Food Acquisition during the COVID-19 Lockdown and Its Associations with the Physical-Digital Integrated Community Food Environment: A Case Study of Nanjing, China

Use of online food retail platforms throughout the COVID-19 pandemic and associated diet-related chronic disease risk factors: A systematic review of emerging evidence

Food accessibility was considerably impacted by restrictions during the coronavirus disease 2019 (COVID-19) pandemic, leading to growth in the online food retail sector, which offered contact-free delivery. This systematic review aimed to assess the change in use of online food retail platforms during COVID-19. The secondary aim was to identify diet-related chronic disease risk factors including dietary intake, eating behaviors, and/or weight status associated with the use of online food retail platforms during the pandemic. The review was registered in the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42022320498) and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Nine electronic databases were searched between January 2020 and October 2023. Studies that reported the frequency or change in use of online groceries, meal delivery applications, and/or meal-kit delivery services before and during the pandemic were included. A total of 53 studies were identified, including 46 cross-sectional studies, 4 qualitative studies, 2 longitudinal cohort studies, and 1 mixed-methods study. Overall, 96% (43/45) of outcomes showed an increase in the use of online groceries during COVID-19, while 55% (22/40) of outcomes showed a decrease in meal delivery applications. Eight of nine outcomes associated the use of online food retail with weight gain and emotional eating. Further research is needed to investigate the links between online food retail and obesity.

Health-Related Rumor Control through Social Collaboration Models: Lessons from Cases in China during the COVID-19 Pandemic

Widely spread health-related rumors may mislead the public, escalate social panic, compromise government credibility, and threaten public health. Social collaboration models that maximize the functions and advantages of various agents of socialization can be a promising way to control health-related rumors. Existing research on health-related rumors, however, is limited in studying how various agents collaborate with each other to debunk rumors. This study utilizes content analysis to code the text data of health-related rumor cases in China during the COVID-19 pandemic. The study found that socialized rumor-debunking models could be divided into the following five categories: the government-led model, the media-led model, the scientific community-led model, the rumor-debunking platform-led model, and the multi-agent collaborative model. In addition, since rumors in public health crises often involve different objects, rumor refutation requires various information sources; therefore, different rumor-debunking models apply. This study verifies the value of socialized collaborative rumor debunking, advocates and encourages the participation of multiple agents of socialization and provides guidance for establishing a collaborative rumor-debunking model, thereby promoting efficient rumor-debunking methods and improving the healthcare of society.