Physical activity phenotyping with activity bigrams, and their association with BMI.

Abstract:

Background:Analysis 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 person's activity levels change across (brief) time points. These variables can, for instance, differentiate between two people spending 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. Methods:We 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. Results:We found several associations between changes in bigram frequencies and BMI. For instance, a one 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% confidence interval (CI): -3.47, -1.26], after accounting for the time spent in sedentary, low, moderate and vigorous activity. Conclusions:Activity bigrams are novel variables that capture how a person's activity changes from one moment to the next. These variables can be used to investigate how sequential activity patterns associate with other traits.

journal_name

Int J Epidemiol

authors

Millard LAC,Tilling K,Lawlor DA,Flach PA,Gaunt TR

doi

10.1093/ije/dyx093

subject

Has Abstract

pub_date

2017-12-01 00:00:00

pages

1857-1870

issue

6

eissn

0300-5771

issn

1464-3685

pii

3902974

journal_volume

46

pub_type

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