Economic Appraisal of the Choice and Targeting of Lifestyle Interventions to Prevent Disease in Deprived Populations

The likelihood that conditions such as heart disease, cancers, diabetes and strokes will occur can be affected by the lifestyles that we adopt - such as smoking, over eating, not taking enough exercise, etc. We aim to provide information for policy makers, the NHS and individuals about which interventions to change unhealthy behaviours are effective, as well as cost-effective. Such information will assist in making decisions about how best to use the limited resources available to improve the health of the nation. The idea is that the consequences (in terms of ill health and costs) of different types of lifestyle are affected by an individuals personal circumstances and the environment in which they live. It is these factors that either promote or provide barriers to an individual changing their behaviour.

The main research questions to be addressed are: the contribution of different lifestyle factors to the ill-health and mortality from CHD, cancer, stroke and diabetes that might be prevented; how this preventable ill-health varies between different areas and different social groups who differ in the amount of deprivation they suffer; and the relative costs and benefits of alternative ways of changing behaviour and their impacts on health inequalities.

The aim of the research is to provide information for policy makers, NHS professionals and individuals about the relative costs and benefits of interventions to change unhealthy behaviours, which will assist in making choices about the targeting of scarce resources for health improvement. The hypothesis underlying this study is that the consequences of adverse lifestyles and, hence, the costs and benefits of preventive interventions, are mediated (positively or negatively) by personal and environmental factors, which either promote or provide barriers to change, and that there is an inverse relationship between the efficiency of targeting interventions and the impact on health inequalities. This hypothesis is investigated using existing secondary data sets which can be linked together to combine information on health behaviours, deprivation relating to individual and area based characteristics and health outcomes. The research builds on an existing study being carried out under the NPRI programme to conduct an economic evaluation of interventions in adults to prevent obesity and hence reduce coronary heart disease, cancer and diabetes. The analysis is extended by giving explicit consideration to other lifestyle factors (smoking and alcohol), by identifying where there are concentrations of preventable ill-health, within particular locations (as clusters of particularly good or bad behaviours) or population subgroups, and by considering the efficiency and effect on health inequalities of targeting preventive interventions. The main research questions to be addressed are: the contribution of different lifestyle factors to the excess burden of ill-health and mortality from CHD, cancer, stroke and diabetes; how this excess burden varies across geographic areas and different social groups in relation to deprivation factors; and the relative costs and benefits of alternative approaches to targeting interventions and the impacts on health inequalities. The study will proceed by first estimating relationships between single health behaviours and health impacts for each disease of interest and then considering combinations of health behaviours and interrelationships between the disease areas. The research will then focus on the role of individual and geographic deprivation factors, and will test alternative approaches to estimating these associations. Finally, the modelling results will be combined with information on interventions drawn from the literature in a cost-benefit framework. The results will inform decisions about priorities: which health behaviours to target, whether to tackle multiple behaviours together, which population groups to prioritise and the trade off between total health gain and the impact on health inequalities.