Background: Smoking in pregnancy is a major cause of morbidity and mortality, with a significant cost burden to the NHS. An estimated 26% of women still report smoking at the beginning of, or just before, pregnancy, with 12% reporting smoking throughout. While economic evaluations of cessation interventions in the non-pregnant population are well developed, similar evaluations of within-pregnancy interventions are not. Because of the special circumstances associated with pregnancy, general smoking evaluations cannot be applied in these settings. This thesis outlines the development of an improved economic model designed to capture the healthcare costs and benefits associated with smoking and cessation within pregnancy. Methods: A series of scoping reviews of the electronic resource Medline were conducted to identify either within-pregnancy or childhood morbidities which had potentially causal associations with smoking during or after pregnancy, as well as the incidences of morbidities and health related quality of life (HRQoL) scores attributable to those identified. A systematic review appraised the previous economic literature on cessation during pregnancy, to determine where improvements were needed. To ensure that relapse to smoking could be accounted for, a second systematic review generated pooled estimates of abstinence from smoking in the postpartum period. This information was used to develop and construct the improved economic model. Results: 11 conditions were identified as having a causal association with smoking during pregnancy. The systematic review of previous evaluations identified 17 studies; however, only three were considered high quality, suggesting the need for an improved model. The pooled estimates of abstinence suggested that by two years postpartum, most women had restarted smoking, with most relapsing after three, but before 12, months postpartum. The Economic impacts of Smoking In Pregnancy (ESIP) model consists of two linked decision trees which capture the within-pregnancy aspects, while two linked Markov chains capture the post-pregnancy smoking behaviour for both the mother and her child. ESIP was also extended to control for uncertainty. Conclusion: ESIP improves on the previous literature since it directly captures the impact of the mother’s smoking behaviour on the health of her offspring, both within-pregnancy and childhood, using the most accurate data currently available. Future extensions to ESIP include an adult component for the infant to capture their smoking behaviour.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:680264 |
| Date | January 2015 |
| Creators | Jones, Matthew John |
| Publisher | University of Nottingham |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://eprints.nottingham.ac.uk/30604/ |
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