Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1016/j.sleep.2021.04.025 http://scihub22266oqcxt.onion/10.1016/j.sleep.2021.04.025 33975776!9017957!33975776     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sleep+Med 2022 ; 91 (ä): 219-225 Nephropedia Template TP {{tp|p=33975776|t=2022. Predictive factors of insomnia during the COVID-19 pandemic in Bangladesh: a GIS-based nationwide distribution |pdf=|usr=}}{{33975776}} gab.com Text Predictive factors of insomnia during the COVID-19 pandemic in Bangladesh: a GIS-based nationwide distribution JO: Sleep Med http://www.kidney.de/pget.php?&tw=1&pmid=33975776 #FOAvip 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. Twit Text FOAVip Predictive factors of insomnia during the COVID-19 pandemic in Bangladesh: a GIS-based nationwide distribution ????Sleep Med http://www.kidney.de/pget.php?&tw=1&pmid=33975776 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33975776 #FOAvip English Wikipedia <ref>{{Cite pmid|33975776}}</ref> Predictive factors of insomnia during the COVID-19 pandemic in Bangladesh: a GIS-based nationwide distribution #MMPMID33975776 Al Mamun F; Gozal D; Hosen I; Misti JM; Mamun MA Sleep Med 2022[Mar]; 91 (ä): 219-225 PMID33975776show ga 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. |*COVID-19/epidemiology[MESH] |*Sleep Initiation and Maintenance Disorders/epidemiology[MESH] |*Sleep Wake Disorders/epidemiology[MESH] |Anxiety/epidemiology[MESH] |Bangladesh/epidemiology[MESH] |Cross-Sectional Studies[MESH] |Depression/epidemiology[MESH] |Female[MESH] |Geographic Information Systems[MESH] |Humans[MESH]Predictive factors of insomnia during the COVID-19 pandemic in Banglad(epmc).pdf DeepDyve Pubget Overpricing