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Analysing student eating habits


Analysing student eating habits

Scientists have for the first time used anonymous data from pre-payment food cards to get a unique insight into the eating habits of first year university students.

Data scientists from the Consumer Data Research Centre at the University of Leeds have been able to build a detailed picture of what 835 students ate, and when, by analysing the data linked to their pre-payment food cards.

The cards revealed what they were buying in the campus refectory and associated food outlets.

The analysis gives the most accurate picture to date of first year student diets. Many previous studies have used food diaries, but their accuracy can be variable because they rely on the student remembering exactly – and being honest about – what they have eaten.

Dr Michelle Morris, a University Academic Fellow in Health Data Analytics based at Leeds Institute for Data Analytics, said understanding student diet had public health implications.

Previous studies in the UK and the US have shown that “fresher” students are at risk of weight gain, probably as a result of the lifestyle changes that come with starting university.

In the US, they talk of the “Freshmen 15”, the 15lbs (6.8kg) that students put on. In the UK, research indicates the average student gains 7.7lbs (3.5kg).

The findings, Assessing diet in a university student population: A longitudinal food card transaction data approach, have been published in the British Journal of Nutrition.

The study, which pre-dated the coronavirus outbreak and followed the students aged 18 to 24 over their first semester (12 teaching weeks), revealed student eating habits which clustered around seven dietary behaviours:

  • Vegetarian: with popular purchases being salads, breakfast cereals, yoghurt and fromage frais and a notable absence of meat products
  • Omnivores: which included the most average amounts of all products purchased, with above average amounts of ice cream, desserts and cakes, breakfast cereals and fish.
  • Dieters: with above average purchases of soups, pasta, noodles and salad.
  • Dish of the Day: which included above average purchases of meat and meat products.
  • Grab and Go: which included above average purchases of sandwiches, crisps, nuts and eggs.
  • Carb Lovers: with bread, cheese, egg products and pasta being among the top picks.
  • Snackers: with confectionery, crisps, nuts being above average choices.

Dr Morris, said the dietary patterns were ranked on the basis of “healthfulness”, with vegetarian the most healthful and snackers being the least.

She added: “Our analysis shows that although some students followed one dietary pattern throughout the semester many switched between them.

“Some students moved from a more healthy to a less healthy pattern; for example,  some vegetarians switched to an omnivore diet; and vice versa with some of the students who started off as snackers – the least healthful diet – did move to the Dish of the Day which offered a more balanced range of food options.

“Worryingly perhaps, the most popular move was from a dieter pattern, to the snacking pattern.”

Females were found to be heavily represented among the vegetarians (88%) and dieters (80%) while the men dominated the dish of the day (84%) and grab and go (62%) diet patterns.

This information could be used to target information about healthier eating to students.
Dr Michelle Morris, Leeds Institute for Data Analytics

Dr Morris said the most popular dietary pattern amongst the slightly older students, those aged between 20 and 24, was the omnivore pattern of eating – that could be due to the fact that they may already have lived away from home and settled into a more varied dietary pattern.

She said: “The information from this analysis reveals the pattern of the students’ eating habits, and how that changes over time. That is information that could be used to target information about healthier eating to students.

“Research has shown that adult eating habits take root early in adulthood. So, time spent at University is a great time to encourage healthy eating behaviours that could remain with them for life.”

The research was funded by the Economic and Social Research Council through a Strategic Network for Obesity grant. Maintaining the anonymity of the students was of utmost importance at all stages of the research.

Notes to editor

For further information or interview requests, please contact University of Leeds Media Relations and Communications Officer David Lewis via d.lewis@leeds.ac.uk

Prioritising food establishment inspections

Prioritising food establishment inspections

Populations who frequently eat fast food and live within close proximity of unhygienic food establishments may be at higher risk of contracting foodborne illness than those who do not eat takeaways regularly – but which food establishments are most likely to be unhygienic?

Recent research by CDRC PhD student Rachel Oldroyd uses logistic regression to identify ecological determinants of non-compliant food outlets in England and Wales.  Rachel’s recent paper in Health & Place highlighted:

  • A clear gradient of association is observed between increased deprivation and the probability of non-compliance.
  • Food outlets in the most deprived areas are 25% less likely (OR = 0.75) to meet hygiene standards than those in the least deprived areas.
  • Takeaways, sandwich shops (OR = 0.504) and small convenience retailers (OR = 0.905) are less likely to be compliant than restaurants.
  • Food outlets in large conurbation areas are less likely (OR = 0.678) to meet hygiene standards than those located in cities and towns.
  • Outlets in deprived and urban areas, especially takeaways, sandwich shops and convenience stores should be prioritised for inspection.

You can read the full paper here.

Demographic profile of pedestrian flows: linking Huq mobile geo-data and SmartStreetSensor footfall data

Birds eye view of a crowd of people on street

Demographic profile of pedestrian flows: linking Huq mobile geo-data and SmartStreetSensor footfall data

Recent research conducted by Consumer Data Research Centre (CDRC) at UCL discussed the potentialities and limitations of football data and mobile geo-data in the context of retail location analysis.

Footfall data derived through SmartStreetSensor project is collected using a network of sensors. This data provides information about the volumes of pedestrian flows, but lacks the contextual insights on the origins of the population.

The geo-data provided by Huq Industries captures around 6% of the average footfall, but maintains a continuous list of locations visited by the users over long periods of time. This information can be used to study the demographics and consumer behaviours of the population.

The preliminary research summarised in this case study sugges linking the contextual information derived from geo-data to footfall counts in order to create a comprehensive understanding of the magnitudes and demographic profile of the pedestrian flows in the retail centres.

Please find the full report here