title: Small area synthetic estimates of smoking prevalence during pregnancy in England.
abstract: BACKGROUND
  Complete and accurate data on maternal smoking prevalence during pregnancy are not available at a local geographical scale in England. We employ a synthetic estimation approach to predict the expected prevalence of smoking during pregnancy and smoking at delivery by Primary Care Trust (PCT).
  
  
  METHODS
  Multilevel logistic regression models were used with data from the 2010 Infant Feeding Survey and 2011 Census to predict the probability of mothers (a) smoking at any point during pregnancy and (b) smoking at delivery, according to age, deprivation, and the ethnic profile of the home area. These probabilities were applied to demographic information on mothers giving birth from 2010/11 Hospital Episode Statistics data to produce expected counts, and prevalence figures, of smokers by PCT, with Bayesian 95 % credible intervals. The expected prevalence of smoking at delivery by PCT was compared with midwife-collected Smoking at the Time of Delivery (SATOD) data using a Bland-Altman plot.
  
  
  RESULTS
  The expected prevalence of smoking during pregnancy by PCT ranged from 8.1 % (95 % CI 5.6-1.0) to 31.6 % (27.5-34.8). The expected prevalence of smoking at delivery ranged from 2.5 % (1.4-4.0) to 17.1 % (13.7-20.4). Figures for expected smoking prevalence at delivery showed some agreement with SATOD, though SATOD data were generally higher than the synthetic estimates (mean difference 2.99 %).
  
  
  CONCLUSIONS
  It is possible to derive good estimates of expected smoking prevalence during pregnancy for small areas, potentially at much lower cost than conducting large surveys. Such data may be useful to help plan and commission smoking cessation services and monitor their effectiveness.
authors.affiliation: Division of Epidemiology and Public Health, University of Nottingham, School of Medicine, Clinical Sciences Building, Nottingham City Hospital, Nottingham, NG5 1PB UK.
authors.forename: Lisa
authors.initials: L
authors.lastname: Szatkowski
authors.affiliation: Division of Primary Care, Medical School, Queen's Medical Centre, University of Nottingham, School of Medicine, Nottingham, NG7 2UH UK.
authors.forename: Samantha J
authors.initials: SJ
authors.lastname: Fahy
authors.affiliation: Division of Primary Care, Medical School, Queen's Medical Centre, University of Nottingham, School of Medicine, Nottingham, NG7 2UH UK.
authors.forename: Tim
authors.initials: T
authors.lastname: Coleman
authors.affiliation: University of Southampton, Geography and the Environment, University Road, Southampton, SO17 1BJ UK.
authors.forename: Joanna
authors.initials: J
authors.lastname: Taylor
authors.affiliation: Department of Geography, University of Portsmouth, Buckingham Building, Lion Terrace, Portsmouth, PO1 3HE UK.
authors.forename: Liz
authors.initials: L
authors.lastname: Twigg
authors.affiliation: University of Southampton, Geography and the Environment, University Road, Southampton, SO17 1BJ UK.
authors.forename: Graham
authors.initials: G
authors.lastname: Moon
authors.affiliation: Division of Epidemiology and Public Health, University of Nottingham, School of Medicine, Clinical Sciences Building, Nottingham City Hospital, Nottingham, NG5 1PB UK.
authors.forename: Jo
authors.initials: J
authors.lastname: Leonardi-Bee
keywords: Pregnancy; Smoking; Synthetic estimation