Crystal Epstein

Early Career Tenure-track Researcher, University of North Carolina, Greensboro

2 active projects

Pregnancy heart rate study

Women’s exposure to social adversity over the life course is associated with altered physiologic set points within stress regulatory systems (e.g. autonomic and endocrine systems). Such physiologic alterations render some women more vulnerable to adverse mental, physical and reproductive health…

Scientific Questions Being Studied

Women’s exposure to social adversity over the life course is associated with altered physiologic set points within stress regulatory systems (e.g. autonomic and endocrine systems). Such physiologic alterations render some women more vulnerable to adverse mental, physical and reproductive health trajectories. Circadian heart rate parameters are an emerging pre-morbid biomarker of sympathovagal balance of the autonomic stress response but few studies have studied this in the context of pregnancy. Therefore, the purpose of this study is to 1) describe within-person trajectories of circadian heart rate over the duration of pregnancy, 2) examine whether between-person variation in these parameters is associated with social and intergenerational adversity and 3) whether within- and between-person nocturnal heart rate parameters are associated with physical activity in pregnancy.

Project Purpose(s)

  • Social / Behavioral
  • Methods Development

Scientific Approaches

We will curate a subset of data from the National Institutes of Health All of Us Research Program for secondary analysis. We will examine a subset of individuals with 1) a confirmed pregnancy and 2) available Fitbit data. Minute-level data on heart rate from the Fitbit will be used to compute circadian heart rate parameters (e.g. nocturnal dipping ratio). Intensive longitudinal data analysis methods will be used for within-person analyses. Multilevel modeling will be used to examine between-person analyses. This research will enhance understanding of stress-related programming effects on pathophysiologic pregnancy complications.

Anticipated Findings

We hypothesize that pregnancy will be associated with an overall increase in heart rate and changes in the nocturnal dipping ratio over the course of pregnancy. Social and intergenerational adversity will be associated with baseline nocturnal dipping ratio and trajectories of heart rate over gestation.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Crystal Epstein - Early Career Tenure-track Researcher, University of North Carolina, Greensboro

Collaborators:

  • Thomas McCoy - Project Personnel, University of North Carolina, Greensboro

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:

  • Crystal Epstein - Early Career Tenure-track Researcher, University of North Carolina, Greensboro
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