Diet

All visualisations on this page were made using data collected by PointX on Public Health England website which can be found here.

https://sadiakd.carto.com/builder/98a9494c-cd18-11e6-866c-0e3ff518bd15/embed

Note if legend does not appear on the map, please enlarge screen.

Figure 3.1 – London choropleth map illustrating number of fast food outlets per 1000 people per borough

Choropleth map analysis
The map shows the density of Fast Food and Takeaway Outlets, Fast Food Delivery Services, Fish and chip shops. It can be seen that the darkest areas are located near the center, where it is likely to have more demand for fast food outlets. If compared to the obesity map, however, it can be seen that higher obesity prevalence areas which are expected to have more outlets are actually light in color. The color scale may be a little misleading, as City of London stands out from the rest with a count of 38.4 per 1000 people. Camden and Westminster, though colored in the same color, are still 1.44 and 2.05, respectively.

In addition, this data is calculated based on the population, which signifies that the figures used as ‘population’ are residents rather than commuters to the area where the outlets are. Considering City of London, for example, whose value had to be replaced to the next highest value because it was too large, demonstrates that these outlets concentrate in areas where there are many people during the day rather than during the night. Hence, calculating the number of fast food outlets in proportion to the population may not sufficiently reveal the relationship with the actual residents of a particular area.

Figure 3.2 – Scatter Plot illustrating the correlation between percentage of obesity and number of fast food outlets.

Spearman’s Rank Correlation Coefficient (SRCC): -0.0954 (3 s.f.)

Scatter plot analysis
Spearman’s rank correlation coefficient is -0.0954 which means that there is a very weak correlation. By looking at the values on the graph, it is also quite apparent that numbers are all within the same range. The values range from 0.24 to 1.99. Clearly the visualisation does not show any effect of fast food on obesity. However, from this data and visualisation it we should not conclude that there is no correlation, for there are various limitations of the data and visualisation.

Limitations of Fast Food Outlet Data
Unfortunately it was hard to identify the year the count of fast outlets was collected. The publishing date was 2006 which is fairly old, considering the growth of certain businesses and emergence of new ones over the past decade. Hence there is a possibility that the fast food outlet count from before 2006 is not large enough to correspond to the obesity rates, which are taken from 2013-2015.

Another limitation of the data and perhaps the most important is the categorisation of fast food. According to Public Health England who published the data, ‘“fast food” refers to food that is available quickly, therefore it covers a range of outlets that include, but are not limited to, burger bars, kebab and chip shops and sandwich shops.’ This indeed is actually quite a diverse range of food, with very different ingredients, nutritional values, and portion sizes. Question arises to whether the sole criterion of ‘time’ spent on cooking and eating is sufficient to decide the healthiness of food.

Other candidates for fast food are food provided in restaurants, takeaways and home delivery. Ready-made sandwiches at coffee shops can be termed fast food as well, though not sold in a shop under the category of ‘fast food’. Public Health England mentions this issue, stating that ‘restaurant or café which would mean they are not considered here despite selling similar types of food to those included in this analysis.’ Similarly, it mentions that bakeries can be a type of fast food provider as well, though they are not included in the analysis. If these were counted, both the distribution of different types of these ‘fast food’ outlets will be revealed and perhaps a more comprehensive picture of the relationship between outlets and health of local residents.

Influence of Fast Food on Obesity
‘People generally have easy access to cheap, highly palatable and energy-dense food frequently lacking in nutritional value, such as fast food.’ (National Obesity Observatory)

There was a controversial film called ‘Super Size Me’ in 2004. In the documentary, the director does an experiment on himself to see what would happen if he only ate food from McDonalds for 30 days. The result is that he gains excessive weight and concludes that McDonalds is unhealthy. However, there are some people who dispute this result by saying that his portion sizes were abnormal, and that it is not the content itself but rather the amount of calories he was taking in, not only from the food but also from the shakes. (McDonalds UK) While it can be said that this authentic type of fast food is high in calories and low in nutritional value, that is a characteristic of a particular type of food rather than the way it is processed.

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References

Gov.uk. (2016). Density of Fast Food Outlets in England. [online] Available at: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/578044/Fast_food_metadata_and_summary_local_authority_data.xlsx [Accessed 18 Jan. 2017].

McDonald’s Press Releases Section – Press Release August, 2004 Page. [online] Available at: https://web.archive.org/web/20071012135323/http://mcdonalds.co.uk/pages/global/supersize.html [Accessed 18 Jan. 2017].

noo.org.uk. (2017). Obesity and the Environment. [online] Available at: https://www.noo.org.uk/uploads/doc/vid_15683_FastFoodOutletMap2.pdf [Accessed 18 Jan. 2017].