Filtering by
- All Subjects: sleep
- All Subjects: Sedentary Behavior
- Creators: Buman, Matthew
- Creators: Whisner, Corrie
protocols, including within sleep-focused studies. This study seeks to address accuracy of
accelerometer data in detection of the beginnings and ends of sleep bouts in young adults with
polysomnography (PSG) corroboration. An existing algorithm used to differentiate valid/invalid wear
time and detect bouts of sleep has been modified with the goal of maximizing accuracy of sleep bout
detection. Methods: Three key decisions and thresholds of the algorithm have been modified with three
experimental values each being tested. The main experimental variable Sleepwindow controls the
amount of time before and after a determined bout of sleep that is searched for additional sedentary
time to incorporate and consider part of the same sleep bout. Results were compared to PSG and sleep
diary data for absolute agreement of sleep bout start time (START), end time (END) and time in bed
(TIB). Adjustments were made for outliers as well as sleep latency, snooze time, and the sum of both.
Results: Only adjustments made to a sleep window variable yielded altered results. Between a 5-, 15-,
and 30-minute window, a 15-minute window incurred the least error and most agreement to
comparisons for START, while a 5-minute window was best for END and TIB. Discussion: Contrary
to expectation, corrections for snooze, latency, and both did not substantially improve agreement to
PSG. Algorithm-derived estimates of START and END always fell after sleep diary and PSG both,
suggesting either participants’ sedentary behavior beginning and ends were at a delay from sleep and
wake times, or the algorithm estimates consistently later times than appropriate. The inclusion of a
sleep window variable yields substantial variety in results. A 15-minute window appears best at
determining START while a 5-minute window appears best for END and TIB. Further investigation on
the optimal window length per demographic and condition is required.
Sleep is imperative for health and wellness with direct impacts on brain function, physiology, emotional well-being, performance and safety when compromised. Adolescents and young adults are increasingly affected by factors affecting the maintenance of regular sleep schedules. College and university students are a potentially vulnerable population to sleep deprivation and sleep insufficiency. Possible factors that could contribute to poor sleep hygiene include, but are not limited to, academic pressures, social activities, and increased screen time. Arguably, students are still experiencing bone mineralization, until the age of 30 or even 40 years old, which makes it more important to understand the effects that altered sleep patterns could have on continued development of bone health. It is our understanding that to date, studies assessing the risk of sleep insufficiency on bone mineral density in college students have not been conducted. We hypothesized that college-aged students, between the ages of 18-25 years, with shorter sleep durations, greater sleep schedule variability, and poorer sleep environments will have significantly lower bone mineral density. ActiGraph monitoring, via a wrist ActiWatch was used to quantitatively measure sleep habits for up to 7 consecutive days. During the week-long study participants also captured their self-reported sleep data through the use of a sleep diary. Participants were measured one time within the study for bone mineral density of the lumbar spine and total hip through a dual energy x-ray absorptiometry. This was a preliminary analysis of a larger cross-sectional analysis looked at 17 participants, of which there were 14 females and 3 males, (n=5, 1 and 11 Hispanic, Black and White, respectively). The mean age of participants was 20.8±1.7 y with an average BMI of 22.9±3.2 kg/m2. ActiWatch measurement data showed a mean daily sleep duration of participants to be 437.5 ± 43.1 (372.5 – 509.4) minutes. Mean sleep efficiency (minutes of sleep divided by minutes of time in bed) and mean number of awakenings were 87.4±4.3 (75.4-93.4) minutes and 32.1±6.4 (22.3-42.7) awakenings, respectively. The median time for wake after sleep onset (WASO) was 34.5±10.5 (18.3-67.4) minutes. The mean bone mineral density (BMD) for the hips was 1.06±0.14 (0.81-1.28) g/cm2 with a mean BMD of the lumbar spine being 1.24±0.12 (0.92-1.43) g/cm2. Age-matched Z-scores of the hips was 0.31±0.96 (-1.6-2.1) and lumbar spine was 0.53 (IQR: 0.13, 0.98; -2.25-1.55). Neither sleep duration nor sleep efficiency was significantly correlated to BMD of either locations. While WASO was positively associated with hip and spine BMD, this value was not statistically significant in this population. Overall, associations between sleep and BMD of the femur and spine were not seen in this cohort. Further work utilizing a larger cohort will allow for control of covariates while looking for potential associations between bone health, sleep duration and efficiency.