Poisson Regression Model to Determine Factors of Microplastic Ingestion by African Catfish

Poisson regression model is used to investigate the relationship among pa-rameters when the response variable is a count data that follows Poisson distribution. The Poisson regression model is widely applied in various fields such as medical and epidemiological study. However, the appli-cation of this model in environmental science, particularly microplastic pollution is still limited. Small plastic particles with a size less than 5 mm or also known as microplastics are reported as an emerging pollutant in the aquatic environment. Microplastics have also been recognized as a serious threat to commercial fish through ingestion. Thus, the Poisson regression model was applied to determine factors that are contributed to the microplastic ingestion by African catfish. Three Poisson regression models were separately developed for each factor such as color, morphol-ogy, and environments. Based on the models, the significant difference was observed for all microplastic colors and morphology except for bead. Meanwhile, only two variables of water quality factor were significant and affected the number of ingested microplastics. In conclusion, the re-lationships between ingested microplastics and its factors was successfully represented using Poisson regression model.