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Number of daily measurements needed to estimate habitual step count levels using wrist-worn trackers and smartphones in 212,048 adults

Daily step count is a readily accessible physical activity measure inversely related to many important health outcomes. However, its day-to-day variability is not clear, especially when measured by recent mobile devices. This study investigates number of measurement days required to reliably estimat...

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Autores principales: Yao, Jiali, Tan, Chuen Seng, Lim, Nicole, Tan, Jeremy, Chen, Cynthia, Müller-Riemenschneider, Falk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8100112/
https://www.ncbi.nlm.nih.gov/pubmed/33953288
http://dx.doi.org/10.1038/s41598-021-89141-3
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author Yao, Jiali
Tan, Chuen Seng
Lim, Nicole
Tan, Jeremy
Chen, Cynthia
Müller-Riemenschneider, Falk
author_facet Yao, Jiali
Tan, Chuen Seng
Lim, Nicole
Tan, Jeremy
Chen, Cynthia
Müller-Riemenschneider, Falk
author_sort Yao, Jiali
collection PubMed
description Daily step count is a readily accessible physical activity measure inversely related to many important health outcomes. However, its day-to-day variability is not clear, especially when measured by recent mobile devices. This study investigates number of measurement days required to reliably estimate the weekly and monthly levels of daily step count in adults using wrist-worn fitness trackers and smartphones. Data were from a 5-month physical activity program in Singapore. The 5-month period was divided into 22 weekly and 5 monthly time windows. For each time window, we leveraged data sampling procedures and estimated the minimum number of measurement days needed to achieve reliable mean daily step count with intraclass correlation coefficients (ICC) above 80%. The ICCs were derived using linear mixed effect models. We examined both simple random and random consecutive measurement days and conducted subgroup analysis by participant characteristics and tracking devices. Analysis of weekly and monthly step count included 212,048 and 112,865 adults, respectively. Fewer simple random measurement days are needed than random consecutive days for weekly time windows (mean 2.5, SD 0.5 vs mean 2.7, SD 0.5; p-value = 0.025). Similarly, monthly time windows require fewer measurements of simple random days than random consecutive days (mean 3.4, SD 0.5 vs mean 4.4, SD 0.5; p-value = 0.025). Younger participants and those tracking steps via smartphones consistently required more days. Being obese was associated with more measurement days for weekly time windows. In sum, to obtain reliable daily step count level, we recommend at least 3 measurement days for weekly and 5 days for monthly time window in adults. Fewer days could be considered for adults age 60+ years, while more days are required when tracking daily step via smartphones.
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spelling pubmed-81001122021-05-07 Number of daily measurements needed to estimate habitual step count levels using wrist-worn trackers and smartphones in 212,048 adults Yao, Jiali Tan, Chuen Seng Lim, Nicole Tan, Jeremy Chen, Cynthia Müller-Riemenschneider, Falk Sci Rep Article Daily step count is a readily accessible physical activity measure inversely related to many important health outcomes. However, its day-to-day variability is not clear, especially when measured by recent mobile devices. This study investigates number of measurement days required to reliably estimate the weekly and monthly levels of daily step count in adults using wrist-worn fitness trackers and smartphones. Data were from a 5-month physical activity program in Singapore. The 5-month period was divided into 22 weekly and 5 monthly time windows. For each time window, we leveraged data sampling procedures and estimated the minimum number of measurement days needed to achieve reliable mean daily step count with intraclass correlation coefficients (ICC) above 80%. The ICCs were derived using linear mixed effect models. We examined both simple random and random consecutive measurement days and conducted subgroup analysis by participant characteristics and tracking devices. Analysis of weekly and monthly step count included 212,048 and 112,865 adults, respectively. Fewer simple random measurement days are needed than random consecutive days for weekly time windows (mean 2.5, SD 0.5 vs mean 2.7, SD 0.5; p-value = 0.025). Similarly, monthly time windows require fewer measurements of simple random days than random consecutive days (mean 3.4, SD 0.5 vs mean 4.4, SD 0.5; p-value = 0.025). Younger participants and those tracking steps via smartphones consistently required more days. Being obese was associated with more measurement days for weekly time windows. In sum, to obtain reliable daily step count level, we recommend at least 3 measurement days for weekly and 5 days for monthly time window in adults. Fewer days could be considered for adults age 60+ years, while more days are required when tracking daily step via smartphones. Nature Publishing Group UK 2021-05-05 /pmc/articles/PMC8100112/ /pubmed/33953288 http://dx.doi.org/10.1038/s41598-021-89141-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Yao, Jiali
Tan, Chuen Seng
Lim, Nicole
Tan, Jeremy
Chen, Cynthia
Müller-Riemenschneider, Falk
Number of daily measurements needed to estimate habitual step count levels using wrist-worn trackers and smartphones in 212,048 adults
title Number of daily measurements needed to estimate habitual step count levels using wrist-worn trackers and smartphones in 212,048 adults
title_full Number of daily measurements needed to estimate habitual step count levels using wrist-worn trackers and smartphones in 212,048 adults
title_fullStr Number of daily measurements needed to estimate habitual step count levels using wrist-worn trackers and smartphones in 212,048 adults
title_full_unstemmed Number of daily measurements needed to estimate habitual step count levels using wrist-worn trackers and smartphones in 212,048 adults
title_short Number of daily measurements needed to estimate habitual step count levels using wrist-worn trackers and smartphones in 212,048 adults
title_sort number of daily measurements needed to estimate habitual step count levels using wrist-worn trackers and smartphones in 212,048 adults
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8100112/
https://www.ncbi.nlm.nih.gov/pubmed/33953288
http://dx.doi.org/10.1038/s41598-021-89141-3
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