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Physical activity insights from mobile phone and accelerometer data

Physical activity insights from mobile phone and accelerometer data

This is a talk I gave at the "Overcoming Barriers to Movement and Physical Activity Seminar", organised by the Movement and Physical Activity Network at the University of Leeds.

I argue that we need good data in order to devise solutions for overcoming barriers. I cite work from two recent papers, one which utilises accelerometer data and one which used mobile phone app data.

The citations for the papers discussed in the talk:

Pontin, F., Lomax, N., Clarke, G. and Morris, M.A., 2021. Socio-demographic determinants of physical activity and app usage from smartphone data. Social Science & Medicine, 284, p.114235. https://doi.org/10.1016/j.socscimed.2021.114235

Clark, S., Lomax, N., Morris, M., Pontin, F. and Birkin, M., 2021. Clustering Accelerometer Activity Patterns from the UK Biobank Cohort. Sensors, 21(24), p.8220. https://doi.org/10.3390/s21248220

Nik Lomax

April 22, 2022
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  1. Physical activity insights
    from mobile phone and
    accelerometer data
    N I K L O M A X
    S C H O O L O F G E O G R A P H Y , U N I V E R S I T Y O F L E E D S
    N . M . L O M A X @ L E E D S . A C . U K

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  2. Overcoming Barriers to Movement and Physical Activity
    • We need data
    • How do patterns vary?
    • Can we better target interventions?

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  3. Accelerometers
    • Traditional study design
    • Short term data collection
    • Only good for acceleration
    based measurement
    • Often detailed demographics

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  4. Mobile phone based apps
    • Longer term collection
    • Greater equity
    • Multiple activity types
    • Secondary data
    • Missing context

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  15. The demographics of activity
    • Female users walk significantly fewer steps than males
    • Male users record both a higher average number of activities a day and a higher
    average number of different activities whilst using the app
    • Female users recorded longer duration activities on average than the male users.
    • Users living in more affluent areas had a higher average daily step count and
    recorded more diverse activity types
    • However, they record significantly fewer minutes of activity than the users living in
    less affluent areas

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  17. Overcoming Barriers to Movement and Physical Activity
    • We need data
    • How do patterns vary?
    • Can we better target interventions?
    • 23% of adults globally are not sufficiently active
    • 34% of men and 42% of women in the United Kingdom (UK)
    not active enough for good health
    • one in six UK deaths can be attributed to physical inactivity

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  18. Physical activity insights
    from mobile phone and
    accelerometer data
    N I K L O M A X
    S C H O O L O F G E O G R A P H Y , U N I V E R S I T Y O F L E E D S
    N . M . L O M A X @ L E E D S . A C . U K

    View Slide