title: An antenatal prediction model for adverse birth outcomes in an urban population: The contribution of medical and non-medical risks.
abstract: OBJECTIVE
  in the Netherlands the perinatal mortality rate is high compared to other European countries. Around eighty percent of perinatal mortality cases is preceded by being small for gestational age (SGA), preterm birth and/or having a low Apgar-score at 5 minutes after birth. Current risk detection in pregnancy focusses primarily on medical risks. However, non-medical risk factors may be relevant too. Both non-medical and medical risk factors are incorporated in the Rotterdam Reproductive Risk Reduction (R4U) scorecard. We investigated the associations between R4U risk factors and preterm birth, SGA and a low Apgar score.
  
  
  METHODS
  a prospective cohort study under routine practice conditions.
  
  
  METHODS
  six midwifery practices and two hospitals in Rotterdam, the Netherlands.
  
  
  METHODS
  836 pregnant women.
  
  
  METHODS
  the R4U scorecard was filled out at the booking visit.
  
  
  METHODS
  after birth, the follow-up data on pregnancy outcomes were collected. Multivariate logistic regression was used to fit models for the prediction of any adverse outcome (preterm birth, SGA and/or a low Apgar score), stratified for ethnicity and socio-economic status (SES).
  
  
  RESULTS
  factors predicting any adverse outcome for Western women were smoking during the first trimester and over-the-counter medication. For non-Western women risk factors were teenage pregnancy, advanced maternal age and an obstetric history of SGA. Risk factors for high SES women were low family income, no daily intake of vegetables and a history of preterm birth. For low SES women risk factors appeared to be low family income, non-Western ethnicity, smoking during the first trimester and a history of SGA.
  
  
  CONCLUSIONS
  the presence of both medical and non-medical risk factors early in pregnancy predict the occurrence of adverse outcomes at birth. Furthermore the risk profiles for adverse outcomes differed according to SES and ethnicity.
  
  
  CONCLUSIONS
  to optimise effective risk selection, both medical and non-medical risk factors should be taken into account in midwifery and obstetric care at the booking visit.
authors.affiliation: Erasmus University Medical Centre, Department of Obstetrics and Gynaecology, Division of Obstetrics and Prenatal Medicine, Rotterdam, The Netherlands. Electronic address: a.posthumus@erasmusmc.nl.
authors.forename: A G
authors.initials: AG
authors.lastname: Posthumus
authors.affiliation: Erasmus University Medical Centre, Department of Obstetrics and Gynaecology, Division of Obstetrics and Prenatal Medicine, Rotterdam, The Netherlands; Institute of Health Policy and Management, Erasmus University Rotterdam, Rotterdam, The Netherlands.
authors.forename: E
authors.initials: E
authors.lastname: Birnie
authors.affiliation: Rotterdam University of Applied Sciences, Research Centre Innovations in Care, Rotterdam, The Netherlands.
authors.forename: M J
authors.initials: MJ
authors.lastname: van Veen
authors.affiliation: Erasmus University Medical Centre, Department of Obstetrics and Gynaecology, Division of Obstetrics and Prenatal Medicine, Rotterdam, The Netherlands.
authors.forename: E A P
authors.initials: EA
authors.lastname: Steegers
authors.affiliation: Erasmus University Medical Centre, Department of Obstetrics and Gynaecology, Division of Obstetrics and Prenatal Medicine, Rotterdam, The Netherlands.
authors.forename: G J
authors.initials: GJ
authors.lastname: Bonsel
mesh_terms: D000328:Adult; D001034:Apgar Score; D001724:Birth Weight; D005260:Female; D005865:Gestational Age; D006801:Humans; D007223:Infant; D007226:Infant Mortality; D015999:Multivariate Analysis; D009426:Netherlands / Q000453:epidemiology; D011247:Pregnancy; D011256:Pregnancy Outcome / Q000453:epidemiology*; D011446:Prospective Studies; D044469:Racial Groups / Q000208:ethnology; D018570:Risk Assessment / Q000706:statistics & numerical data*; D012307:Risk Factors; D012309:Risk-Taking; D012931:Social Environment; D014505:Urban Population / Q000706:statistics & numerical data*; D055815:Young Adult
keywords: Adverse outcomes; Antenatal risk assessment; Ethnicity; Prediction; Socio-economic status