Background: Recent cohort studies have proven the association between sleep deprivation and adverse glycemic control (GC). The aim of this study was to assess the prevalence of excessive daytime sleepiness (EDS), a subjective measure of sleep deprivation, among type 2 diabetic mellitus (T2DM) patients and its association with GC.
Methods: This cross-sectional study was conducted between July 2015 and June 2016 in five diabetes clinics in the district of Erode, Tamil Nadu, India. An equal number of consenting patients with T2DM was recruited consecutively from each of the centers, and EDS was measured subjectively using the Epworth sleepiness scale (ESS), whereas GC was assessed using HbA1c levels.
Results: In all, 126 patients were screened and 102 were found eligible for the study. The prevalence of EDS was 17.5% (95% confidence interval 10.13-24.87). The association between ESS scores and HbA1c levels was analyzed using linear regression after adjusting for age, dietary intake, inflammatory markers (erythrocyte sedimentation rate), depression (Patient Health Questionnaire-9 score) and stress (Perceived Stress Scale score): for every unit increase in the ESS score, HbA1c increased by 0.143 g/dL (P < 0.001).
Conclusion: Subjective EDS was seen in approximately one-quarter of patients with diabetes in our population. There was a positive association between EDS and glycemic control. Screening of patients with diabetes for EDS should be part of routine diabetes management.
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http://dx.doi.org/10.1111/1753-0407.12825 | DOI Listing |
Chronobiol Int
January 2025
Research Center for Overwork-Related Disorders, National Institute of Occupational Safety and Health, Kawasaki, Japan.
In modern society, many workers struggle with sleep deprivation due to their work schedules and excessive workloads. Accurate self-awareness and self-monitoring abilities are crucial for workers to adopt risk-coping strategies and protective behaviors when fatigued. The current study examined the relationship between chronotypes and self-monitoring performance during 24 h of sleep deprivation.
View Article and Find Full Text PDFJ Sleep Res
January 2025
Flinders Health and Medical Research Institute: Sleep Health, Flinders University, Adelaide, South Australia, Australia.
Sleepiness-related errors are a leading cause of driving accidents, requiring drivers to effectively monitor sleepiness levels. However, there are inter-individual differences in driving performance after sleep loss, with some showing poor driving performance while others show minimal impairment. This research explored if there are differences in self-reported sleepiness and driving performance in healthy drivers who exhibited vulnerability or resistance to objective driving impairment following extended wakefulness.
View Article and Find Full Text PDFSleep Breath
January 2025
Faculty of Medicine, Institute of Health Sciences, Department of Public Health, University of Hacettepe, Ankara, Türkiye.
Background: Fatigue, sleep disorders, and daytime sleepiness are interconnected, posing significant risks to occupational health and workplace safety. However, the literature on their relationships remains fragmented, with notable gaps, particularly concerning working populations. This descriptive cross-sectional study aimed to evaluate sleep quality (SQ), daily sleep time in hours (DST), daytime sleepiness, fatigue levels among employees in an automotive workplace, and their interrelationships.
View Article and Find Full Text PDFStudy Objectives: The Psychomotor Vigilance Task (PVT) is widely recognized as the gold standard for measuring vigilance, providing a rapid and objective measure of this state. While driving simulations are also used, they typically require longer administration times. This study examines the sensitivity of driving simulation variables to sleep deprivation throughout the task.
View Article and Find Full Text PDFSleep Biol Rhythms
January 2025
Sleep Research Institute, Edogawa University, 474 Komagi, Nagareyama, Chiba 270-0198 Japan.
To examine whether the effects of low sleep quality, sleep deprivation, and chronotype on daytime cognitive function varied by age group. All data were collected online. We obtained the data from 366 employed people in their 20s, 40s, or 60s.
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