Evidence map›Paper›PMID 33975776›Full record

ArticleSleep medicine2022

Predictive factors of insomnia during the COVID-19 pandemic in Bangladesh: a GIS-based nationwide distribution.

Firoj Al Mamun, David Gozal, Ismail Hosen, Jannatul Mawa Misti, Mohammed A Mamun

Open access · greenAbstract read
In one paragraph

Article in Sleep medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
5.5field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed, 33 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 2 countries.

Firoj Al MamunCHINTA Research Bangladesh (Centre for Health Innovation, Networking, Training, Action and Research - Bangladesh), Savar, Dhaka, Bangladesh; Department of Public Health and Informatics, Jahangirnagar University, Savar, Dhaka, Bangladesh. Electronic address: firojphiju@gmail.com.
David GozalDepartment of Child Health and the Child Health Research Institute, The University of Missouri School of Medicine, Columbia, MO, United States. Electronic address: gozald@health.missouri.edu.
Ismail HosenCHINTA Research Bangladesh (Centre for Health Innovation, Networking, Training, Action and Research - Bangladesh), Savar, Dhaka, Bangladesh; Department of Public Health and Informatics, Jahangirnagar University, Savar, Dhaka, Bangladesh. Electronic address: ihosen1631@gmail.com.
Jannatul Mawa MistiCHINTA Research Bangladesh (Centre for Health Innovation, Networking, Training, Action and Research - Bangladesh), Savar, Dhaka, Bangladesh; Pabna Medical College, Hemayetpur, Pabna, Bangladesh. Electronic address: misti.jannatulmawa@gmail.com.
Mohammed A MamunCHINTA Research Bangladesh (Centre for Health Innovation, Networking, Training, Action and Research - Bangladesh), Savar, Dhaka, Bangladesh; Department of Public Health and Informatics, Jahangirnagar University, Savar, Dhaka, Bangladesh. Electronic address: mamunphi46@gmail.com.
Jahangirnagar University · BDPabna University of Science and Technology · BDUniversity of Missouri Health System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn a densely populated country like Bangladesh, mental health-related burden and associated adverse outcomes are quite prevalent. However, exploration of sleep-related issues in general, and more specifically of insomnia during the COVID-19 pandemic has been scarce and restricted to a single location. The present study investigated the prevalence of insomnia and its predictive factors in the general population, and included Geographic Information System (GIS) analysis to identify regional heterogeneities of insomnia in Bangladesh.

methodsThis cross-sectional study was conducted during the early period of the COVID-19 pandemic. Information related to socio-demographics, knowledge of COVID-19, behaviors related to COVID-19, fear of COVID-19, and insomnia were included in a questionnaire, and coupled with GIS-based spatial analysis to identify regional susceptibility to insomnia.

resultsApproximately 30.4%, 13.1% and 2.8% of participants reported sub-threshold, moderate, and severe forms of insomnia, respectively. Independent predictive risk factors of insomnia symptoms included female gender, college education, urban residence, presence of comorbidities, using social media, taking naps during daytime, and fear of COVID-19. District-wide variations in the spatial distribution of fear of COVID-19 and insomnia were significantly associated.

conclusionInsomnia is frequently present during a pandemic, and exhibits regional variability along with multifactorial determinants. These analytic approaches should enable improved detection and targeting of at-risk sectors of the population, and enable implementation of appropriate measures to ensure improved sleep quality.

Indexed as

COVID-19Sleep Initiation and Maintenance DisordersSleep Wake DisordersAnxietyBangladeshCross-Sectional StudiesDepressionFemaleGeographic Information SystemsHumansPandemicsBangladeshCOVID-19 psychological impactFear of COVID-19GIS-Based nationwide studyInsomniaSleep problems

Identifiers

PMID33975776
PMCPMC9017957
OpenAlexW3159681481

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.