Risk factors for the prevalence of poor sleep quality in lecturers during COVID-19 pandemic in Ethiopia: an institution-based cross-sectional study

Abstract

ObjectiveThis study was conducted to assess the prevalence and risk factors of poor sleep quality (SQ) among the academic staff at the University of Gondar, Northwestern Ethiopia.DesignAn institution-based cross-sectional study was conducted from March to April 2021. A validated, self-administered, standardised Pittsburgh Sleep Quality Index (PSQI) was used to quantify the amount of self-reported poor SQ. The collected data were entered into EpiData V.4.6 and analysed using Stata V.14 software. Binary logistic regressions were computed to determine the association between variables. The association was determined using an adjusted OR (AOR) with a 95% CI at a p value of <0.05.SettingThe study was conducted at the University of Gondar, Northwestern Ethiopia.ParticipantsA total of 607 lecturers participated in this study.Outcome measuresThe primary outcome is the prevalence of poor SQ, which was measured using the PSQI.ResultsOverall response rate was 95.60% (N=607). The age of the participants ranges from 21 to 70 with a mean of 32.39 (SD±6.80) years. The magnitude of poor SQ during the COVID-19 pandemic in the last month was 60.30% (95% CI (56.28% to 64.21%)). Working greater than 10 hours per day (AOR=2.19, 95% CI (1.16 to 4.27)), electronic device use before bedtime (AOR=1.53, 95% CI (1.04 to 2.27)), high-risk perception of COVID-19 infections (AOR=1.60, 95% CI (1.04 to 2.46)) and perceived job stress (AOR=2.15 (95% CI (1.50 to 3.08)) were risk factors for poor SQ.ConclusionThe study revealed that the prevalence of poor SQ was high during the COVID-19 pandemic. The finding highlights the importance of optimising the working hours per day, minimising electronic device use before bedtime, promoting risk perception toward COVID-19 infection and developing workplace coping strategies for stress, which play a substantial role in minimising poor SQ.

Prevalence of work-related burnout and associated factors among police officers in central Gondar zone, Northwest Ethiopia, 2023

“…The variance inflation factor was used to verify the multicollinearity assumption (VIF < 2.15). To account for potential confounding variables, the variables that demonstrated statistically significant relationships with the dependent variable at p -values <0.2 ( 73 , 75 , 76 ) in the bivariable logistic regression analysis were subsequently deemed suitable for a multivariable logistic regression. The Hosmer and Lemeshow goodness-of-fit test was used to check the model’s fitness, and it was well fitted ( p value >0.05).…”

Prevalence and associated factors of poor sleep quality among industrial workers in Addis Ababa, Ethiopia: findings from a cross-sectional study

“…The total work-related scale was divided into two categories: a score of less than 21=0 (not stressed), and a score of 21 and above=1 (stressed) with their current job 56. These questionnaires have been employed in earlier research conducted in a country’s context and have been proven to be reliable 24 74 75. The final section of the questionnaire ended with information consisting of work-related characteristics of the participants, such as working hours per day, the practice of taking breaks, workload, night shift work and the presence of noise disruption during sleep time.…”

“…56 These questionnaires have been employed in earlier research conducted in a country’s context and have been proven to be reliable. 24 74 75 The final section of the questionnaire ended with information consisting of work-related characteristics of the participants, such as working hours per day, the practice of taking breaks, workload, night shift work and the presence of noise disruption during sleep time. Finally, the questionnaire was translated into the Amharic version by authors and language experts, and a face-to-face interview was carried out at the workplaces of the respondents.…”

“… 8 In Ethiopia, the pooled prevalence of poor sleep quality was 53% among the general population and university students, with incidences ranging from 26% to 66.2%. 23 The extent of poor sleep quality among industrial workers might be expected to increase over time due to the expansion of industry 24 and the exposure of workers in these industries to a range of workplace conditions, 25 but studies on sleep quality, particularly among industrial workers, are scarce.…”