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Smartphone Apps and Activity – tracking trends in who, how and when we move

Someone doing up a shoelace and wearing a fitness tracker watch

Smartphone apps and activity – tracking trends in who, how and when we move

The advantages of being physically active have never been more apparent, with proven benefits across a wide range of health conditions. Traditionally, we might consider the beneficial role of physical activity to be in reducing obesity incidence and preventing non-communicable diseases, such as cardiovascular disease and type 2 diabetes. However, the COVID-19 pandemic has thrown further positives into the spotlight, as being physically active has been shown to reduce the risk of severe COVID-19 outcomes. Moreover, lockdowns and state-sanctioned time for exercise highlighted the importance of physical activity to mental health and wellbeing.

Physical inactivity is responsible for 1 in 6 deaths in the UK (equivalent to the risk from smoking1), with 1 in 3 men and 1 in 2 women not meeting the recommended 150 minutes of moderate to vigorous activity a week1. To reduce physical inactivity, we need to identify and remove the barriers to being active. These barriers are diverse and wide ranging, varying from person to person. Examples include, but are not limited to: increasingly sedentary occupations, time or monetary constraints and environments that do not support activity.

To best identify what and where these barriers to being active are, we need to establish a good understanding of where, when and how people are active. However, studies investigating physical activity behaviour are typically limited by sample sizes, small study areas and shorter study durations.

Increasingly, individuals are monitoring their own activity and fitness levels using smartphone apps or wearable trackers such as Fitbit, Garmin or smartwatches. Secondary use of these consumer data can provide researchers with new insights into physical activity behaviour. In this research, we use secondary app data provided by FUELL Ltd‘s Bounts app (available for use by researchers via application to the CDRC). We evaluate how useful secondary smartphone data are in providing insight into how active the public are. To do this, we first need to assess how representative app users are of the population as a whole. Finally we uncover key activity behaviours associated with different age and gender user profiles.

The app – who is using it?

The Bounts app was commercially available on all major app provider stores, with users earning points for activities which could later be exchanged for vouchers and prizes. All user data is pseudonymised and no identifiable user information is shared with the researchers. Additionally, data is only accessible to those with data security training and in a data secure environment.

We used the data of 30,804 app users who recorded seven or more days of activity in 2016. With an average user age of 39, women make up a significantly larger proportion of app users (77.7% of users). 43.8% of users provided a postcode district which we linked to the Office for National Statistics socioeconomic classification. Unlike traditional studies, which tend to underrepresent lower socio-economic groups, we found there was no substantial socioeconomic difference in the areas where Bounts users lived compared to the general population.

Research highlights

Seasonal and weekly trends in physical activity behaviour

Users recorded on average 218 days of activity, which is substantially longer than the typical seven-day data collection period in traditional physical activity studies. Thanks to this long monitoring period, we were able to observe distinct patterns in activity behaviour across weekly and seasonal timeframes.

Across the year, we can see the role daylight saving plays, with a higher number of activities recorded by users over the summer months when evenings are longer, dropping off in autumn as the days get shorter (Figure 1).

Figure 1 – Seasonal trend heatmap of total daily activity recorded by all app users
Figure 2 – Heatmap of total daily activity recorded by all app users standardised by week, highlighting weekly patterns of behaviour

We can also see a weekly pattern in activity behaviour with the highest number of activities recorded mid-week, peaking on Tuesdays (Figure 2). Higher weekday activity levels are suspected to be functional activity around commuting behaviours. This goes against the ‘weekend warrior’ theory that individuals tend to exercise more on the weekends and less on weekdays.

A higher level of functional activity is associated with women and those in less affluent socioeconomic groups. This corresponds to our user sample which has a high proportion of women and captures users from less affluent socioeconomic groups, who are usually underrepresented in physical activity studies.

Who is meeting the physical activity guidelines?

For each week that a user recorded activity, we calculated whether the culmination of this activity was enough to meet physical activity guidelines of 150 minutes of moderate to vigorous activity per week. This includes any activity with greater or equal intensity to brisk walking.

Despite the known health benefits, the overall proportion of weeks meeting these physical activity guidelines was low. The youngest and oldest users were the least likely to meet the guidelines, with those aged 35 to 44 most likely to meet the sufficiently active threshold.

Men were almost twice as likely to meet the guidelines, with 24.2% of weeks recorded by male users classed as adequately active compared to 12.4% of weeks recorded by female users. Additionally, living in the most affluent area compared to the least affluent (in terms of employment), improved the odds of recording an active week by almost 5%.

How useful are secondary smartphone data?

Secondary smartphone data are an invaluable tool to provide new insights into physical activity and other health behaviours, as they give a breadth and depth of detailed data not available from other methods.

On the flip side, using these data requires careful consideration, including meticulous implementation of data anonymity and ethics, attention to data handling and cleaning processes, and skilled training to be able to handle such a large detailed dataset. Used in tandem with more traditional primary data collection studies, secondary smartphone app data have the capability to address some of the most complex questions around physical activity behaviour.  We are still very much in the infancy of using these data and have just scratched the surface of their full potential.

Read the full paper: Pontin F, Lomax N, Clarke G, et al. Socio-demographic determinants of physical activity and app usage from smartphone data. Social Science & Medicine 2021: 114235.

References

1. Public Health England. Physical activity: applying All Our Health.  2019.

New partnership pilots trials to help change eating habits

New partnership pilots trials to help change eating habits

What we choose to put into our shopping baskets and how we make those choices will come under the microscope in a series of pilot trials designed to encourage healthy and sustainable diets.

