Category Archives: Data

Income deprivation and ethnicity

By Helena Tunstall & Stephanie Prady

Do deprivation indices based on means-tested benefits underestimate poverty in neighbourhoods with large minority ethnic populations? 

BorninBradford1Research has just been published which assesses how well the Income Deprivation Affecting Children Index (IDACI) identifies neighbourhood poverty in areas of Bradford with different ethnic populations.

This study was a collaboration between researchers at the University of York, the Bradford Institute for Health Research and CRESH. It compared neighbourhood IDACI scores, based upon social security benefit claims, to socio-economic data collected from families in the Born in Bradford (BiB) cohort study.

This study concludes that income deprivation measures based on means-tested benefits may underestimate deprivation in neighbourhoods with large minority ethnic populations due to the low take-up of benefits among poor families in some ethnic groups.

Continue reading Income deprivation and ethnicity

Empowering communities: An interactive tobacco and alcohol outlet density webmap for Scotland

Today we are launching an interactive webmap that allows users to map tobacco and alcohol outlet density, and related health outcomes, for neighbourhoods (‘datazones‘) across Scotland.  The underlying data we have collected and assembled can also be freely downloaded for use.  Our research from Scotland shows that outlet density matters for health:

  • areas with the highest alcohol outlet density have double the death rate of those with the lowest densities (see our blog postreport and infographic)
  • adolescents living in areas with the highest tobacco outlet density are almost 50% more likely to smoke than those with the lowest (see our blog post, paper and infographic).

ALCOHOL OUTLET DATA UPDATED 25 JUNE 2015:  Previous to this date the alcohol outlet density data had used an alternate measure of density than outlets per km2, resulting in values that were typically 30-40% lower than the actual value.  Whilst the figures have changed the general picture has not: an area of high density remains an area of high density.  The rest of the data are unaffected.


Continue reading Empowering communities: An interactive tobacco and alcohol outlet density webmap for Scotland

Smoking and Health in Scotland: key stats

smoking_infographic2Today we’re launching our hot-off-the-press infographic about Smoking and Health in Scotland.  In collaboration with Action on Smoking and Health (ASH) Scotland we’ve created this summary of some of the key statistics on smoking and health in Scotland, featuring some headline results from our own research.  Please use and circulate widely! Continue reading Smoking and Health in Scotland: key stats

Is multiple environmental deprivation related to population health in Portugal?

By Ana Isabel Ribeiro

In our recently published paper (open access version here) we describe the development of a multivariate measure of physical environmental deprivation for the 278 municipalities of Portugal, and demonstrate its strong relationship with mortality rates. Continue reading Is multiple environmental deprivation related to population health in Portugal?

Alcohol outlet densities correlate with alcohol-related health outcomes in Scotland: but so what?

By Elizabeth Richardson

In our recently-published study into alcohol outlets and health in Scotland we found strong correlations between the two: neighbourhoods with higher availability of outlets had higher rates of alcohol-related deaths and hospitalisations.  In fact, residents of neighbourhoods with the highest availability were more than twice as likely to die a drink-related death than those with the fewest outlets, all else* being equal (*deprivation and urban/rural status).

Altway, 2012
Source: under Creative Commons licence

But what does this actually mean? Continue reading Alcohol outlet densities correlate with alcohol-related health outcomes in Scotland: but so what?

Mapping life expectancy in Scottish Parliamentary Constituencies

By Helena Tunstall, Elizabeth Richardson & Jamie Pearce

New life expectancy at birth figures for 2011-2013 for Scottish Parliamentary Constituencies have just been released by National Records of Scotland (NRS). We’ve mapped and graphed these data to illustrate the latest geographical patterns of mortality in Scotland. Continue reading Mapping life expectancy in Scottish Parliamentary Constituencies

Are experimental studies always best?

Work has begun on our NIHR funded evaluation of Forestry Commission Scotland’s Woodlands In and Around Town (WIAT) scheme. WIAT aims to improve quality of life in towns and cities by bringing neglected woodlands into management, creating new woods and supporting people to use and enjoy their local woods. Our study, led by Catharine Ward Thompson at OpenSpace, is focused on whether changes to the local woodland environment affect people’s health. The WIAT evaluation is exciting partly because it’s a rare opportunity to ask what impact environment has on health, at a population level, via an experimental study.

