Study on the correlation between the number of mushroom poisoning cases and meteorological factors based on the generalized additive model in Guizhou Province, 2023

• Main Authors: Sufang Xiong (Author), Anzhong Wu (Author), Ling Weng (Author), Li Zhang (Author), Muli Wu (Author), Haijiao Li (Author), Peipei Zuo (Author), Shu Zhu (Author), Jun Li (Author), Hua Guo (Author), Tao Long (Author)
• Format: Book
• Published: BMC, 2024-09-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.1186/s12889-024-20050-6; 1471-2458
• Keywords: Mushroom poisoning; Meteorological factors; Generalized additive model; Interaction; Public aspects of medicine; RA1-1270
• Source: BMC Public Health, Vol 24, Iss 1, Pp 1-9 (2024)

Abstract Background Mushroom poisoning is a significant food safety issue in Guizhou Province, China. Studies on this topic are essential for its prevention and control. We aimed to analyze the epidemiological characteristics of mushroom poisoning and study the correlation between its cases and meteorological factors in Guizhou Province. Methods We collected data on mushroom poisoning and meteorological factors in Guizhou Province in 2023. A descriptive analysis was conducted on the epidemiological features of mushroom poisoning and meteorological factors. We used Spearman correlation analysis and the generalized additive model to examine the relationship between meteorological factors and the number of mushroom poisoning cases. Results In 2023, mushroom poisoning cases in Guizhou Province were concentrated among individuals aged 20-59. Clinical symptoms were primarily gastrointestinal symptoms and occurrences peaked from June to October, mainly in the northeastern region of the province. Most incidents occurred in households. In 72 mushroom poisoning incidents where species were identified, 33 poisonous mushrooms were found. The number of mushroom poisoning cases in Guizhou Province was positively correlated with each meteorological factor(P < 0.05). The generalized additive model showed a significant nonlinear relationship between DGT, PRE, RHU, SSD, and the number of mushroom poisoning cases (P < 0.05). Interaction analysis showed that the risk of mushroom poisoning in Guizhou Province increased with the rising values of any two of these four meteorological factors. Conclusion Mushroom poisoning incidents in Guizhou Province are characterized by high-risk groups, seasonality, and specific high-incidence regions and places. Public awareness for high-risk groups and early warnings for high-incidence regions and places should be strengthened every summer and fall. There is a correlation between meteorological factors and the number of mushroom poisoning cases, suggesting that these factors could serve as early warning indicators for the prevention and control of mushroom poisoning.