Clinical trial NCT04880629: Monitoring Sleep and Glucose Among University Students
Official title: Monitoring Sleep and Glucose Among University Students
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Sleep
Keywords: Glucose
Insulin
Lead sponsor: National University of Singapore
Sponsor class: OTHER
First posted: 2021-05-11
Enrollment: 131
Sex: ALL
Minimum age (years): 21
Maximum age (years): 30
Standard ages: ADULT
Accepts healthy volunteers: yes
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: BASIC_SCIENCE

Brief summary: This study aims to characterise associations between day-to-day sleep, activity, meal schedules, well-being and continuous glucose profiles in a cohort of free-living healthy, young adults. Multi-day data will be collected using wearables and smartphone-based measures in field settings.

Detailed description: There are two iterations of this study.

In the first iteration (METWI1), wearables and smartphone-based measures are used to characterise free-living sleep, activity, meal schedules, well-being and continuous glucose profiles in a cohort of healthy, young Chinese university students for 4 weeks during the normal school term. While undergoing glucose monitoring (2 weeks), participants consume a standardised meal plan catered by the laboratory to reduce added variance from dietary intake.

Examining relationships between sleep and behavioural characteristics and glucose profiles may contribute to the identification of phenotypes at higher risk of developing metabolic disorders. Data collected in this study may furthermore aid the identification of changes in sleep patterns associated with closer proximity to academic assessments, when students are predicted to experience increased academic workload and stress. Delays and more irregularity in sleep timing, shorter sleep durations and reduced sleep quality are expected closer to assessment dates. These in turn are predicted to result in higher glucose levels and glycemic variability.

In the second iteration (METWI2), in addition to the above measures, participants undergo an oral glucose tolerance test following a night of moderate sleep restriction and baseline sleep (without sleep restriction). This allows us to examine effects of moderate, at-home sleep restriction on glucose tolerance and insulin sensitivity.

In terms of sleep monitoring, we additionally aim to validate passive WiFi sensing against measurement of sleep using a commercial sleep and activity tracker (Oura ring), smartphone touchscreen interactions (tappigraphy-based sleep estimation) and sleep diary logs in students who are residing in dormitories. Studying this sample affords a convenient, and privacy protecting way of obtaining WiFi data. This can contribute to establishing whether a combination of multiple data sources for sleep detection can improve accuracy of sleep detection, incorporating the influence of device usage in the peri-sleep period. The secondary goal of this sleep study is the triangulation of sleep detection techniques for long term sleep monitoring on university campus. The hope is to access a larger population of students to infer sleep behaviours and sleep health, and eventually, to develop interventions to improve population health using individualised sleep data.

Eligibility criteria: Inclusion Criteria:

* Chinese
* NUS student residing on campus during semester
* Healthy
* No sleeping disorders/eating disorders/neurological illnesses
* BMI between 18.0 and 24.9

Exclusion Criteria:

* Smoker
* Pregnant
* Dietary restrictions
* Not able to collect meals and adhere to provided meal plan, or habitual meals/mealtimes from 3-day food diary deemed unsuitable for provided meal plan
* Moderate to severe depression/anxiety scores from BDI or BAI respectively
* Impaired glucose tolerance

Primary outcomes:
measure: Intraindividual changes in sleep duration measured by wearable device (mins) across time
timeFrame: 4 weeks
measure: Intraindividual changes in sleep timing measured by wearable device (mins) across time
timeFrame: 4 weeks
measure: Intraindividual changes in sleep regularity measured by wearable device (mins) across time
timeFrame: 4 weeks
measure: Intraindividual changes in nap behaviour measured by self-report and wearable device (mins) across time
timeFrame: 4 weeks
measure: Intraindividual changes in daily self-reported stress across time
timeFrame: 4 weeks
measure: Intraindividual changes in daily self-reported sleep quality across time
timeFrame: 4 weeks
measure: Intraindividual changes in daily self-reported mood across time
timeFrame: 4 weeks
measure: Intraindividual changes in glucose values across time
timeFrame: 4 weeks
measure: Intraindividual changes in average glucose across time
timeFrame: 4 weeks
measure: Intraindividual changes in glycemic variability across time
timeFrame: 4 weeks
measure: Intraindividual changes in postprandial glucose across time
timeFrame: 4 weeks
measure: Differences in average glucose between individuals with habitually different sleep profiles
timeFrame: 4 weeks
measure: Differences in glycemic variability between individuals with habitually different sleep profiles
timeFrame: 4 weeks
measure: Accuracy of sleep detection using multiple data sources
timeFrame: 4 weeks
measure: Effect of sleep restriction condition on glucose tolerance measured by oral glucose tolerance test.
timeFrame: 1 day
measure: Effect of sleep restriction condition on insulin resistance measured by oral glucose tolerance test.
timeFrame: 1 day
Secondary outcomes:
Other outcomes:
Locations:
city: Singapore
country: Singapore
facility: National University of Singapore
state: (No States Listed)
Study officials:
References: