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Applying Latent Class Assignments for Accelerometry Data to External Populations: Data from the National Health and Nutrition Examination Survey 2003-2006

Citation

Evenson, Kelly R.; Wen, Fang; Howard, Annie Green; & Herring, Amy H. (2016). Applying Latent Class Assignments for Accelerometry Data to External Populations: Data from the National Health and Nutrition Examination Survey 2003-2006. Data in Brief, 9, 926-930. PMCID: PMC5118612

Abstract

Latent class analysis can identify unmeasured mutually exclusive categories (class membership) among participants for either observed categorical or continuous variables. More recently, latent class analysis has been applied to accelerometry to better understand the day-to-day patterns of physical activity and sedentary behavior. Typically, the class assignments are only relevant to the study for which they were derived and not made available for others to use. Using one-week accelerometry (ActiGraph #AM7164) data collected from the National Health and Nutrition Examination Survey during 2003-2006, latent classes of physical activity and sedentary behavior were derived separately for youths 6-17 years and adults >=18 years. The purpose of this article is to provide the latent class assignments developed on this source population (United States) available to others to apply to their studies using similarly collected accelerometry. This method will extend the usefulness of the latent class analysis and allow for comparisons across studies.

URL

http://dx.doi.org/10.1016/j.dib.2016.11.007

Reference Type

Journal Article

Year Published

2016

Journal Title

Data in Brief

Author(s)

Evenson, Kelly R.
Wen, Fang
Howard, Annie Green
Herring, Amy H.

PMCID

PMC5118612