Öztürk Onur, Domaç Alaıddın, Ceylan Șuayıp, Ayraler Arzu, Tapur Mehmet Akif, Oruç Muhammet Ali
Department of Family Medicine, Faculty of Medicine, Samsun University, Samsun 55070, Turkey.
Clinic of Anesthesiology and Reanimation, Bafra State Hospital, Samsun 55400, Turkey.
Med Int (Lond). 2023 Dec 5;4(1):3. doi: 10.3892/mi.2023.127. eCollection 2024 Jan-Feb.
The present study aimed to evaluate the reasons behind the fact that some individuals did not contract coronavirus disease 2019 (COVID-19), considering certain socio-demographic data. The present cross-sectional study was conducted at a state hospital between February 1, 2022 and March 1, 2022. The study group consisted of individuals who never had COVID-19, and the control group consisted of individuals who did not know at the time of the study whether they had COVID-19. A data collection form consisting of 29 questions created based on a literature review was used. A total of 2,958 subjects (study group, 669; control group, 2,289) were included; of these, 53.1% were females and 46.9% were males. It was found that housewives (P<0.001), individuals with secondary school and lower education levels (P=0.02), those residing in rural areas (P=0.003), those who received a combination vaccine (P<0.001), those with chronic diseases (P=0.016), those who consumed more fruits (P=0.001), those who used N95 masks (P=0.002), those with pets (P<0.001) and those who did not follow the news regarding COVID-19 (P=0.016) had a higher probability of not contracting COVID-19. On the whole, the present study observed that socio-demographic factors affected the non-COVID-19 status.
本研究旨在结合某些社会人口统计学数据,评估一些人未感染2019冠状病毒病(COVID-19)背后的原因。本横断面研究于2022年2月1日至2022年3月1日在一家州立医院进行。研究组由从未感染过COVID-19的个体组成,对照组由在研究时不知道自己是否感染过COVID-19的个体组成。使用了一份基于文献综述创建的包含29个问题的数据收集表。总共纳入了2958名受试者(研究组669名;对照组2289名);其中,53.1%为女性,46.9%为男性。研究发现,家庭主妇(P<0.001)、中学及以下教育水平的个体(P=0.02)、居住在农村地区的个体(P=0.003)、接种过联合疫苗的个体(P<0.001)、患有慢性病的个体(P=0.016)、食用较多水果的个体(P=0.001)、使用N95口罩的个体(P=0.002)、养宠物的个体(P<0.001)以及不关注COVID-19相关新闻的个体(P=0.016)感染COVID-19的可能性较低。总体而言,本研究观察到社会人口统计学因素会影响未感染COVID-19的状态。