Birth records and hospital admission records are valuable for research on maternal smoking, but individually are known to under-estimate smokers. This study investigated the extent to which combining data from these records enhances the identification of pregnant smokers, and whether this affects research findings such as estimates of maternal smoking prevalence and risk of adverse pregnancy outcomes associated with smoking.Methods:
A total of 846,039 birth records in New South Wales, Australia, (2001–2010) were linked to hospital admission records (delivery and antenatal). Algorithm 1 combined data from birth and delivery admission records, whereas algorithm 2 combined data from birth record, delivery and antenatal admission records. Associations between smoking and placental abruption, preterm birth, stillbirth, and low birthweight were assessed using multivariable logistic regression.Results:
Algorithm 1 identified 127,612 smokers (smoking prevalence 15.1%), which was a 9.6% and 54.6% increase over the unenhanced identification from birth records alone (prevalence 13.8%), and delivery admission records alone (prevalence 9.8%), respectively. Algorithm 2 identified a further 2,408 smokers from antenatal admission records. The enhancement varied by maternal socio-demographic characteristics (age, marital status, country of birth, socioeconomic status); obstetric factors (multi-fetal pregnancy, diabetes, hypertension); and maternity hospital. Enhanced and unenhanced identification methods yielded similar odds ratios for placental abruption, preterm birth, stillbirth and low birthweight.Conclusions:
Use of linked data improved the identification of pregnant smokers. Studies relying on a single data source should adjust for the under-ascertainment of smokers among certain obstetric populations.