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Determining the optimal number of wearing-days given a fixed number of accelerometers in population-level study

Determining the optimal number of wearing-days given a fixed number of accelerometers in population-level study
Determining the optimal number of wearing-days given a fixed number of accelerometers in population-level study
Background: In research using accelerometers to measure physical activity, the number of accelerometers that can be utilized in a study and the study duration are both constrained. It means that increasing the number of accelerometer wearing days for all subjects leads to a decrease in the total number of participants the study can recruit. We used simulations to find the optimal combination of the number of wearing days and number of participant given a fixed number of accelerometer days.
Methods: Two scenarios were studied here, including estimation of population physical activity level and the association between physical activity level and a health outcome. Another similar simulation was conducted by bootstrapping the National Health and Nutrition Examination Survey (NHANES) 2003-2006 accelerometer data (n = 4,069).
Results: The simulation results of the first scenario showed that the error was minimized when the number of wearing days was 1 to 2. Simulation results of the second scenario showed that the optimal number of wearing days increased with the total number of accelerometer days and decreased with intra-class correlation (ICC).
Conclusion: We developed a tool for researchers to determine the optimal combination of the number of the accelerometer wearing days and the total number of participants and showed that 1 to 2 accelerometer wearing days is optimal for estimation of population physical activity level.
Accelerometry, Epidemiology, Measurement, Optimization, Statistics
0917-5040
432-443
Lee, Paul H.
02620eab-ae7f-4a1c-bad1-8a50e7e48951
Lee, Paul H.
02620eab-ae7f-4a1c-bad1-8a50e7e48951

Lee, Paul H. (2019) Determining the optimal number of wearing-days given a fixed number of accelerometers in population-level study. Journal of Epidemiology, 29 (11), 432-443. (doi:10.2188/jea.JE20180095).

Record type: Article

Abstract

Background: In research using accelerometers to measure physical activity, the number of accelerometers that can be utilized in a study and the study duration are both constrained. It means that increasing the number of accelerometer wearing days for all subjects leads to a decrease in the total number of participants the study can recruit. We used simulations to find the optimal combination of the number of wearing days and number of participant given a fixed number of accelerometer days.
Methods: Two scenarios were studied here, including estimation of population physical activity level and the association between physical activity level and a health outcome. Another similar simulation was conducted by bootstrapping the National Health and Nutrition Examination Survey (NHANES) 2003-2006 accelerometer data (n = 4,069).
Results: The simulation results of the first scenario showed that the error was minimized when the number of wearing days was 1 to 2. Simulation results of the second scenario showed that the optimal number of wearing days increased with the total number of accelerometer days and decreased with intra-class correlation (ICC).
Conclusion: We developed a tool for researchers to determine the optimal combination of the number of the accelerometer wearing days and the total number of participants and showed that 1 to 2 accelerometer wearing days is optimal for estimation of population physical activity level.

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More information

Accepted/In Press date: 27 September 2018
Published date: 5 November 2019
Additional Information: Publisher Copyright: © 2018 Paul H. Lee.
Keywords: Accelerometry, Epidemiology, Measurement, Optimization, Statistics

Identifiers

Local EPrints ID: 475069
URI: http://eprints.soton.ac.uk/id/eprint/475069
ISSN: 0917-5040
PURE UUID: 2c7a881b-47ab-4ef1-b5cf-cb309fa9e354
ORCID for Paul H. Lee: ORCID iD orcid.org/0000-0002-5729-6450

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Date deposited: 09 Mar 2023 19:02
Last modified: 17 Mar 2024 04:16

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Author: Paul H. Lee ORCID iD

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