Regional Character, Restaurant Size, and Food Safety Risk: Evidence from Food Safety Violation Data in Gansu Province, China

• Published in: Journal of food protection Vol. 83; no. 4; pp. 677 - 685
• Main Authors: Sha, Yongzhong, Song, Xiangrong, Zhan, Jian, Lu, L I, Zhang, Qingxia, Lu, Yao
• Format: Journal Article
• Language: English
• Published: United States Elsevier Limited 01.04.2020
• Subjects: Catering; China; Customer services; Data processing; Economic analysis; Economic development; Economics; Food; Food Inspection; Food Safety; Food service; GDP; Gross Domestic Product; Humans; Hypotheses; Illnesses; Influence; Inspection; Low income groups; Population density; Public Health; Regions; Regression analysis; Regression models; Resource allocation; Restaurants; Restaurants - standards; Restaurants - statistics & numerical data; Risk analysis; Safety; Social responsibility; Supervision; Violations; China; Food safety violation; Economic development; Restaurant management; China; Population density; Food safety risk
• ISSN: 0362-028X; 1944-9097
• DOI: 10.4315/0362-028X.JFP-19-457

Restaurants are a place where food is prepared and cooked directly for customers. Food safety in restaurants is a public health concern and a multidisciplinary issue that needs to be explored. To protect the health of consumers and identify external factors that may affect food safety risk, this study explores how economic development and population density at the local level relate to food safety inspection outcomes in restaurants of different sizes. Using food safety violation data from 2017 and 2018, we categorized restaurants in Gansu Province, China, into small and large ventures to examine the relationships among regional character, restaurant size, and food safety risk. Data were analyzed using Mann-Whitney U tests and negative binomial regression models. Our results show that large restaurants have a higher food safety risk than small restaurants. Moreover, the region with the lowest level of economic development had the highest food safety risk, while the region with the lowest population density had insufficient local inspections. By providing insight into which establishments demonstrate the highest food safety risks, our findings contribute to the development of processes that seek to effectively identifying food safety risks.