Parental divorce is one of the most stressful life events for youth and is often associated with (long-lasting) emotional and behavioral problems (EBP). However, not much is known about the timing of the emergence of these EBP in adolescents relative to the moment of parental divorce, and its longitudinal effects. We therefore assessed this timing of EBP in adolescents of divorce and its longitudinal effects. We used the first four waves of the TRacking Adolescent’s Individual Lives Survey (TRAILS) cohort, which included 2230 10–12 years olds at baseline. EBP were measured through the Youth Self-Report (YSR), as internalizing and externalizing problems. We applied multilevel analysis to assess the effect of divorce on EBP. The levels of both internalizing and externalizing problems were significantly higher in the period after parental divorce (β = 0.03, and 0.03, respectively; p < 0.05), but not in the period before divorce, with a persistent and increasing effect over the follow-up periods compared to adolescents not experiencing divorce. Adolescents tend to develop more EBP in the period after parental divorce, not before. These effects are long-lasting and underline the need for better care for children with divorcing parents.

The gut microbiome is involved in the bi-directional relationship of the gut – brain axis. As most studies of this relationship are small and do not account for use of psychotropic drugs (PTDs), we explored the relations of the gut microbiome with several internalizing disorders, while adjusting for PTDs and other relevant medications, in 7,656 Lifelines participants from the Northern Netherlands (5,522 controls and 491 participants with at least one internalizing disorder). Disorders included dysthymia, major depressive disorder (MDD), any depressive disorder (AnyDep: dysthymia or MDD), generalized anxiety disorder (GAD) and any anxiety disorder (AnyAnx: GAD, social phobia and panic disorder). Compared to controls, 17 species were associated with depressive disorders and 3 were associated with anxiety disorders. Around 90% of these associations remained significant (FDR <0.05) after adjustment for PTD use, suggesting that the disorders, not PTD use, drove these associations. Negative associations were observed for the butyrate-producing bacteria Ruminococcus bromii in participants with AnyDep and for Bifidobacterium bifidum in AnyAnx participants, along with many others. Tryptophan and glutamate synthesis modules and the 3,4-Dihydroxyphenylacetic acid synthesis module (related to dopamine metabolism) were negatively associated with MDD and/or dysthymia. After additional adjustment for functional gastrointestinal disorders and irritable bowel syndrome, these relations remained either statistically (FDR <0.05) or nominally (P < 0.05) significant. Overall, multiple bacterial species and functional modules were associated with internalizing disorders, including gut – brain relevant components, while associations to PTD use were moderate. These findings suggest that internalizing disorders rather than PTDs are associated with gut microbiome differences relative to controls.

In literature, not much emphasis has been placed on methods for analyzing repeatedly measured independent variables, even less so for the use in prediction modeling specifically. However, repeated measurements could especially be interesting for the construction of prediction models. Therefore, our objective was to evaluate different methods to model a repeatedly measured independent variable and a long-term fixed outcome variable into a prediction model. Six methods to handle a repeatedly measured predictor were applied to develop prediction models. Methods were evaluated with respect to the models’ predictive quality (explained variance R2 and the area under the curve (AUC)) and their properties were discussed. The models included overweight and BMI-standard deviation score (BMI-SDS) at age 10 years as outcome and seven BMI-SDS measurements between 0 and 5.5 years as longitudinal predictor. Methods for comparison encompassed developing models including: all measurements; a single (here: the last) measurement; a mean or maximum value of all measurements; changes between subsequent measurements; conditional measurements; and growth curve parameters. All methods, except for using the maximum or mean, resulted in prediction models for overweight of similar predictive quality, with adjusted Nagelkerke R2 ranging between 0.230 and 0.244 and AUC ranging between 0.799 and 0.807. Continuous BMI-SDS prediction showed similar results. The choice of method depends on hypothesized predictor-outcome associations, available data, and requirements of the prediction model. Overall, the growth curve method seems to be the most flexible method capable of incorporating longitudinal predictor information without loss in predictive quality.

