a reference chart for knee flexion over the first 120 days following TKA. The best fitting model utilized a non-linear time trend, with smoothing splines for median and variance parameters. Additionally, optimization of the number of knots in smoothing splines and power transformation of time improved model fit. The reference chart performed adequately in a test set of 171 patients (377 observations), with accurate centile coverage and minimal average bias (< 3 degrees). CONCLUSION: A reference chart developed with clinically collected data offers a new approach to monitoring knee flexion following TKA.

Combining multiple imputation and bootstrap in the analysis of cost-effectiveness trial data.

In healthcare cost-effectiveness analysis, probability distributions are typically skewed and missing data are frequent. Bootstrap and multiple imputation are well-established resampling methods for handling skewed and missing data. However, it is not clear how these techniques should be combined. This paper addresses combining multiple imputation and bootstrap to obtain confidence intervals of the mean difference in outcome for two independent treatment groups. We assessed statistical validity and efficiency of 10 candidate methods and applied these methods to a clinical data set. Single imputation nested in the bootstrap percentile method (with added noise to reflect the uncertainty of the imputation) emerged as the method with the best statistical properties. However, this method can require extensive computation times and the lack of standard software makes this method not accessible for a larger group of researchers. Using a standard unpaired t-test with standard multiple imputation without bootstrap appears to be a robust alternative with acceptable statistical performance for which standard multiple imputation software is available.

Systematic review indicates postnatal growth in term infants born small-for-gestational-age being associated with later neurocognitive and metabolic outcomes.

We systematically reviewed papers published in English between 1994 and October 2015 on how postnatal weight gain and growth affect neurodevelopment and metabolic outcomes in term-born small-for-gestational-age (SGA) infants. Two randomised trials reported that enriched infant formulas that promoted early growth also increased fat mass, lean mass and blood pressure (BP), but had no effect on early neurocognitive outcomes. Meanwhile, 31 observational studies reported consistent positive associations between postnatal weight gain and growth with neurocognitive outcomes, adiposity, insulin resistance and BP. CONCLUSION: Few intervention studies exist, despite consistent positive associations between early growth and neurocognition in term-born SGA infants.

Reference Values for Noninvasive Blood Pressure in Children during Anesthesia: A Multicentered Retrospective Observational Cohort Study.

BACKGROUND: Although noninvasive blood pressure (NIBP) monitoring during anesthesia is a standard of care, reference ranges for blood pressure in anesthetized children are not available. We developed sex- and age-specific reference ranges for NIBP in children during anesthesia and surgery. METHODS: In this retrospective observational cohort study, we included NIBP data of children with no or mild comorbidity younger than 18 yr old from the Multicenter Perioperative Outcomes Group data set. Sex-specific percentiles of the NIBP values for age were developed and extrapolated into diagrams and reference tables representing the 50th percentile (0 SD), +1 SD, -1 SD, and the upper (+2 SD) and lower reference ranges (-2 SD). RESULTS: In total, 116,362 cases from 10 centers were available for the construction of NIBP age- and sex-specific reference curves. The 0 SD of the mean NIBP during anesthesia varied from 33 mmHg at birth to 67 mmHg at 18 yr. The low cutoff NIBP (2 SD below the 50th percentile) varied from 17 mmHg at birth to 47 mmHg at 18 yr old. CONCLUSIONS: This is the first study to present reference ranges for blood pressure in children during anesthesia. These reference ranges based on the variation of values obtained in daily care in children during anesthesia could be used for rapid screening of changes in blood pressure during anesthesia and may provide a consistent reference for future blood pressure-related pediatric anesthesia research.

Synthetic growth reference charts.

OBJECTIVES: To reanalyze the between-population variance in height, weight, and body mass index (BMI), and to provide a globally applicable technique for generating synthetic growth reference charts. METHODS: Using a baseline set of 196 female and 197 male growth studies published since 1831, common factors of height, weight, and BMI are extracted via Principal Components separately for height, weight, and BMI. Combining information from single growth studies and the common factors using in principle a Bayesian rationale allows for provision of completed reference charts. RESULTS: The suggested approach can be used for generating synthetic growth reference charts with LMS values for height, weight, and BMI, from birth to maturity, from any limited set of height and weight measurements of a given population. CONCLUSION: Generating synthetic growth reference charts by incorporating information from a large set of reference growth studies seems suitable for populations with no autochthonous references at hand yet.

Developing regional weight-for-age growth references for malaria-endemic countries to optimize age-based dosing of antimalarials.

OBJECTIVE: To derive regional weight-for-age growth references to help optimize age-based dosing of antimalarials in Africa, the Americas, South-East Asia and the Western Pacific. METHODS: A weight-for-age database was constructed from pre-existing population-based anthropometric data obtained from household surveys and research groups. It contained data collected between 1995 and 2012 on 1,263,119 individuals (909,368 female, 353,751 male) older than 14 days and younger than 50 years in 64 malaria-endemic countries. Regional growth references were generated using a generalized additive model for location, scale and shape by combining data with varying distributions from a range of sources. Countries were weighted by their population at risk of malaria to enable references to be used in optimizing the dosing of antimalarials. FINDINGS: Large differences in weight-for-age distributions existed between the regions and between the regions and global growth standards. For example, the average adult male from the Americas weighed 68.1 kg ­ 6.0 kg more than males in South-East Asia and the Western Pacific (average: 62.1 kg). For adult women, the difference was over 10.4 kg: the average was 60.4 kg in the Americas and 50.0 kg in South-East Asia and the Western Pacific. CONCLUSION: There were substantial variations in weight-for-age growth curves between malaria-endemic areas. The growth reference charts derived here can be used to guide the evidence-based optimization of aged-based dosing regimens for antimalarials and other drugs often prescribed by age.