Data analysts from the University of Leeds have joined forces with social impact organisation, the Institute of Grocery Distribution (IGD), to test different ways to encourage healthy and sustainable eating.

They are working in partnership with 20 leading retailers and manufacturers, including Morrison’s, Sainsbury’s and Aldi, to trial different strategies, including signposting better choices, the positioning of products in shops and online and the use of influencers and recipe suggestions.

Some have already begun to use some of those techniques in real-life settings as part of the research designed and implemented by the Leeds Institute for Data Analytics (LIDA) and the Consumer Data Research Centre (CDRC).

Researchers from LIDA and CDRC will analyse the results by capturing and measuring sales data from each intervention, enabling the project group to see exactly what is going on in people’s shopping baskets and assess what truly drives long-term behaviour change.

Dr Michelle Morris, who leads the Nutrition and Lifestyle Analytics team at LIDA and is a CDRC Co-Investigator, said: “I am passionate about helping our population move towards a diet that is both healthier and more sustainable. I believe that unlocking the power of anonymous consumer data, collected by retailers and manufacturers, is a really important step towards this goal.

“Working with the IGD and its members to evaluate their healthy and sustainable diets programme is very exciting – testing strategies to change purchasing behaviour and evaluating the wider impact of these changes.”

The pilot trials have been funded by IGD and form a key part of the charity’s Social Impact ambition to make healthy and sustainable diets easy for everyone.

Hannah Pearse, Head of Nutrition at IGD, said: “We want to lead industry collaboration and build greater knowledge of what really works. Our Appetite for Change research tells us that 57% of people are open to changing their diets to be healthy and more sustainable, and they welcome help to do it. But we also know that people don’t like to be told what to do and information alone is unlikely to change behaviour.

“We believe consumers will make this transition if we make it easier for them; that’s why we are delighted to be partnering with our industry project group and our research partners at the University of Leeds, to pilot this series of interventions over the coming months. The team at LIDA are experts in capturing, storing and analysing big data and have a variety of academic specialties that will be critical for this work.”

The work being carried out by CDRC researchers at the University of Leeds is unique because it will use the secure infrastructure at LIDA to allow retailers and manufacturers to share anonymised transaction data over a sustained period of time.

It is hoped that the results of the first pilot trial will be published towards the end of this year.

Celebrating collaboration: the CDRC Masters Dissertation Scheme

Celebrating collaboration: the CDRC Masters Dissertation Scheme

Celebrating collaboration: the CDRC Masters Dissertation Scheme. Thursday 29th April 2021, 10:30-15:00.

The CDRC Masters Dissertation Scheme, now in its tenth year, has been successfully run by the Consumer Data Research Centre for the last seven years. The event celebrated the success of the scheme, and explored the changing nature of academic-industry collaboration. Masters students who had gone through the scheme presented project case studies, and a selection of alumni spoke of the positive impact the scheme had had on their data science careers. A panel session rounded off the event with a discussion of the possibilities and ambitions for the next seven years of the Masters Dissertation Scheme. The event was attended by industry partners, MDS alumni, and the CDRC team including Paul Longley, Alex Singleton, and Jonathan Reynolds.

Speaker biographies

Programme

1030-1130: The Business of Engagement. Session recording (Longley 0:06, Dugmore 7:05, Reynolds 28:27, Squires 41:21)

  • Introduction & welcome: Professor Paul Longley, Director, CDRC
  • The evolution of academic-industry collaboration: Keith Dugmore, Demographic Decisions. Slides
  • CDRC: Where are they now? MDS 7 years on: Dr Jonathan Reynolds, Deputy Director (Oxford), CDRC. Slides
  • The business of engagement: the firm’s perspective: Martin Squires, Director of Advanced Analytics, Pets at Home. Slides

1145-1245: Alumni presentations. Session recording (Murage 2:16, Davies 25:10, Tonge & Montt 45:53)

  • Nombuyiselo Murage, Tamoco. Dissertation at Tamoco. MSc Geographic Data Science, University of Liverpool. Slides
  • Alec Davies, Pets at Home. Dissertation at Sainsbury’s. MSc Geographic Data Science, University of Liverpool, PhD Geographic Data Science. Slides
  • Christian Tonge, Movement Strategies. MSc Geographic Data Science, University of Liverpool, and Cristobal Montt, Movement Strategies. MSc Data Science, City, University of London. Dissertations at Movement Strategies. Slides

1400-1505: Alumni presentations (continued) and panel discussion. Session recording (Ushakova 1:48, Samson 21:29, Panel 37:26)

  • Alumni presentation: Dr Anastasia Ushakova, Senior Research Associate, University of Lancaster. Dissertation at British Gas.
    MSc Public Policy, UCL; PhD Computational Social Science. Slides
  • Alumni presentation: Nick Samson, Associate Director, CBRE. Dissertation at British Gas. MSc Geographic Information Science, UCL. Slides
  • Panel Discussion. The next 7 years. Achievements and ambitions: Alex Singleton, Deputy Director (Liverpool), CDRC;
    Samantha Hughes, Analytics Innovation Manager, Avon; Martin Squires, Director of Advanced Analytics, Pets at Home.
  • Thanks & conclusion: Professor Paul Longley, Director, CDRC

Nick Samson, 2014 MDS alumnus. Dissertation at British Gas. Project title: Can smart meters save consumers and British Gas money and carbon by pinpointing which consumers are most likely and best placed to install insulation in their homes?

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