Juseong Kim

Undergraduate Student, Duke University

2 active projects

State-level Activity Inequality

How is physical activity distributed within states in the US? Analysis of such activity distributions and inequality can reveal important relationships between physical activity disparities, health outcomes, and modifiable factors, as studied by Althoff et al. in their paper Large-scale…

Scientific Questions Being Studied

How is physical activity distributed within states in the US? Analysis of such activity distributions and inequality can reveal important relationships between physical activity disparities, health outcomes, and modifiable factors, as studied by Althoff et al. in their paper Large-scale physical activity data reveal worldwide activity inequality (2017).

Project Purpose(s)

  • Educational

Scientific Approaches

The cohort will consist of Fitbit users in the US, with analysis being subdivided to the state level. Various graphs will be utilized to help visualize the low- and high-activity trends across states. Well-defined measures such as the Gini coefficient will be used to aid in the analysis of activity inequality.

Anticipated Findings

The study aims to find relationships between activity inequality and health outcomes, such as obesity levels. With the growing accessibility of fitness trackers and activity sensors built into personal devices, this study hopes to leverage the volume of available data and potentially inform measures to improve population activity and health.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Collaborators:

  • Geetika Singh - Graduate Trainee, Duke University

Duplicate of How to Work With Wearable Device Data

We recommend that all researchers explore the notebooks in this workspace to learn the basics of how to work with Fitbit data, which is the first pilot of wearable device data currently available within the All of Us Registered Tier…

Scientific Questions Being Studied

We recommend that all researchers explore the notebooks in this workspace to learn the basics of how to work with Fitbit data, which is the first pilot of wearable device data currently available within the All of Us Registered Tier dataset. What should you expect? This notebook will give an overview characterization of the Fitbit data elements currently available in the current Curated Data Repository (CDR) and provide best practices and tips for how to retrieve them.

Project Purpose(s)

  • Educational
  • Methods Development
  • Other Purpose (This is an All of Us Tutorial Workspace. It is meant to provide instruction for key Researcher Workbench components and All of Us data representation.)

Scientific Approaches

This Tutorial Workspace contains one Jupyter Notebook written in Python. The notebook contains information on how to extract and work with the current set of All of Us Fitbit data. What are the anticipated findings from the study? How would your findings contribute to the body of scientific knowledge in the field? By reading and running the notebook in this Tutorial Workspace, researchers will learn how to query information about steps, heart rate, and daily activity summary.

Anticipated Findings

By reading and running the notebook in this Tutorial Workspace, researchers will understand how to work with Fitbit CDR data from the workbench. They will learn how to query information about steps, heart rate, and daily activity summary.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

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