Improving the evidence for place effects on (children’s) health

Four members of the CRESH team attended a two-day ‘Good Places, Better Health for Scotland’s Children’ conference (November 27th and 28th 2012, at Murrayfield, Edinburgh; @gpbhscotland and #gpbhconf).  Good Places Better Health (GPBH) is the Scottish Government’s strategy on health and the environment.  The conference reported on the first phase (2008-2011), which addressed how places can help to deliver improvements in four key health challenges facing children under 9 years old in Scotland: obesity, asthma, unintentional injury, mental health and wellbeing.  In 2012 the GPBH team published the recommendations that have arisen from the work programme.

The conference started by outlining how health and place ‘intelligence’ had been brought together to inform the recommendations.  The first step involved developing a conceptual model within which each of the issues and their influences could be framed (see Scottish Government report for more info).  Subsequently, evidence for place effects on health and wellbeing was brought together from scientific literature and workshops with scientific experts, practitioners, and communities.  The need to value and learn from the ‘anecdotes’ from the workshops as well as the ‘hard science’ from the literature reviews was stressed.  When reviewing the evidence gathered the GPBH team noted that (a) the absence of evidence did not equate with absence of possible effect, and that (b) the social, economic, cultural and physical components of places influence our health in complex and intertwined ways that are very difficult to disentangle.

Interestingly, and importantly, the evidence from literature, experts and practitioners varied.  In the case of childhood obesity, experts rated the strongest scientific evidence for the influence of place as being for ‘downstream’ influences on diet (portion size, snacking, fast food and soft drinks), and determinants of sedentary behaviour and of physical activity in schools and nurseries.  But practitioners (e.g., health care, police, and councils) ranked neighbourhood attributes most highly: unattractive, unsightly and unsafe neighbourhoods were 1st, and neighbourhoods without accessible play and sports facilities were 2nd.

Community engagement approaches were used to assess how communities saw and experienced things – as ‘on-the-ground’ experts.  When asked how place impacted upon their children’s health, parents and carers concurred with the practitioners.  They highlighted mainly negative neighbourhood attributes: anti-social behaviour, dog fouling, junkies, drug dealers, hooligans, drug paraphernalia, vandalism, and the lack of appropriate neighbourhood facilities.  There was a strong sense from these meetings that what researchers often label ‘low-level incivilities’ – things like dog mess, litter and graffiti – can cause a very high level of distress and potential health detriment.  These personal insights should inform and direct our investigations of neighbourhood influences on health.

When bringing the evidence together the team noted that the evidence was mainly for downstream determinants of health, such as displaying sweets at shop tills, and that the much-needed evidence for upstream drivers (the economic, social and political driving forces) would remain elusive until we were ‘permitted’ to randomise society and conduct controlled experiments!  Fortunately for all concerned this is unlikely to happen.  But the difficulties involved in evidencing the impacts of these wider determinants are clear.

What will help are neat approaches to working with pre-existing data that have been collected for individuals or populations over time – e.g., longitudinal survey datasets such as the British Household Panel Survey, repeated cross-sectional surveys such as the Scottish Health Survey, or national death records.  These provide us with a cost-effective means of assessing how wider changes to the upstream drivers of health might influence our health and health behaviours, by exploiting what are often referred to as ‘natural experiments’.  Here we can assess how health or behaviour changed either side of a particular ‘event’ (e.g., introduction of a policy to create smoke-free public buildings: see Jamie Pearce’s work in New Zealand) without needing to establish costly monitoring programmes that might not last long enough to show any effect.  Evidence from natural experiments can be even more robust if, in addition to ‘before and after’ data, we can also identify ‘treatment and control’ sites.  In the UK we have the opportunity of survey data that include both treatment and control nations: for example smoking was banned in public places in Scotland one year before it was in England, Wales or Northern Ireland.

If we remain fixated on the idea that ‘randomised controlled trials’ are the only evidence that counts (see Rich Mitchell’s blog post for discussion) we risk seeing public health policies being made on little or no research evidence (see Dunn and Bobak).  Alternatively, accepting the value of what we can learn from natural experiments and other longitudinal study designs will enable us to provide policy-makers with evidence for how upstream drivers influence our health.   The wealth of already-collected data available in the UK and elsewhere gives us a great opportunity to ‘add value’ to these investments and uncover important lessons about environment and health relationships.  We should continue to utilise these data, improve our use of them, and support the continuation of their collection.

Author: Elizabeth Richardson

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