MOLGENIS Armadillo: a lightweight server for federated analysis using DataSHIELD.

Summary: Extensive human health data from cohort studies, national registries, and biobanks can reveal lifecourse risk factors impacting health. Combining these sources offers increased statistical power, rare outcome detection, replication of findings, and extended study periods. Traditionally, this required data transfer to a central location or separate partner analyses with pooled summary statistics, posing ethical, legal, and time constraints.

Socioeconomic position during pregnancy and pre-school exposome in children from eight European birth cohort studies.

Distribution of environmental hazards and vulnerability to their effects vary across socioeconomic groups. Our objective was to analyse the relationship between child socioeconomic position (SEP) at birth and the external exposome at pre-school age (0-4 years). This study included more than 60,000 children from eight cohorts in eleven European cities (Oslo, Copenhagen, Bristol, Bradford, Rotterdam, Nancy, Poitiers, Gipuzkoa, Sabadell, Valencia and Turin).

Green spaces and respiratory, cardiometabolic, and neurodevelopmental outcomes: An individual-participant data meta-analysis of >35.000 European children.

Studies evaluating the benefits and risks of green spaces on children's health are scarce. The present study aimed to examine the associations between exposure to green spaces during pregnancy and early childhood with respiratory, cardiometabolic, and neurodevelopmental outcomes in school-age children. We performed an Individual-Participant Data (IPD) meta-analysis involving 35,000 children from ten European birth cohorts across eight countries.

Associations of Maternal Educational Level, Proximity to Green Space During Pregnancy, and Gestational Diabetes With Body Mass Index From Infancy to Early Adulthood: A Proof-of-Concept Federated Analysis in 18 Birth Cohorts.

International sharing of cohort data for research is important and challenging. We explored the feasibility of multicohort federated analyses by examining associations between 3 pregnancy exposures (maternal education, exposure to green vegetation, and gestational diabetes) and offspring body mass index (BMI) from infancy to age 17 years. We used data from 18 cohorts (n = 206,180 mother-child pairs) from the EU Child Cohort Network and derived BMI at ages 0-1, 2-3, 4-7, 8-13, and 14-17 years.

Correction: Gestational age at birth and body size from infancy through adolescence: An individual participant data meta-analysis on 253,810 singletons in 16 birth cohort studies.

[This corrects the article DOI: 10.1371/journal.pmed.

Gestational age at birth and body size from infancy through adolescence: An individual participant data meta-analysis on 253,810 singletons in 16 birth cohort studies.

Background: Preterm birth is the leading cause of perinatal morbidity and mortality and is associated with adverse developmental and long-term health outcomes, including several cardiometabolic risk factors and outcomes. However, evidence about the association of preterm birth with later body size derives mainly from studies using birth weight as a proxy of prematurity rather than an actual length of gestation. We investigated the association of gestational age (GA) at birth with body size from infancy through adolescence.

Dynamic prediction model to identify young children at high risk of future overweight: Development and internal validation in a cohort study.

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.

Development of a prediction model to target screening for high blood pressure in children.

Targeted screening for childhood high blood pressure may be more feasible than routine blood pressure measurement in all children to avoid unnecessary harms, overdiagnosis or costs. Targeting maybe based e.g.

Childhood prediction models for hypertension later in life: a systematic review.

Background: Hypertension, even during childhood, increases the risk of developing atherosclerosis and cardiovascular disease. Therefore, starting prevention of hypertension early in the life course could be beneficial. Prediction models might be useful for identifying children at increased risk of developing hypertension, which may enable targeted primordial prevention of cardiovascular disease.

Repeatedly measured predictors: a comparison of methods for prediction modeling.

Background: 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.