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January 03, 2010

Do younger pupils really ‘mimic the habits of obese children in older classes’? Answer - probably not!

A tweat posted by @GuardianEdu yesterday (2 January 2010) attracted my interest:

‘Younger pupils mimic habits of obese children in older classes http://bit.ly/7KUEez’

The link takes you to the full news article published today in The Observer (3 January 2010) that is based on research conducted by a team from Ontario, Canada. Here’s some of the key extracts from the Observer article:

Children at schools where older students are obese or otherwise overweight are significantly more likely to suffer weight problems themselves, researchers report. For each one per cent increase in the prevalence of obese students aged 16 to 18 years, the odds of a student at 14 to 16 years old attending that school also being overweight increased significantly.

"It was the one risk factor that held true across every school we looked at," said Dr Scott Leatherdale, the chair of research at Cancer Care Ontario and lead investigator with the School Health Action, Planning and Evaluation System. "Schools that had a large number of obese younger students were disproportionately likely also to have a high percentage of overweight older students. The association was completely consistent."

"It could be that younger students look up to older students, and so emulate their sedentary behaviour and bad eating habits and do not judge the older children's body shape," he said. "Or it could be that the school doesn't encourage enough physical activity among its students, and the older students' weight issues are an indication of that.”’

The research from which these findings are taken is due to be published in the Journal of Youth Adolesence. Fortunately, the journal article itself is available to download as an ‘online early’ article at:

Leatherdale, S. T. and Papadakis, S. ‘A multi-level examination of the association between older social models in the school environment and overweight and obesity among younger students’, Journal of Youth Adolesence, DOI 10.1007/s10964-009-9491-z

In this instance, the news article does seem to broadly reflect the findings as reported in the journal article. As the authors conclude in the article:

‘[T]he junior students in our sample were more likely to be overweight or obsese if they attended a school with a high prevalence of senior students who are obese. … For each 1% increase in the prevalence of obese senior students at a school, the odds of a junior student at that school being obese increased (OR 1.19, 95% CI 1.16-1.24, p < .001). … This finding is consistent with previous empirical research which suggests that characteristics of the school a student attends can have important impact on their weight status.’

Having decided that the prevalence of overweight and obese senior students represents a risk factor in terms of junior pupils being overweight or obese, the authors conclude by arguing for the need to use indicators like this to develop more targeted school-based intervention programmes.

The statistical analysis upon which this article is based need not overly concern us here. For those interested, the authors used multi-level binary logistic regression to consider what factors (pupil-level and school-level) were associated with the chances of a pupil being overweight and also obese. The analysis itself, involving a sample of 12,049 grades 9-12 pupils from 76 Ontario secondary schools, seems to be technically correct. However, and as is often the case, it is the interpretation of the results of this analysis that are problematic. In this case, you don’t need to be a statistician to be able to identify some of the problems relating to the interpretation of the results from this study. Here’s some of the key ones:

First, the authors place a lot of emphasis on the importance of the school environment in providing an environment that influences levels of obesity in pupils. And yet, when reading the “fine print” of the study, the authors report that schools could only account for 1.8% of the variation in levels of obesity between pupils. In other words, school-level factors themselves would seem to have only a marginal influence on whether children are obese or not (with between 98.2% of the variation between children being associated with non-school based factors). The only reason why this finding is statistically significant is because of the huge sample size (n=12,049) where any difference, however minor, is likely to be statistically significant. This is therefore a good example of where findings may be statistically significant but not practically significant.

Second, the authors claim that with every one percentage point increase in the proportion of senior students who are obese, this increases the odds of junior pupils being obese by a factor of 1.19 (i.e. increasing their chances by 19%). This seems to be quite a notable relationship. However, quoting odds ratios like this can be misleading, especially when you’re dealing with only a small absolute number of children. In this case, the proportions of pupils in each school who were found to be obese were small, with only 6.5% of children categorised as obese on average within each school. In this instance, what therefore seems to be large changes in the odds of children becoming obese will only reflect very small changes in the actual numbers of pupils (in this case, literally, a handful of pupils).

Third, and even putting the above points to one side, there is a more fundamental problem relating to inferring a causal relationship from a correlation. While it may be true that the proportions of junior pupils in a school who are obese is correlated with the proportions of senior pupils who are obese, we cannot assume that there is any direct (or, indeed, indirect) causal relationship between the two at all. Unfortunately, this does not stop the authors from hypothesising wildly about how junior pupils may be emulating their senior counterparts. This is just irresponsible and misleading. Moreover, and in this case, it is what also generated the headline in The Observer news article – a headline with absolutely no evidence to substantiate it at all.

