There is no readily-available dataset of the number of fast-food outlets, but it doesn't take much effort to create one. The Food Standards Agency maintains the Food Hygeine Rating System (FHRS) service, covering England, Wales and Northern Ireland. FSA data records the names and types of any unit serving food that will be rated for its hygeine standards by local councils, as well as other information such as addresses, hygiene rate, and date of inspection. This includes units such as restaurants, takeaways, shops, food vans, schools, hospitals and workplace canteens.
If we're going to create a list of fast-food outlets, the question remains how to define "fast-food". Should it simply cover any takeaway? If so, should sandwich shops be included? And what about outlets classed as "restaurants" but serve what is typically referred to as "junk food"? There is no strict definition, so any result will be open to interpretation. If we are transparent about the method, however, this can reduce uncertainty.
Based on the fields available in the FHRS data we've used the following method to create a dataset of fast-food outlets across Northern Ireland.
- Include any unit marked with the business type 'takeaway/sandwich shop'
- Include all McDonalds, Kentucky Fried Chicken/KFC, Subways, Dominos and Burger King by name
- Include any restaurant/cafe/canteen with "burger", "chip", "kebab" (most of these were captured with the takeaway search, this is just to make sure)
Big brands such as McDonalds and KFC are nearly always recorded as "restaurants/cafés", rather than as a takeaway in the FHRS data, so it seems important that they are included by name. It's likely that the different recording is due to the need for a different type of hygiene inspection to take place in a sit-in rather than a solely take-out unit. We don't include mobile catering units either, as though they have a registered address, they don't have a fixed location for serving food.
As we're able to republish data from the FHRS dataset thanks to its open licence, you can look at our dataset for yourself and see if this has been a good method to capture fast-food outlets.
This method found 1,667 matching units across Northern Ireland. From this, analysis of the density of outlets can be determined (i.e. the number of outlets per 100,000 residents). The above map shows the density across Northern Ireland by Local Government District. It ranges from 69.3 outlets per 100,000 people (Ards and North Down), to 118.9 (Belfast). The Northern Ireland average is 90 outlets per 100,000 people. This is slightly higher than the 88 per 100,000 that Public Health England found across England, but using a different methodology.*
Associations between this fast-food outlet density measure with other factors, such as deprivation and measures of diet-related health and disease prevalence, can be investigated using other publicaly-available data.
Is there an assocation of circulatory disease death rates and the fast food outlet density in across council areas? There is a clear positive correlation.
Standardised Circulatory Disease Death Rate Data from NISRA
There is also a similar correlation with childhood obesity rates (the percentage of Primary 1 children classified as 'obese')
Childhood Obesity Rate Data from Department of Health Sub-Regional Health Inequalities
These, however, are associations, and not clear demonstration of relationships or cause and effect. A simple study of this kind cannot prove either that the prevalence of fast-food outlets leads to a higher level of consumption of takeaways and poorer diets (though it might indicate it), nor can it prove that the number of takeaways nearby is a cause of poor health outcomes.
Though clear links between poor diets, which include a high level of takeaway consumption (as well as other lifestyle and genetic factors) and health outcomes have been evidenced, drawing a link between higher exposure to fast food outlets as a cause of coronary heart disease, or obesity, is less certain, so do interpret these demonstrations with caution.
More focussed studies show that the prevalence of fast-food outlets around workplaces is a stronger influence on increased takeaway food consumption (and marginally higher BMI levels) than being near to where people live. We have used resident population numbers to calculate density (and the health indicators are also residence, rather than workplace, based), so cannot account for the differences in where people work and where they live between each council area.
Also, there will be varying amounts of custom from one fast-food outlet to another in our database. It's possible that while an area may have more outlets per person, they do less overall trade than outlets in another area, so while the density will be higher the amount of takeaways consumed in the area could be similar or potentially lower.
Other factors may have more of an influence on indicators such as heart disease and childhood obesity other than takeaway consumption and how many fast-food outlets are nearby. It may be the case that there are more fast-food outlets the more socially and economically deprived an area is, which is a confounding factor as deprivation is also a high predictor of poorer health outcomes (commonly referred to as health inequalities). The correlation between social deprivation and fast-food density is as clear as it is for the above health outcomes.
Multiple Deprivation Measure data from NISRA
And finally, in some cases, there is no clear correlation between takeaway density and poor health outcomes, where it may have been expected. For example, there seems to be no relationship between the density of fast-food outlets and coronary heart disease prevalence.
Coronary Heart Disease Prevalence data from NISRA
* Public Health England use a different approach in qualifying fast-food outlets. From the Ordnance Survey 'PointX' database (which does not cover Northern Ireland), PHE extracted commercial units in England maked as 'Fast Food and Takeaway Outlets', 'Fast Food Delivery Services', and 'Fish and chip shops'. This can result in some of the same limitations that our analysis faces, as well as some different limitations. PHE also exclude data for the City of London from their analysis, due to the relatively high number of units but low resident population. For full details of the PHE methodology, see their site.