On the third Thursday of every month, we speak to a recent graduate about their thesis and their studies. This month’s guest is Dr Tuba Saygin Avşar who has a PhD from the University of Birmingham. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.
What kinds of interventions are recommended in this context?
Financial incentives (mostly in the form of shopping vouchers for groceries) have been found the most effective and cost-effective intervention to help pregnant women quit smoking. However, we know from evidence that relapse rates are quite high amongst women who quit smoking just before or during pregnancy. Most women restart smoking in the first month after quitting or the month before delivery. We also know that women who live with other smokers are less likely to quit and more likely to restart smoking after quitting. So, interventions aiming at pregnant women should be long-term and include frequent contacts with healthcare professionals to prevent relapses. These should include financial incentives and incorporate other smokers at home to generate smoke-free households.
Another consideration is that some women may not want to quit entirely, or they may not be ready for this yet. Therefore, we need to support women to reduce the number of cigarettes consumed since the evidence shows that women who smoke more cigarettes daily(and their infants) are at more risk of experiencing serious health problems. Moreover, women who smoke fewer cigarettes are less likely to expose their children to second-hand smoking, and they are more likely to quit smoking later on.
How does your cost-effectiveness model differ from other models for smoking cessation?
The Economics of Smoking in Pregnancy – Household (ESIP.H) model is the first model to have a household perspective by including mothers, partners (significant others), and offspring. Considering partners’ smoking enables us to account for the impact of having a smoking partner on the probability of quitting and experiencing health problems because of second-hand smoking during pregnancy. For the offspring, the model incorporates the probability of second-hand smoke exposure during childhood and smoking uptake at the age of 16, depending on the mother’s and mother’s partner’s smoking behaviour.
ESIP.H is first also in considering the number of cigarettes consumed daily; smokers in the model are grouped as light, moderate and heavy smokers and the risk of experiencing health conditions increases respectively as the probability of quitting reduces. Thus, this is the first model that can evaluate the impacts of reducing smoking during pregnancy.
So, with ESIP.H, we can evaluate the interventions aimed at pregnant smokers more accurately and help decision-makers choose the optimum interventions. ESIP.H estimates the incremental costs per quitter and per quality-adjusted-life-year for mother, partner, and offspring separately and combined. ESIP.H also calculates return-on-investment at one year and for the lifetime, which is useful for local decision-makers.
Was it easy for you to find high-quality estimates for all of your model’s parameters?
No! I conducted an umbrella review (systematic review of reviews) to identify the health outcomes that should be incorporated into the model. The review was important in identifying relevant parameters. This model was built based on the extensive work carried out by Dr Matthew Jones, and I used some of the sources he used as well. This was helpful but finding the estimates for different smoking groups was especially challenging.
Most studies did not assess the impact of the amount of daily cigarette consumption on health outcomes. Similarly, there was limited evidence on the impacts of second-hand smoking. Additionally, some studies did not account for the confounding factors fully. For instance, women who quit smoking just before pregnancy were often grouped with women who had never smoked, and this might have meant that the risk for that health condition was underestimated.
These limitations were addressed by conducting scenario analyses and deterministic and probabilistic sensitivity analyses in my research. I discussed the potential impacts of these limitations in detail in my thesis.
What would be your advice to a UK policymaker?
Smoking during pregnancy causes significant health problems, and it is a health inequality issue. In the UK, the current target is to reduce the proportion of women who smoke at the time of delivery from 10% to 6% or less by 2022. Achieving this target is unlikely with the existing stop smoking services (SSS) for pregnant women. This is mainly because around 25% of pregnant women who smoke are admitted to the SSS, and this standard care has very limited impact. It includes only one face-to-face meeting with a smoking cessation specialist, ten weeks of nicotine replacement therapy and around four phone calls. There is no help available for pregnant women who do not want to quit smoking entirely but would like to reduce smoking. Additionally, all the existing smoking cessation interventions for pregnant women (e.g. mobile-based interventions) are cost-effective mainly because they are low-cost interventions, but the impact is usually limited and short-term.
If we would like to reduce smoking during pregnancy significantly in the UK, we should be willing to invest in novel interventions that are more intensive, long-term and comprehensive. We should also provide support for women who would like to reduce their smoking. The economic evaluations in my thesis showed that these interventions would generate smoke-free households, be cost-effective, extend the reach and address health inequalities.
Are these findings likely to be useful in other settings?
We know that the prevalence of smoking during pregnancy is high, and it is a health inequality issue in high-income countries. There is evidence on the effectiveness of financial incentives from different high-income settings. In low and middle-income countries (LMICs), however, we see a different picture. The prevalence of smoking during pregnancy seems lower, and there is minimal evidence on what works.
I conducted a qualitative study to explore the applicability of these findings in LMICs. The results show that the findings of this PhD thesis might have useful insights for LMIC settings. First, some countries have a high prevalence of smoking during pregnancy, such as Turkey (15%) and Jordan (10%). Thus, the findings may apply to those settings.
Additionally, although the PhD focuses on smoking cessation interventions, there is no known difference between smoking cessation and smokeless tobacco cessation techniques. Hence, the findings could be useful for some LMICs where the smoking during pregnancy rate alone is low, but tobacco use during pregnancy is high, e.g. Madagascar (12%). Additionally, some features of the optimum interventions suggested in this thesis are applicable to many LMICs. For instance, having a household perspective may help pregnant women quit smoking, and this offers an opportunity to reach partners and other family members since male smoking is high in most LMICs. However, in addition to cost-effectiveness, affordability and cultural appropriateness should also be considered in LMICs.
How would you like to see this research topic develop in the future?
To take the PhD project further, the first step would be to pilot the suggested interventions in the UK, followed by a feasibility study. In addition, any smoking cessation intervention designed for pregnant women can be evaluated using the ESIP.H model. ESIP.H could also be used to evaluate an intervention in an LMIC setting. This would require identifying context-specific parameters which may not be readily available for every component of the model.
There is also some methodological work that could be undertaken. For example, reparameterising ESIP.H for women from low socioeconomic groups and comparing the outputs with the current version would be interesting. Similarly, the inclusion of e-cigarettes into the economic model would be a valuable contribution.
Related to the public acceptability of financial incentives, further research is required to gain more insight on the issue in the light of recent evidence showing that financial incentives are the most effective and cost-effective intervention.