Fourth, there is actually a much simpler – and far more plausible – explanation for this correlation that the authors remarkably do not seem to recognize. It is not surprising that the proportions of junior and senior pupils tend to be similar within individual schools given that they tend to come from the same neighbourhoods or catchment areas. In this sense, any between-school variations found are likely to be due to variations in the socio-demographic nature of the catchment areas of the schools rather than anything that the schools themselves are doing.

Fifth, and finally, the authors do not make any distinction between different types of school-level factors; in particularly, those that are related to the school itself (the school ethos, the curriculum taught etc.) and those that are actually related to the wider neighbourhood in which a school is located and thus are  not influenced by the school at all (i.e. socio-demographic  characteristics – including levels of obesity – that may vary from school to school but that are not caused by the schools as such but simply reflect their different catchment areas).

This is an important distinction to make. In this case, the absence of such a distinction has lead the authors to making misleading claims regarding the existing and direct influence of the school environment on levels of obesity. This is not to say that schools cannot play an important role in helping to promote healthier lifestyles and reduce levels of childhood obesity but this is a different issue. The authors are focusing here on attempting to identify the existing influences that schools have.

So, here is another example of where the basic point that should have been drilled into any undergraduate student taking a research methods course – that correlation does not necessarily imply causality – seems to have been lost. In this present case, we cannot simply blame the sensationalist and misleading reporting of a journalist. As we saw, the news article broadly reflected the findings from the journal article itself. It may be, therefore, that part of the problem here is that as the research is based on a rather advanced and complex form of statistical modeling then people are going to be less likely to feel qualified in assessing the validity of the claims being made and thus more likely just to take the key findings ‘on trust’. However, and as demonstrated above, this is a dangerous approach to take and can easily lead to important policy decisions being made on the basis of false evidence.

Ultimately, this is why the peer-review process is so important in, hopefully, helping to identify and remove some of the more blatant cases of poor quality research. With this in mind, the key question we are left with is how did this article, with the claims it is making, get through the peer-review process of the Journal of Youth Adolescence seemingly unimpeded? Did none of the reviewers (or the editors) recognize and/or raise any of the concerns highlighted above?

December 16, 2009

Further analysis of GCSE results in England by DCSF. Good or bad news? Depends who’s reporting. ... And the news might not be news at all.

The DCSF (Department for Children, Schools and Families) in England released a new report yesterday providing more detailed analyses of GCSE attainment in England by pupil characteristics (for the report see:  http://www.dcsf.gov.uk/rsgateway/DB/SFR/s000900/index.shtml). I haven’t had time to read it yet but three points emerge from news coverage of this report that are already worth commenting on.

The first is political spin. The figures seem to be good or bad depending on who you listen to. For the government, the figures are encouraging. A tweat from the @DCSF yesterday declared: “New GCSE figures: attainment gap between those on free school meals and their peers has narrowed”.

However, positive stories are never as newsworthy as negative ones and so here’s how @bbceducation reported the findings in their own tweat that came out within a few hours of the one from the DCSF: “Poor white teenage boys in England have slipped further behind other youngsters in their GCSE results

So, here’s the first lesson – never trust any press release or news story to give you the full picture! You will always need to look at the evidence for yourself. However, two further lessons emerge when you do begin looking at the evidence. Infact we need look no further than the statistics reported in the press releases/news items accompanying these tweats to begin to find these lessons.

Both tweats imply notable changes in performance and yet the actual changes reported (and remember the statistics in the press releases/news items are the ones that have been cherry-picked to back up their respective positions) are marginal. Take the finding on free school meals (FSM) for example. On the DCSF’s website, they report that the proportion of those pupils eligible for FSM gaining the expected level (five good passes at GCSE) rose by 3.4 percentage points over the last year. As they go onto claim, this is: “a faster improvement than the 3.1 percentage point rise for non-FSM pupils”.

BBC Education did little better in relation to their news story – this time choosing to emphasise the negative results. The gap between poor white boys (those in eligible for FSM) and other white boys (those not eligible for FSM) widened from 29.8 percentage points to 31.6 percentage points. A whopping 1.8 percentage point increase!

So here are the two further lessons from this cursory review of tweats and press releases/news stories. The first is the need for all those involved to be much clearer in their headline reporting of the actual size of any effects found. Most people won’t even go beyond the headlines and will thus simply be left with the impression that either things are getting better (the DCSF line) or worse (the BBC line) for young people from disadvantaged backgrounds. And yet in both cases, the change is marginal. Unfortunately, marginal changes are no good to politicians or the media.

