Some time back, someone (I forget who) pointed me to this report by Christopher Snowdon (Institute of Economic Affairs) on the relationship between the density of fast food outlets and obesity. It was of interest to me because the underlying theory linking fast food outlets to obesity is substantively the same as one of the key theories linking alcohol outlets and various measures of alcohol-related harm. That theory is known as availability theory, and posits that more outlets (fast food, or alcohol) in a particular area reduces the 'full cost' of the good (fast food, or alcohol), and therefore increases consumption (the straightforward consequence of a downward-sloping demand curve). The 'full cost' includes the price, as well as the cost of travelling to obtain the good. Both of those components of the full cost may be lower when there are more outlets. Price may be lower due to greater local competition, while travel cost may be lower because each consumer will likely live closer to the nearest outlet. The last component of availability theory is that because there is more consumption (fast food, or alcohol), there are more problems (obesity, or alcohol-related harms). This last component is essentially taken on faith.
Anyway, Snowdon summarises the literature analysing the relationship between fast food outlets and obesity, which is made up of 74 studies published between 2004 and 2017. I say summarise, rather than review, for good reason. Snowdon's report doesn't provide a critical appraisal of the quality of the included studies, nor does it attempt to synthesise from this literature, other than to conclude that:
Of the 74 studies identified, only fifteen (20%) found a positive association between the proximity and/or density of fast food outlets and obesity/BMI. Forty-four (60%) found no positive association, of which eleven (15%) found a negative (inverse) association. Fifteen (20%) produced a mix of positive, negative and (mostly) null results, which, taken together, point to no particular conclusion.
Of the 39 studies that looked specifically at children, only six (15%) found a positive association while twenty-six (67%) found no association and seven (18%) produced mixed results. Of the studies that found no association, five (13%) found an inverse relationship between fast food outlet density/proximity and childhood obesity/overweight...
Overall, the weight of evidence suggests that there is no association between obesity and either the proximity or density of fast food outlets to schools, homes and workplaces.
When Snowdon refers to the 'weight of the evidence', you can almost take him literally. He has effectively counted the number of studies on each side of the debate, and concluded that the side with more studies is correct. That is not how literature should be reviewed, as it takes no account of the quality of the methods or data in each study, nor the diversity (or lack thereof) in study contexts (most of the studies were conducted in the US).
To be fair to Snowdon, he does say that:
Science is not decided by sheer weight of numbers, but the fact that most studies in the literature have found no association between obesity/BMI and fast food outlet density/proximity strongly suggests that no such relationship exists. This conclusion is not based on an absence of evidence. There is plenty of evidence.
However, the second part of that quote seems to contradict the first part. Anyway, how could we do better? A quick and dirty assessment of the journals in which these 74 studies were published suggests to me that we might put more weight on those that found positive associations between fast food outlets and obesity, as they were published in high-quality journals like the American Economic Journal: Economic Policy, Health Economics, and Social Science and Medicine. Studies that found mixed or null results were published in (among others) Social Science and Medicine, Economics and Human Biology, American Journal of Public Health, and Journal of Urban Health. Maybe that's only a slight difference in the quality of journals though, and you might argue that there is greater publication bias towards statistically significant results in higher-quality journals. On the other hand, you'd expect the better journals to take a harder line on quality of analysis. A second alternative is to expect that more recently published articles are likely to have built on the learnings of earlier articles, and therefore should have more weight. In that case, we would tend more towards the mixed and null findings, as those that found positive associations tend to be older.
Both of those approaches are admittedly crude. A much better approach is to actually synthesise the literature properly. You could do this narratively, or you could apply meta-analysis, where the coefficient estimates are combined quantitatively to arrive at an overall measure of the relationship between variables (in this case, the relationship between fast food outlets and obesity). Meta-analysis is much more credible than simply listing the papers and counting them. It doesn't apply a crude statistically-significant-or-not approach, since both the coefficient estimates and the standard errors are included in the overall estimate. That way, we aren't ignoring or potentially misclassifying studies with large, but imprecisely measured, coefficients.
It seems to me that this literature on fast food outlets and obesity is ripe for a meta-analysis (although, here is one that focuses on childhood obesity). That might make a nice project for a suitably motivated and interested Honours or Masters student.
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