Dataset Information

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

ABSTRACT:

Background

In 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.

Methods

This 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.

Results

Approximately 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.

Conclusion

Insomnia 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.

SUBMITTER: Al Mamun F

PROVIDER: S-EPMC9017957 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Publications

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

Al Mamun Firoj F Gozal David D Hosen Ismail I Misti Jannatul Mawa JM Mamun Mohammed A MA

Sleep medicine 20210426

<h4>Background</h4>In 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 ident ...[more]

PMID: 33975776

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Project description:BackgroundThe COVID-19 pandemic is a public health threat of international concern, intensifying peoples' psychological risk and vulnerability by strengthening mental health stressors such as fear, panic and uncertainty. The unexpected fear of COVID-19 has been reported to be associated with suicide occurrences, similar to prior pandemics.AimsIdentifying the factors associated with fear of COVID-19 could help us to develop better mental health strategy and practice to improve the situation here in Bangladesh. This was the first attempt to present a Geographic Information System (GIS)-based distribution of fear of COVID-19 across the country's administrative districts in a nationwide sample.MethodData for a total of 10 067 individuals were collected by an online survey during the first wave of the pandemic (1 to 10 April 2020); data for 10 052 participants were finally analysed after excluding 15 transgender individuals. The survey questionnaire included items concerning sociodemographic, behavioural and health-related variables, COVID-19-related issues, and the Bangla Fear of COVID-19 Scale.ResultsThe mean fear of COVID-19 scores was 21.30 ± 6.01 (out of a possible 35) in the present sample. Female gender, highly educated, non-smoker, non-alcohol consumer, having chronic diseases, using social media, and using social media and not using newspapers as COVID-19 information sources were associated with a higher level of fear of COVID-19. Higher levels of fear of COVID-19 were found in districts of Magura, Panchagarh, Tangail, Sunamganj and Munshiganj; by contrast, Kushtia, Pirojpur, Chapainawabganj, Jhalokathi and Naogaon districts had lower fear of COVID-19. Based on the GIS-distribution, fear of COVID-19 was significantly associated with the district as well as in respect to its gender-based and education-level-based associations. However, fear of COVID-19 and COVID-19 cases were heterogeneously distributed across the districts; that is, no consistent association of higher COVID-19 cases with higher fear of COVID-19 was found.ConclusionsThis study being exploratory in nature may help to facilitate further studies, as well as directing governmental initiatives for reducing fear of COVID-19 in at-risk individuals. Providing adequate resources and mental health services in the administrative regions identified as highly vulnerable to fear of COVID-19 is recommended.

Project description:Objective/backgroundTo describe and characterize insomnia symptoms and nightmare profiles in Portugal during the first six weeks of a national lockdown due to COVID-19.Patients/methodsAn open cohort study was conducted to collect information of the general population during the first wave of SARS-CoV-2/COVID-19 pandemic in Portugal. We analyzed data from 5011 participants (≥16 years) who answered a weekly questionnaire about their well-being. Two questions about the frequency of insomnia and nightmares about COVID-19 were consecutively applied during six weeks (March-May 2020). Latent class analysis was conducted and different insomnia and nightmare profiles were identified. Associations between individual characteristics and both profiles were estimated using odds ratios (ORs) and 95% confidence intervals (CI).ResultsFive insomnia (No insomnia, Stable-mild, Decreasing-moderate, Stable-severe, Increasing-severe) and three nightmares profiles (Stable-mild, Stable-moderate, Stable-severe) were identified. Being female, younger, perceiving their income as insufficient and feelings of fear towards COVID-19 were associated with higher odds of insomnia (Women: OR = 6.98 95%CI: 4.18-11.64; ≥60 years: OR = 0.30 95%CI: 0.18-0.53; Insufficient income: adjusted OR (aOR) = 8.413 95%CI: 3.93-16.84; Often presenting fear of being infected with SARS-CoV-2 infection: aOR = 9.13 95%CI: 6.36-13.11), and nightmares (Women: OR = 2.60 95%CI: 1.74-3.86; ≥60 years: OR = 0.45 95%CI: 0.28-0.74; Insufficient income: aOR = 2.60 95%CI: 1.20-5.20; Often/almost always presenting fear of being infected with SARS-CoV-2 infection: aOR = 6.62 95%CI: 5.01-8.74). Having a diagnosis of SARS-CoV-2 virus infection was associated with worse patterns of nightmares about the pandemic.ConclusionsSocial and psychological individual factors are important characteristics to consider in the development of therapeutic strategies to support people with sleep problems during the COVID-19 pandemic.

