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Background: Measuring multiple and higher‐order interaction effects between multiple categorical variables proves challenging. Objectives: To illustrate a multilevel modelling approach to studying complex interactions. Methods: We apply a two‐level random‐intercept linear regression to a binary outcome for individuals (level‐1) nested within strata (level‐2) defined by all observed combinations of multiple categorical exposure variables. As a pedagogic application, we analyse 36 strata defined by five risk factors of preeclampsia (parity, previous preeclampsia, chronic hypertension, multiple pregnancies, body mass index category) among 652,603 women in the Swedish Medical Birth Registry between 2002 and 2010. Results: The absolute risk of preeclampsia was 4% but was predicted to vary from 1% to 44% across strata. The stratum discriminatory accuracy was 30% according to the variance partition coefficient (VPC) and 0.73 according to the area under the receiver operating characteristic curve (AUC). While the risk heterogeneity across strata was primarily due to the main effects of the categories defining the strata, 5% of the variation was attributable to their two‐ and higher‐way interaction effects. One stratum presented a positive interaction, and two strata presented negative interaction. Conclusions: Multilevel modelling is an innovative tool for identifying and analysing higher‐order interaction effects. Further work is needed to explore how this approach can best be applied to making causal inferences. [ABSTRACT FROM AUTHOR]

Background: Large birth cohort studies are extremely valuable in assessing associations between early life exposures and long-term outcomes. Establishing new birth cohorts is challenging due to declining participation rates. Online methods of data collection may increase feasibility, but have not been evaluated thoroughly.Objective: The primary objective of the ongoing PRegnancy and Infant DEvelopment (PRIDE) Study is to identify exposures during pregnancy and in early life that may affect short-term or long-term health of mother and/or child. In this manuscript, we aimed to evaluate methods of recruitment and online data collection applied.Population: Dutch women aged ≥18 years in early pregnancy.Design: Prospective cohort study.Methods: Initially, only prenatal care providers recruited participants, but alternative recruitment methods were added as a result of disappointing participation rates, including collaboration with "Moeders voor Moeders" (organisation that visits women in early pregnancy) and Facebook advertisements. Data on demographic characteristics, obstetric history, maternal health, life style factors, occupational exposures, nutrition, pregnancy complications, and infant outcomes are primarily collected through Web-based questionnaires at multiple time points during and after pregnancy. Additional data collection components include paternal questionnaires, blood and saliva sampling, and linkage to medical records.Preliminary Results: By September 2019, 9573 women were included in the PRIDE Study, of which 1.3% completed paper-based questionnaires. Mean age of the women analysed was 30.6 years, 71.1% had a high level of education, 57.2% were primiparae, and mean gestational age at enrolment was 9.9 (range 3, 37) weeks, with slight differences between recruitment methods. Pregnancy outcome was known for 89.8%. Retention rate at 6 months after the estimated date of delivery was estimated at 70%. Multiple validation studies conducted within the PRIDE Study indicated high data quality.Conclusion(s): Although challenging and time-consuming, online methods for recruitment and data collection may enable the establishment of new birth cohort studies. [ABSTRACT FROM AUTHOR]

Background: Clinical conditions leading to delivery are heterogeneous. However, most studies examining the short- and long-term consequences of birth on child health only consider gestational age at delivery, not the underlying cause.Objective: To examine the effect of both gestational age at delivery and underlying cause of delivery on child health outcomes.Methods: This population-based retrospective cohort study of singleton infants born in Alberta (April 2004-March 2005) used linked administrative and perinatal data to identify birth subtypes by underlying cause (infection/inflammation (I/I), placental dysfunction (PD), both, or neither), gestational age at delivery, and child health outcomes (neonatal morbidity and mortality, paediatric complex chronic conditions, and neurodevelopmental disorders and disabilities). Poisson regression with robust variance was used to assess differences in the (adjusted) risk ratio (RR) of each outcome by gestational age, and by cause of delivery. The roles of gestational age and cause of delivery were examined using mediation analysis methods.Results: A total of 38,192 children were included, with 66.7% experiencing neither I/I nor PD (I/I: 4.0%, PD: 27.5%, both: 1.8%). Infants born preterm had higher risk of all outcomes compared to those born at term and late-term. Infants with exposure to both causes had higher risk of all outcomes (neonatal morbidity, RR 8.96, 95% confidence interval [CI] 7.55, 10.63; paediatric complex chronic conditions, RR 3.94, 95% CI 3.08, 5.05; and neurodevelopmental disorders, RR 1.58, 95% CI 1.37, 1.84). The effect of underlying cause of delivery on child health outcomes was partially explained by gestational age, more in cases involving I/I than in those involving PD alone.Conclusions: Short- and long-term child health outcomes differ by the underlying cause leading to delivery, as well as the gestational age at delivery. Having a clearer prognosis for infants may promote the use of clinical interventions earlier for children at increased risk. [ABSTRACT FROM AUTHOR]