Rural–urban disparities in knowledge, behaviors, and mental health during COVID-19 pandemic

Abstract

To examine the knowledge level, behaviors, and psychological status of the Chinese population during the COVID-19 pandemic, and to explore the differences between urban and rural areas. We carried out a cross-sectional survey of the knowledge, behaviors related to COVID-19, and mental health in a probability sample of 3001 community residents in 30 provinces or districts across China from February 16–23, 2020. Convenience sampling and a snowball sampling were adopted. We used General Anxiety Disorder (GAD), the 9-item Patient Health Questionnaire (PHQ-9), and knowledge and behaviors questionnaire of community residents regarding COVID-19 designed by us to investigate the psychological status, disease-related knowledge, and the behavior of Chinese urban and rural residents during the pandemic. The average score of anxiety and depression among urban residents was 9.15 and 11.25, respectively, while the figures in rural areas were 8.69 and 10.57, respectively. There was a statistically significant difference in the levels of anxiety ( P < .01) and depression ( P < .01). Urban participants reported significantly higher levels of knowledge regarding COVID-19 in all aspects (transmission, prevention measures, symptoms of infection, treatment, and prognosis) ( P < .01), compared to their rural counterparts. While a majority of respondents in urban areas obtained knowledge through WeChat, other apps, and the Internet ( P < .01), residents in rural areas accessed information through interactions with the community ( P < .01). Urban residents fared well in exchanging knowledge about COVID-19 and advising others to take preventive measures ( P < .01), but fared poorly in advising people to visit a hospital if they displayed symptoms of the disease, compared to rural residents ( P < .01). Regression analysis with behavior showed that being female (OR = 2.106, 95%CI = 1.259–3.522), aged 18 ≤ age < 65 (OR = 4.059, 95%CI = 2.166–7.607), being satisfied with the precautions taken by the community (OR = 2.594, 95%CI = 1.485–4.530), disinfecting public facilities in the community (OR = 2.342, 95%CI = 1.206–4.547), having knowledge of transmission modes (OR = 3.987, 95%CI: 2.039, 7.798), symptoms (OR = 2.045, 95%CI = 1.054–4.003), and outcomes (OR = 2.740, 95%CI = 1.513–4.962) of COVID-19, and not having anxiety symptoms (OR = 2.578, 95%CI = 1.127–5.901) were positively associated with affirmative behavior in urban areas. Being married (OR = 4.960, 95%CI = 2.608–9.434), being satisfied with the precautions taken by the community (OR = 2.484, 95%CI = 1.315–4.691), screening to ensure face mask wearing before entering the community (OR = 8.809, 95%CI = 2.649–19.294), and having knowledge about precautions (OR = 4.886, 95%CI = 2.604–9.167) and outcomes (OR = 2.657, 95%CI = 1.309–5.391) were positively associated with acceptable c...

Changes in the body mass of adult residents of rural and urban areas in the initial months of the COVID-19 pandemic vs. their mental, physical and sexual health

“…In the case of anxiety, the mean index was equal to 9.15 and 8.69, respectively. In the case of depression, the mean index decreased from 11.25 in urban to 10.57 in rural areas [30]. In the current study, urban residents also showed a higher average stress level than residents of rural areas (6.44 vs. 6.29).…”

Urban-rural difference in community willingness to isolate during COVID-19 pandemic in Benue State Nigeria 2021

“…These findings are similar to a study which was done in China with regards the COVID-19 pandemic which showed that young women's knowledge acceptance and behavioural changes were better than their male counterparts and in addition, most women are more compliant and more willing than men to choose appropriate behaviour to protect themselves and their families. 31 Other studies also show that women had a higher literacy level of prevention and control of infectious diseases than men, and men were more likely to engage in risky behaviour. 32,33 Our study also revealed that singles are 9 times more likely to stay in isolation than other forms of marital status however, these findings are contrary to a cross sectional study that was done in China which revealed that married people demonstrated greater positive behaviours than their single counterparts and in addition, married residents did not consider themselves as just individuals, but they often considered family factors and acted accordingly.…”

“…Meanwhile, if family members chose positive behaviours, under their influence, they would act in accordance with them, which was conducive to the positive behaviour of married people. 31 Among dwellers living in the rural communities, those who attained secondary school to bachelor's degree as well as self-employed respondents were independent factors of willingness to isolate during COVID-19 pandemic as they are 2 to 3 times more likely to stay in isolation and these findings are in line with a study in China which found that lower income and education were associated with lower levels of behavioural performance, positive attitude, and knowledge related to COVID-19 preventive behaviours. 27 Previous studies also found that vulnerable populations like the unemployed and less educated are more likely to use and trust health information from social media where information accuracy and quality are questionable.…”

Predicting COVID-19–Related Health Care Resource Utilization Across a Statewide Patient Population: Model Development Study

“…Features that influenced the prediction of health care resource utilization included patient age [ 27 ], chronic obstructive pulmonary disease status [ 28 ], smoking [ 28 ], diabetes [ 29 ], indication of neurological diseases via diagnosis (eg, dementia [ 30 ]) or medications (eg, anti-Parkinson and related therapy agents), mental disorders (eg, anxiety disorders), residence (urban vs rural) [ 31 , 32 ], and income-level, measured on the basis of the type of insurance used by the patient. None of the patient-level social determinants of health factors extracted from the International Classification of Diseases diagnosis data were found to be impactful enough for inclusion in either model.…”