COVID-19 fear and its associated correlates among type-2 diabetes patients in Bangladesh: A hospital-based study.
Suvasish Das ShuvoMd Toufik HossenMd Sakhawot HossainAsma KhatunSanaullah MazumdarMd RiazuddinDeepa RoyPublished in: Global mental health (Cambridge, England) (2023)
The outbreak of COVID-19 has caused widespread fear among people around the world, particularly those with underlying health conditions such as type-2 diabetes. This study aimed to investigate COVID-19 fear and its associated potential factors among type-2 diabetes patients in Bangladesh. A total of 1,036 type-2 diabetes patients residing in the Jashore district of Bangladesh were interviewed using the COVID-19 Fear Scale in Bengali language. A pre-validated questionnaire was used to collect data on sociodemographic, lifestyle-related characteristics, and COVID-19-related information. Logistic regression was performed to identify factors associated with perceived fear of COVID-19. The mean score of the COVID-19 fear was 18.1 ± 5.6. Approximately 45 and 39% were most afraid and uncomfortable thinking about COVID-19, respectively. Regression analysis revealed that gender, age, occupation, residence, physical activity, smoking, and dietary diversity score were associated with fear. Additionally, respondents who had limited self-care practice, unaffordable medicine, medicine shortages, a close friend or family member diagnosed with COVID-19, and financial problems during COVID-19 were significant predictors of COVID-19 fear. Healthcare providers should implement interventions, including appropriate education and counseling, to address the psychological impact of the COVID-19 pandemic on type-2 diabetes patients in Bangladesh.
Keyphrases
- coronavirus disease
- sars cov
- type diabetes
- healthcare
- end stage renal disease
- physical activity
- chronic kidney disease
- ejection fraction
- newly diagnosed
- mental health
- cardiovascular disease
- primary care
- prognostic factors
- respiratory syndrome coronavirus
- autism spectrum disorder
- depressive symptoms
- young adults
- public health
- body mass index
- single cell
- climate change
- social media
- artificial intelligence
- quality improvement
- health information
- big data
- psychometric properties