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An antenatal prediction model for adverse birth outcomes in an urban population: The contribution of medical and non-medical risks.
Midwifery 2016 July
OBJECTIVES: 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.
DESIGN: a prospective cohort study under routine practice conditions.
SETTING: six midwifery practices and two hospitals in Rotterdam, the Netherlands.
PARTICIPANTS: 836 pregnant women.
INTERVENTIONS: the R4U scorecard was filled out at the booking visit.
MEASUREMENTS: 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).
FINDINGS: 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.
KEY 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.
IMPLICATIONS FOR PRACTICE: 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.
DESIGN: a prospective cohort study under routine practice conditions.
SETTING: six midwifery practices and two hospitals in Rotterdam, the Netherlands.
PARTICIPANTS: 836 pregnant women.
INTERVENTIONS: the R4U scorecard was filled out at the booking visit.
MEASUREMENTS: 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).
FINDINGS: 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.
KEY 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.
IMPLICATIONS FOR PRACTICE: 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.
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