Geographical inequalities in perinatal health and child welfare require attention. To improve the identification, and care, of mothers and young children at risk of adverse health outcomes, the HP4All-2 program was developed. The program consists of three studies, focusing on creating a continuum for risk selection and tailored care pathways from preconception and antenatal care towards 1) postpartum care, 2) early childhood care, as well as 3) interconception care. The program has been implemented in ten municipalities in the Netherlands, aiming to target communities with a relatively disadvantageous position with regard to perinatal and child health outcomes. To delineate the position of the ten participating municipalities, we present municipal and regional differences in the prevalence of perinatal mortality, perinatal morbidity, children living in deprived neighbourhoods, and children living in families on welfare. Data on all singleton births in the Netherlands between 2009 and 2014 were analysed for the prevalence of perinatal mortality and morbidity. In addition, national data on children living in deprived neighbourhoods and children living in families on welfare between 2009 and 2012 were analysed. The prevalence of these outcomes were calculated and ranked for 62 geographical areas, the 50 largest municipalities and the 12 provinces, to determine the position of the municipalities that participate in HP4All-2. Considerable geographical differences were present for all four outcomes. The municipalities that participate in HP4All-2 are among the 25 municipalities with the highest prevalence of perinatal mortality, perinatal morbidity, children living in deprived neighbourhoods, or children in families on welfare. This study illustrates geographical differences in perinatal health and/or child welfare outcomes and demonstrates that the HP4All-2 program targets municipalities with a relative unfavourable position. By targeting these municipalities, the program is expected to contribute most to improving the care for young children and their mothers at risk, and hence to reducing their risks and health inequalities.

Having an infant in the neonatal intensive care unit (NICU) elicits maternal anxiety, which may hamper parent−child bonding. We performed a prospective cohort study to describe anxiety in mothers of infants born before 30 weeks of gestation during NICU stay in The Netherlands, and investigated the influence of infant stress and gestational age. Second, we performed a randomized-controlled live-performed music therapy trial (LPMT trial) to investigate whether music therapy applied to the infant alleviated maternal anxiety. The relation between infant stress, gestational age, and maternal anxiety was measured in 45 mother−infant dyads, using the Neonatal Infant Stressor Scale and the State-Trait Anxiety Inventory (STAI). The effect of LPMT on anxiety was assessed in 21 mothers whose infants were assigned to either LPMT (n = 12) or waitlist (n = 9). Mothers completed the STAI before and after this period. Maternal anxiety decreased over time in all mothers, and was strongly related with infant stress (r = 0.706, p < 0.001), but not with gestational age. Anxiety scores decreased by 12% after LMPT, and increased by 1% after a waitlist period (p = 0.30). Our results indicate that LPMT in the weeks after birth may accelerate the reduction of maternal anxiety. Further research should focus on the effects on mother−child bonding.

Summary: Background: Primary prevention of overweight is to be preferred above secondary prevention, which has shown moderate effectiveness.Objective: To develop and internally validate a dynamic prediction model to identify young children in the general population, applicable at every age between birth and age 6, at high risk of future overweight (age 8).Methods: Data were used from the Prevention and Incidence of Asthma and Mite Allergy birth cohort, born in 1996 to 1997, in the Netherlands. Participants for whom data on the outcome overweight at age 8 and at least three body mass index SD scores (BMI SDS) at the age of ≥3 months and ≤6 years were available, were included (N = 2265). The outcome of the prediction model is overweight (yes/no) at age 8 (range 7.4‐10.5 years), defined according to the sex‐ and age‐specific BMI cut‐offs of the International Obesity Task Force.Results: After backward selection in a Generalized Estimating Equations analysis, the prediction model included the baseline predictors maternal BMI, paternal BMI, paternal education, birthweight, sex, ethnicity and indoor smoke exposure; and the longitudinal predictors BMI SDS, and the linear and quadratic terms of the growth curve describing a child's BMI SDS development over time, as well as the longitudinal predictors' interactions with age. The area under the curve of the model after internal validation was 0.845 and Nagelkerke R² was 0.351.Conclusions: A dynamic prediction model for overweight was developed with a good predictive ability using easily obtainable predictor information. External validation is needed to confirm that the model has potential for use in practice.