4.2 Article

Small area synthetic estimates of smoking prevalence during pregnancy in England

Journal

POPULATION HEALTH METRICS
Volume 13, Issue -, Pages -

Publisher

BIOMED CENTRAL LTD
DOI: 10.1186/s12963-015-0067-8

Keywords

Smoking; Pregnancy; Synthetic estimation

Funding

  1. National Institute for Health Research (NIHR) under Programme Grants for Applied Research programme [RP-PG 0109-10020]
  2. British Heart Foundation
  3. Cancer Research UK
  4. Economic and Social Research Council
  5. Medical Research Council
  6. Department of Health under auspices of UK Clinical Research Collaboration
  7. NIHR Collaboration for Leadership in Applied Health Research and Care East Midlands at NHS Nottingham City CCG
  8. ESRC Secondary Data Analysis Initiative [ES/K003046/1]
  9. ESRC [ES/K003046/1] Funding Source: UKRI
  10. Economic and Social Research Council [ES/K003046/1, ES/G007489/1] Funding Source: researchfish
  11. Medical Research Council [MR/K023195/1, MR/K023195/1B] Funding Source: researchfish
  12. National Institute for Health Research [RP-PG-0109-10020] Funding Source: researchfish

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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.

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