Imputation of systematically missing predictors in an individual participant data meta-analysis: a generalized approach using MICE.

Individual participant data meta-analyses (IPD-MA) are increasingly used for developing and validating multivariable (diagnostic or prognostic) risk prediction models. Unfortunately, some predictors or even outcomes may not have been measured in each study and are thus systematically missing in some individual studies of the IPD-MA. As a consequence, it is no longer possible to evaluate between-study heterogeneity and to estimate study-specific predictor effects, or to include all individual studies, which severely hampers the development and validation of prediction models. Here, we describe a novel approach for imputing systematically missing data and adopt a generalized linear mixed model to allow for between-study heterogeneity. This approach can be viewed as an extension of Resche-Rigon's method (Stat Med 2013), relaxing their assumptions regarding variance components and allowing imputation of linear and nonlinear predictors. We illustrate our approach using a case study with IPD-MA of 13 studies to develop and validate a diagnostic prediction model for the presence of deep venous thrombosis. We compare the results after applying four methods for dealing with systematically missing predictors in one or more individual studies: complete case analysis where studies with systematically missing predictors are removed, traditional multiple imputation ignoring heterogeneity across studies, stratified multiple imputation accounting for heterogeneity in predictor prevalence, and multilevel multiple imputation (MLMI) fully accounting for between-study heterogeneity. We conclude that MLMI may substantially improve the estimation of between-study heterogeneity parameters and allow for imputation of systematically missing predictors in IPD-MA aimed at the development and validation of prediction models.

Thinness in the era of obesity: trends in children and adolescents in The Netherlands since 1980.

BACKGROUND: Although children both at the upper and lower tail of the body mass index (BMI) distribution are at greater health risk, relatively little is known about the development of thinness prevalence rates in developed countries over time. We studied trends in childhood thinness and assessed changes in the BMI distribution since the onset of the obesity epidemic. METHODS: Growth data from 54 814 children aged 2-18 years of Dutch, Turkish and Moroccan origin living in The Netherlands were used. Anthropometric measurements were performed during nationwide cross-sectional growth studies in 1980 (only Dutch), 1997 and 2009. Prevalence rates of thinness grades I, II and III were calculated according to international cut-offs. BMI distributions for 1980, 1997 and 2009 were compared. RESULTS: Since 1980, thinness (all grades combined) reduced significantly from 14.0% to 9.8% in children of Dutch origin, but the proportion of extremely thin children (grade III) remained constant. Thinness in children of Moroccan origin decreased significantly from 8.8% to 6.2% between 1997 and 2009. No significant difference was observed in children of Turkish origin (5.4% in 1997 vs. 5.7% in 2009). Thinness occurred most often in children aged 2-5 years. There were no differences between boys and girls. The BMI distribution widened since 1980, mainly due to an upward shift of the upper centiles. CONCLUSION: Since the onset of the obesity epidemic, prevalence rates of thinness decreased. However, we found a small but persistent group of extremely thin children. More research is needed to gain insight into their health status.

Call for early prevention: prevalence rates of overweight among Turkish and Moroccan children in The Netherlands.

BACKGROUND: Monitoring overweight in risk groups is necessary. Our aim is to assess the trend in overweight and obesity in Turkish and Moroccan children in the Netherlands since 1997 and to monitor the levels of lifestyle-related behaviours in 2009. METHODS: We selected cross-sectional data of Turkish and Moroccan children aged 2-18 years from two national Growth Studies performed in 1997 and 2009 in the Netherlands. Lifestyle-related behaviours were obtained in the 2009 study by questionnaire. RESULTS: In 2009, 31.9% of Turkish and 26.6% of Moroccan children had overweight, whereas this was, respectively, 26.7% and 19.6% in 1997. Already at 2 years, 21.1% in Turkish and 22.7% in Moroccan children had overweight in 2009. The prevalence of obesity was above 4% from 3 years onwards. High (i.e. ≥ 25%) prevalence rates of unhealthy lifestyle-related behaviours were found for not having breakfast (26-49%) among Turkish and Moroccan adolescent (i.e. 15-18 years) girls, consuming no fruit (29-45%) and watching TV/PC ≥ 2 h (35-72%) among all Turkish and Moroccan adolescents, no walking/cycling to school/day care among preschool children (2-4 years) (28-56%) and adolescents (34-94%), drinking ≥ 2 glasses of sweet beverages (44-74%) and being <1 h physically active (29-65%) among all children. CONCLUSION: An upward trend of overweight and obesity occurred in Turkish and Moroccan children. Already at 2 years of age, one out of five Turkish and Moroccan children had overweight, which calls for early prevention with attention to specific lifestyle-related behaviours.

Postnatal growth in preterm infants and later health outcomes: a systematic review.

UNLABELLED: In preterm infants, poor postnatal growth is associated with adverse neurocognitive outcomes; conversely, rapid postnatal growth is supposedly harmful for future development of metabolic diseases. CONCLUSION: In this systematic review, observational studies reported consistent positive associations between postnatal weight or head growth and neurocognitive outcomes; however, there was limited evidence from the few intervention studies. Evidence linking postnatal weight gain to later adiposity and other cardiovascular disease risk factors in preterm infants was also limited.