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Adherent Use of Digital Health Trackers Is Associated with Weight Loss
We study the association between weight fluctuation and activity tracking in an on-line population of thousands of individuals using digital health trackers (1,749 ≤ N ≤ 14,411, depending on the activity tracker considered) with millions of recorded activities (119,292 ≤ N ≤ 2,221,382) over the year...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4822791/ https://www.ncbi.nlm.nih.gov/pubmed/27049859 http://dx.doi.org/10.1371/journal.pone.0152504 |
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author | Pourzanjani, Arya Quisel, Tom Foschini, Luca |
author_facet | Pourzanjani, Arya Quisel, Tom Foschini, Luca |
author_sort | Pourzanjani, Arya |
collection | PubMed |
description | We study the association between weight fluctuation and activity tracking in an on-line population of thousands of individuals using digital health trackers (1,749 ≤ N ≤ 14,411, depending on the activity tracker considered) with millions of recorded activities (119,292 ≤ N ≤ 2,221,382) over the years 2013–2015. In a first between-subject analysis, we found a positive association between activity tracking frequency and weight loss. Users who log food with moderate frequency lost an additional 0.63% (CI [0.55, 0.72]; p < .001) of their body weight per month relative to low frequency loggers. Frequent workout loggers lost an additional 0.38% (CI [0.20, 0.56]; p < .001) and frequent weight loggers lost an additional 0.40% (CI [0.33, 0.47]; p < .001) as compared to infrequent loggers. In a subsequent within-subject analysis on a subset of the population (799 ≤ N ≤ 6,052) with sufficient longitudinal data, we used fixed effect models to explore the temporal relationship between a change in tracking adherence and weight change. We found that for the same individual, weight loss is significantly higher during periods of high adherence to tracking vs. periods of low adherence: +2.74% of body weight lost per month (CI [2.68, 2.81]; p < .001) during adherent weight tracking, +1.35% per month (CI [1.26, 1.43]; p < .001) during adherent food tracking, and +0.60% per month (CI [0.44, 0.76]; p < .001) during adherent workout tracking. The findings suggest that adherence to activity tracking can be utilized as a convenient real-time predictor of weight fluctuations, enabling large-scale, personalized intervention strategies. |
format | Online Article Text |
id | pubmed-4822791 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-48227912016-04-22 Adherent Use of Digital Health Trackers Is Associated with Weight Loss Pourzanjani, Arya Quisel, Tom Foschini, Luca PLoS One Research Article We study the association between weight fluctuation and activity tracking in an on-line population of thousands of individuals using digital health trackers (1,749 ≤ N ≤ 14,411, depending on the activity tracker considered) with millions of recorded activities (119,292 ≤ N ≤ 2,221,382) over the years 2013–2015. In a first between-subject analysis, we found a positive association between activity tracking frequency and weight loss. Users who log food with moderate frequency lost an additional 0.63% (CI [0.55, 0.72]; p < .001) of their body weight per month relative to low frequency loggers. Frequent workout loggers lost an additional 0.38% (CI [0.20, 0.56]; p < .001) and frequent weight loggers lost an additional 0.40% (CI [0.33, 0.47]; p < .001) as compared to infrequent loggers. In a subsequent within-subject analysis on a subset of the population (799 ≤ N ≤ 6,052) with sufficient longitudinal data, we used fixed effect models to explore the temporal relationship between a change in tracking adherence and weight change. We found that for the same individual, weight loss is significantly higher during periods of high adherence to tracking vs. periods of low adherence: +2.74% of body weight lost per month (CI [2.68, 2.81]; p < .001) during adherent weight tracking, +1.35% per month (CI [1.26, 1.43]; p < .001) during adherent food tracking, and +0.60% per month (CI [0.44, 0.76]; p < .001) during adherent workout tracking. The findings suggest that adherence to activity tracking can be utilized as a convenient real-time predictor of weight fluctuations, enabling large-scale, personalized intervention strategies. Public Library of Science 2016-04-06 /pmc/articles/PMC4822791/ /pubmed/27049859 http://dx.doi.org/10.1371/journal.pone.0152504 Text en © 2016 Pourzanjani et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Pourzanjani, Arya Quisel, Tom Foschini, Luca Adherent Use of Digital Health Trackers Is Associated with Weight Loss |
title | Adherent Use of Digital Health Trackers Is Associated with Weight Loss |
title_full | Adherent Use of Digital Health Trackers Is Associated with Weight Loss |
title_fullStr | Adherent Use of Digital Health Trackers Is Associated with Weight Loss |
title_full_unstemmed | Adherent Use of Digital Health Trackers Is Associated with Weight Loss |
title_short | Adherent Use of Digital Health Trackers Is Associated with Weight Loss |
title_sort | adherent use of digital health trackers is associated with weight loss |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4822791/ https://www.ncbi.nlm.nih.gov/pubmed/27049859 http://dx.doi.org/10.1371/journal.pone.0152504 |
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