Physical Activity Phenotyping With Activity Bigrams, And Their Association With BMI

Millard, L. A.; Tilling, K.; Lawlor, D. A.; Flach, P. A.; Gaunt, T. R.

doi:10.1101/121145

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bioRxiv · 10.1101/121145

Physical Activity Phenotyping With Activity Bigrams, And Their Association With BMI

Millard, L. A.·Tilling, K.·Lawlor, D. A.·Flach, P. A.·Gaunt, T. R.

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Abstract

BackgroundAnalysis of physical activity usually focuses on a small number of summary statistics derived from accelerometer recordings: average counts per minute, and the proportion of time spent in moderate-vigorous physical activity or in sedentary behaviour. We show how bigrams, a concept from the field of text mining, can be used to describe how a persons activity levels change across (brief) time points. These variables can, for instance, differentiate between two people with the same time in moderate activity, where one person often stays in moderate activity from one moment to the next and the other does not.\n\nMethodsWe use data on 4810 participants of the Avon Longitudinal Study of Parents and Children (ALSPAC). We generate a profile of bigram frequencies for each participant and test the association of each frequency with body mass index (BMI), as an exemplar.\n\nResultsWe found several associations between changes in bigram frequencies and BMI. For instance, a 1 standard deviation decrease in the number of adjacent minutes in sedentary then moderate activity (or vice versa), with a corresponding increase in the number of adjacent minutes in moderate then vigorous activity (or vice versa), was associated with a 2.36 kg/m2 lower BMI [95% CI: -3.47, -1.26], after accounting for the time spent at sedentary, low, moderate and vigorous activity.\n\nConclusionsActivity bigrams are novel variables that capture how a persons activity changes from one moment to the next. These variables can be used to investigate how sequential activity patterns associate with other traits.\n\nKey MessagesO_LIEpidemiologists typically use only a small number of variables to analyse the association of physical activity with other traits, such as the average counts per minute and the proportion of time spent in moderate-vigorous physical activity or being sedentary.\nC_LIO_LIWe demonstrate how activity bigrams can be used as a set of interpretable variables describing how a persons activity levels change from one moment to the next.\nC_LIO_LITesting the association of activity bigrams with exposures or outcomes can help us gain further understanding of how physical activity is associated with other traits; with further research they might provide evidence for more refined public health advice.\nC_LI

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Millard, L. A., Tilling, K., Lawlor, D. A., Flach, P. A., Gaunt, T. R.. 2017-03-28. Physical Activity Phenotyping With Activity Bigrams, And Their Association With BMI. https://doi.org/10.1101/121145

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