The second lesson is the need to step back and look at trends over time. We can expect minor fluctuations in statistics year-by-year, simply due to random variation in the make-up of any particular cohort of school pupils. Without further information we have no way of knowing whether these (very minor) changes reported do actually represent an underlying trend or are simply random fluctuations.

So, the next thing I need to do – and what I’d advise everyone else to do as well – is to read the full report for myself; only then can we develop a more balanced view of what is going on and determine whether some or all of these findings are actually indicative of real trends at all or may just reflect random fluctuation.

October 31, 2009

Governments, evidence and politics – some reflections on the UK Govt’s sacking of its chief scientific drugs adviser

There are plenty of examples from education of the UK government introducing major policy initiatives without any evidence to suggest whether they are going to work or not. Indeed, there are also examples where policies have been introduced despite overwhelming evidence to the contrary. However, the decision of the government to sack its chief scientific drugs adviser – Professor David Nutt – is perhaps the most stark recent example of the precarious place of evidence-based policy.

Professor Nutt’s position became untenable after he accused government ministers of "devaluing and distorting scientific evidence" regarding the misuse of illicit drugs after the government decided to reclassify cannabis from a Class C to a Class B drug against the advice of its Advisory Council on the Misuse of Drugs. Reacting to his sacking, and quoted in the Guardian (see: http://bit.ly/3CCi2W), Professor Nutt explained that the Prime Minister had ‘made up his mind’ to reclassify cannabis despite evidence to the contrary: "Gordon Brown comes into office and, soon after that, he starts saying absurd things like cannabis is lethal... it has to be a class B drug. He has made his mind up."We went back, we looked at the evidence, we said, 'No, no, there is no extra evidence of harm, it's still a class C drug.' He said, 'Tough, it's going to be class B'. [...]  He is the first Prime Minister, this is the first government, that has ever in the history of the Misuse of Drugs Act gone against the advice of its scientific panel.""And then it did it again with ecstasy and I have to say it's not about [me] overstepping the line, it's about the government overstepping the line. They are making scientific decisions before they've even consulted with their experts.”

There are two points worth drawing out from this example. The first, clearly, is the worrying trend of governments (in plural, let’s not just blame this on the present administration) to play fast and free with evidence. The fact that the government can show such disregard for the available evidence, and for its own scientific advisers, is deeply worrying. Let’s be clear, governments have always used evidence selectively; happy to quote it and take the moral high ground when it fits in with its latest policy initiative and yet equally happy to blatantly ignore it when it doesn’t suit. Witness, for example, the government’s reaction just last week to the publication of the findings of the Cambridge Review of Primary Education (see: http://bit.ly/J0xN).

However, and here’s the second point, it is important that in our concern  with this latest sacking, we don’t find ourselves occupying the equally untenable position whereby government policy is simply based on evidence with political influences excised completely. After all, policy-making is a complex and inherently political process where value judgements need to be made. The use of evidence is only one component of this process.Take, for example, the issue of boys’ underachievement in school. Let’s assume we have strong and rigorous evidence that a particular classroom-based approach can significantly increase boys’ educational attainment scores. While we may have the evidence that this approach is effective (in terms of increasing boys’ attainment), there remain important and legitimate political considerations to address before we simply press ahead and roll out the approach across all schools.

For example, what is the effect of this approach on girls and their educational attainment? It could be that the approach is based upon ‘masculinising’ the curriculum and classroom to make education more appealing to boys. However, this may then alienate girls and thus adversely effects their attainment. Moreover, and in this case, we also need to ask what types of masculinity are being promoted for boys to engage with and aspire to? While such forms of masculinity may be proven to increase boys’ educational attainment, they may have adverse consequences for other aspects of their lives, including their socio-emotional development.

The point is that while governments need to make best use of evidence, they also need to act politically (and actually can’t avoid doing so). However, even political decisions need to be based on evidence rather than mere unsubstantiated belief. In the example above, we would want some evidence of how the particular approach to raising boys’ attainment was actually impacting upon girls. Similarly, we’d also want to ascertain whether there is evidence to support our concerns that the dominant forms of masculinity being promoted were adversely impacting on other aspects of the boys’ development.

Of course good evaluative designs of educational interventions not only focus on the intended effects of the initiative in question but also their potentially unintended (and possibly adverse) effects. In this sense, the design of an evaluation and the outcomes to be measured need to be informed by theoretical and political considerations. It is in this sense that while political decisions need to be informed by evidence, the creation of evidence also needs to be informed by political decisions. Politics and evidence are inherently related.