Project description:BackgroundCommon psychosocial health problems (PHPs) have become more prevalent among adolescents globally during the COVID-19 pandemic. However, the psychosocial health of school-going adolescents has remained unexplored in Bangladesh due to limited research during the pandemic. The present study aimed to estimate the prevalence of PHPs (i.e., depression and anxiety) and assess associated lifestyle and behavioral factors among school-going adolescents in Bangladesh during the COVID-19 pandemic.MethodsA nationwide cross-sectional survey was conducted among 3,571 school-going adolescents (male: 57.4%, mean age: 14.9±1.8 years; age range: 10-19 years) covering all divisions, including 63 districts in Bangladesh. A semi-structured e-questionnaire, including informed consent and questions related to socio-demographics, lifestyle, academics, pandemic and PHPs, was used to collect data between May and July 2021.ResultsThe prevalence of moderate to severe depression and anxiety were 37.3% and 21.7%, respectively, ranging from 24.7% in the Sylhet Division to 47.5% in the Rajshahi Division for depression, and from 13.4% in the Sylhet Division to 30.3% in the Rajshahi Division for anxiety. Depression and anxiety were associated with older age, reports of poor teacher cooperation in online classes, worries due to academic delays, parental comparison of academic performance with other classmates, difficulties coping with quarantine situations, changes in eating habits, weight gain, physical inactivity and having experienced cyberbullying. Moreover, being female was associated with higher odds of depression.ConclusionsAdolescent psychosocial problems represent a public health problem. The findings suggest a need for generating improved empirically supported school-based psychosocial support programs involving parents and teachers to ensure the well-being of adolescents in Bangladesh. School-based prevention of psychosocial problems that promote environmental and policy changes related to lifestyle practices and active living should be developed, tested, and implemented.

Project description:BackgroundInsomnia is a prevalent sleep disorder that affects people all over the world. Creating suitable interventions will require a better understanding of the magnitude and determinants of insomnia. This study aimed to assess the prevalence and associated factors of insomnia symptoms among residents of Mettu town during the pandemic lockdown.MethodologyA community-based cross-sectional study was conducted among residents of Mettu town from October 1st to October 15th, 2020. Residents who lived in Mettu town at least for six months were included. To determine the prevalence and determinants of insomnia symptoms, both descriptive and inferential analyses were used. The chi-squared test of association and logistic regression was used to identify predictors of insomnia symptoms among residents of Mettu town. We used SPSS version 25 for all statistical analyses.Principal findingsThe prevalence of depressive symptoms among residents of Mettu town was 52.6%. According to results of multivariable binary logistic regression, being female [AOR = 3.677, 95%CI: 2.124-6.365], being aged between 19 and 40 [AOR = 13.261, 95%CI: 6.953-25.291], being aged above 41 [AOR = 2.627, 95%CI: 1.120-6.159], smoking [AOR = 15.539, 95%CI: 7.961-30.329], satisfaction with information available [AOR = 0.310, 95%CI: 0.168-0.570], fear Corona Virus Disease 2019 (COVID-19), [AOR = 2.171, 95%CI: 1.262-3.733], feeling alienated from others [AOR = 3.288, 95%CI: 1.897-5.699], having somatic symptoms [AOR = 2.298, 95% CI: 1.360-3.884], having depressive symptoms [AOR = 1.841, 95% CI: 1.073-3.160], and experiencing psychological distress [AOR = 1.962, 95% CI: 1.173-3.281] were significantly associated with insomnia symptoms.ConclusionIn this study, the prevalence of insomnia symptoms was found to be high among residents of Mettu town. Being female, being aged between 19 and 40, being aged above 41 years, smoking, fear of Corona Virus Disease 2019, feeling alienated from others, having somatic symptoms, having depressive symptoms, and experiencing psychological distress were all associated with an increased risk of developing insomnia symptoms while being satisfied with the information available decreased the risk of insomnia symptoms among residents of Mettu town. Interventions should be put in place to promote healthy sleep among residents of Mettu town.

Dataset Information

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

Background

Methods

Results

Conclusion

Publications

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

Similar Datasets

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