ArticleScientific reports2023
Sleep duration during the COVID-19 pandemic in Bangladesh: A GIS-based large sample survey study.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Human Circadian Rhythm Through the Lens of GIScience: A Systematic Review.Research square · 2026Article
- Prevalence, associated factors, and machine learning-based prediction of probable depression among individuals with chronic diseases in Bangladesh.BMC psychiatry · 2025Article
- Prevalence and Factors Associated with Insomnia Among Chronic Disease Patients in Bangladesh: A Machine Learning Study.Nature and science of sleep · 2025Article
- Perceived risk of COVID-19 hurts mental health: the mediating role of fear of COVID-19 and the moderating role of resilience.BMC psychiatry · 2024Article
- Exploring Sleep Duration and Insomnia Among Prospective University Students: A Study with Geographical Data and Machine Learning Techniques.Nature and science of sleep · 2024Article
Corrections and comments
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Authors and funding
18 authors at 10 institutions in 9 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although several studies have been conducted in Bangladesh regarding sleep problems during the COVID-19 pandemic, none have utilized a large nationwide sample or presented their findings based on nationwide geographical distribution. Therefore, the aim of the present study was to explore the total sleep duration, night-time sleep, and daily naptime and their associated factors as well as geographic information system (GIS) distribution. A cross-sectional survey was carried out among 9730 people in April 2020, including questions relating to socio-demographic variables, behavioral and health factors, lockdown, depression, suicidal ideation, night sleep duration, and naptime duration. Descriptive and inferential statistics, both linear and multivariate regression, and spatial distribution were performed using Microsoft Excel, SPSS, Stata, and ArcGIS software. The results indicated that 64.7% reported sleeping 7-9 h a night, while 29.6% slept less than 7 h nightly, and 5.7% slept more than 9 h nightly. 43.7% reported 30-60 min of daily nap duration, whereas 20.9% napped for more than 1 h daily. Significant predictors of total daily sleep duration were being aged 18-25 years, being unemployed, being married, self-isolating 4 days or more, economic hardship, and depression. For nap duration, being aged 18-25 years, retired, a smoker, and a social media user were at relatively higher risk. The GIS distribution showed that regional division areas with high COVID-19 exposure had higher rates of non-normal sleep duration. Sleep duration showed a regional heterogeneity across the regional divisions of the country that exhibited significant associations with a multitude of socioeconomic and health factors.
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Registered trials
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