The vast majority of evidence about how health and behaviour are affected by environment comes from cross-sectional studies. In cross-sectional studies, we measure both the environmental characteristic of interest (for example, how much green space there is in a neighbourhood), and the outcome of interest (for example, how healthy or happy the residents of that neighbourhood are) at the same time. Cross-sectional studies are great for suggesting links or associations between environmental characteristics and health or related behaviour, but they have many problems. In particular, we can’t be certain that the aspect of environment we are interested in causes the health outcome in question. In the case of green space and health for example, we worry that the apparent relationship between access to green space in a neighbourhood and good health among residents is really because the residents of greener neighbourhoods tend to be wealthier, and wealthier people are more likely to be healthier anyway. So, it might be that access to green space in a neighbourhood doesn’t cause better health, it’s just that healthier people are more likely to live in greener neighbourhoods.

Experimental studies are very different. In an experiment, we deliberately alter some aspect of the environment for one group of people (the intervention group), but not for another very similar group of people (the control group). We then compare what happens to health or related behaviour in the intervention and control groups. If health improves in the intervention group, but not in the control group, we can be more certain that the change in environment has caused the change in health. So, in our WIAT study, we’ll be comparing what happens to the health of communities whose woodlands are improved and promoted, with those whose woodlands are not. (That sounds a bit unfair on the ‘control’ communities but, in fact, they’ll be eligible to get their woods improved later).

A lot has been written recently about how important experimental studies are*, how much better they are for telling us ‘what works’ to improve health and behaviour, and how we need far more of them. The idea has taken hold, helped by research funding and by the fact that some key journals in public health and epidemiology now refuse to even peer review studies that are cross-sectional. Jim Dunn and Martin Bobak’s editorial* on taking over the editorship of JECH is a good indication of increased interest in experimental designs from leading journals. Mark Petticrew has also written* about it.

I am excited about the prospect of experimental studies being used to examine the impacts of environment on health and health-related behaviour. I believe that the characteristics of the places we live and work in can be a strong influence on our health and behaviour and, in turn, I think that environment could be an effective lever for improving population health and narrowing health inequalities. Experimental studies are, in theory, the best way of finding out if my ideas are right or not.

However, I do have a few concerns about the assumption that experimental approaches are always best for researching ‘what works’ to improve public health. Their strengths have been highlighted in the literature, but there has been relatively little critical thinking about them.

The processes by which environment influence our health and behaviour are complex and life long. Environment doesn’t simply determine health and behaviour; people and environments influence each other. Think about the cycling infrastructure in Copenhagen for example. The environment there enables and encourages people to cycle, so the city’s high rates of active travel are partly because of the environment. However, the environment is so conducive to active travel because the residents use it, protect it, value it and continue to improve it.

Our relationships with different aspects of environment are also formed over the whole of our lives. Catharine Ward Thompson’s work*, for example, shows that one of the strongest predictors of whether we visit woodlands as adults was whether we did so as children. That means just changing access to woodlands in the neighbourhood may not affect immediately, or at all, residents who don’t have ‘visiting the woods’ as part of their culture.

Do we know how long it will take for an environmental change to affect health and behaviour? My guess is that the time will vary by environmental characteristic and/or the health or behavioural outcome being measured. I think, in many cases, effects will be slow to materialise. Yet the reality of research, and research funding, is that it’s difficult to sustain an experiment for a long time. In turn, this might lead us, or perhaps other less critical audiences, to prioritise interventions on aspects of environment that show a quick effect, at the expense of those which may have a greater but slower effect. Worse, if brief experimental studies find no effect of environmental intervention on health, and we think experimental evidence is the best there is, it may lead to the assumption that environment does not affect health.

I worry that in the rush to use experimental designs to see ‘what works’ for public health, we have forgotten some of what we know about relationships between health and environment specifically, and about relationships between place and identity more broadly.  I think experiments are very important, but I’d like to see a more critical perspective.

What do you think?

*NB links to journal articles may require institutional/personal subscription to the journal