ORCID

https://orcid.org/0000-0003-0696-5674

Year

2023

Season

Spring

Paper Type

Master's Thesis

College

Brooks College of Health

Degree Name

Master of Science in Health Science (MSH)

Department

Clinical & Applied Movement Sciences

NACO controlled Corporate Body

University of North Florida. Department of Clinical & Applied Movement Sciences

First Advisor

Dr. James R. Churilla

Second Advisor

Dr. M. Ryan Richardson

Third Advisor

Dr. Lindsay P. Toth

Fourth Advisor

Dr. Tammie M. Johnson

Department Chair

Dr. Joel Beam

College Dean

Dr. Curt Lox

Abstract

BACKGROUND: Prescription medication use and extended sedentary time are independently related to poor health outcomes (e.g., diabetes, metabolic syndrome, mortality). Historically, survey methods have been used to obtain estimates of total sedentary time (ST), however, recent use of accelerometers avoids self-report bias and affords more characteristics of ST that may be factors in health outcomes (e.g., frequency and duration of sedentary bouts). The aims of this pilot study were to 1) examine the association between objectively measured ST via accelerometers and self-reported prescription medication use in adults and 2) examine the independent association of sedentary bout length and frequency with prescription medication use.

METHODS: Adults (N=32) were asked to wear an accelerometer continuously on their right hip for seven days while manually recording sleep times and instances of activity monitor removal. Participants were also asked to report the number and type of medications they were currently prescribed. Poisson regression analysis was used to predict the number of prescriptions medications an individual consumed based on the average hours of ST per day, average number of bouts per day, and average time (min) of sedentary bouts.

RESULTS: Analysis revealed a significantly higher prevalence of prescription medications for each hour of ST per day (PR 1.66; 95% CI 1.25-2.19; P

CONCLUSIONS: Our findings suggest that increased sedentary time is associated with greater prescription medication use among adults.

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