When the coalition came to power, I, like many others, was nervous about whether the government would see inequality reduction as one of its core aims. However, while its related policy choices can and should be debated, its explicit acceptance of the Marmot Review and its commitment to ‘improving the health of the poorest, fastest’ shows that inequality reduction is an important policy goal for the government.
The government has also been as busy on public health reform as it has in the NHS, continuing to produce a raft of public health strategy documents around key risky lifestyle behaviors such as smoking, obesity, and alcohol and supporting the Responsibility Deal and campaigns such as Change4Life. The latest steps include the intention to adopt a minimum price for alcohol and the consultation on plain packaging for tobacco.
However, while there is continual evolution in policy on individual behaviors, we tend to hear much less about how unhealthy behaviors cluster together in different population groups and how that, in turn, may relate to inequalities in health. We think this is an important, complementary way of looking at behavior change and have published a study of how four common lifestyle behaviors – smoking, non-adherence to guidelines on fruit and vegetable consumption, excessive consumption of alcohol, and low levels of physical activity – cluster in the English population and how that is changing over time.
We used two waves of the Health Survey for England. We found that between 2003 and 2008, the proportion of the population who had three or four of these unhealthy behaviors fell significantly, from around one in three adults to around one in four. This is really good news since we know – from a long-term study on the combined impact of health behaviors and mortality that followed people over time, using similar metrics – that after an average of 11 years of follow-up, about one in four people with all four behaviors had died compared to just one in 20 of those with none of them. Any news that the population as a whole is moving down the ladder’ of multiple lifestyle risks, therefore, means saved lives.
The bad news is that the large majority of the improvements have come from people from high socio-economic groups and with higher education levels. Although there did not seem to be any worsening over time, the poorest and least educated saw no improvement between health surveys over the five years. This means that relative inequalities have increased and are becoming more polarised. For example, the chances of someone with no qualifications having four unhealthy behaviors compared to someone with higher education increased from three-fold to five-fold over the period.
We can only speculate on why we have seen these changes. The adage that more research is necessary is very true since this is the first study we’re aware of that has looked at change in this way in the English population. This type of research can provide a valuable tool for the government to help it achieve its aim to increase the health of the poorest and fastest. But it does raise serious questions about whether a focus on single behavior approaches, while necessary, are on their own sufficient in relation to inequality goals.
While the central government can help in setting laws and regulating industry and prices, much of the future responsibility for behavior change will lie with local authorities. Understanding the very specific ways that behaviors cluster in local patches will be important if efforts are to be rewarded. Re-analyzing local health and well-being surveys along the lines above is a simple first step to doing this. Beyond that, there are already some great examples of where ‘every contact counts’ is starting to inform the work of local authorities as a whole. We also believe there is great potential in the existing health trainer and community champions networks to make a real impact on reducing the evident inequalities in the clustering of behaviors our report has unearthed.