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How many days of pedometer monitoring predict weekly physical activity in adults?
Abstract
Background The study purpose was to establish the number (and type) of days needed to estimate mean pedometer-determined steps/day in a field setting.Methods Seven days of data were collected from 90 participants (33 males, age = 49.1 +/- 16.2 years, BMI = 27.2 +/- 4.1 kg/m(2); 57 females, age = 44.8 +/- 16.9 years, BMI = 27.0 +/- 5.9 kg/m(2)). Mean steps/day were computed for all 7 days (the criterion), each single day, and combinations of days. Analyses included repeated measures ANOVA, intra-class correlations (ICC), and regression.Results There was a significant difference (P < 0.001) between days. The difference was limited to Sunday and accounted for 5% of the variance. ICC analyses indicated a minimum of 3 days is necessary to achieve a reliability of 0.80. The adjusted R(2) was 0.79 for a single day (specifically Wednesday), 0.89 for 2 days (Wednesday, Thursday), and 0.94 for 3 days (Wednesday, Thursday, Friday). Sunday was the last day to enter the model.Conclusions Although there is a statistical difference between days, there is little practical difference, and the primary distinction appears limited to Sunday. Although a single day of collection is not acceptable, any 3 days can provide a sufficient estimate.
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“This missingness seems acceptable in comparison with prior studies which considered data to be valid if activity was captured on at least 3 out of 7 days (that is, up to 57% missing data)18.”
From Association of step counts over time with the risk of chronic disease in the All of Us Research Program (2022) · cites this paper as [18]
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Metadata
- Authors
- TUDORLOCKE, C., BURKETT, L., REIS, J., AINSWORTH, B., MACERA, C., & WILSON, D.
- Affiliations
- Arizona State University (US)
- San Diego State University (US)
- University of South Carolina (US)
- ORCID
- WILSON, D
- Venue
- Preventive Medicine
- Publisher
- Elsevier BV
- Published
- 2005-03
- Volume
- 40
- Issue
- 3
- Pages
- 293-298
- ISSN
- 0091-7435 (ISSN-L)
- OpenAlex
- W2039648153
- Cited by
- 479
- References
- 29
- Citations by year
- 2026: 7 · 2025: 16 · 2024: 17 · 2023: 11 · 2022: 28 · 2021: 14 · 2020: 22 · 2019: 27 · 2018: 23 · 2017: 19 · 2016: 25 · 2015: 33 · 2014: 32 · 2013: 33 · 2012: 26
- FWCI
- 6.80
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Preventive Medicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- University of South Carolina
- Centers for Disease Control and Prevention
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Physical Activity and Health
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Medicine › Physiology (medical) › Cardiovascular and exercise physiology
- Keywords
- pedometer monitoring, daily step count, physical activity estimation, measurement reliability, intra-class correlation, weekly physical activity, adults
- MeSH terms
- Adult, Female, Humans, Male, Middle Aged, Monitoring, Physiologic, Motor Activity, Predictive Value of Tests, Reference Standards, Regression Analysis, Time Factors, Reproducibility of Results, Walking
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