Cargando…
Exploring aflatoxin contamination and household-level exposure risk in diverse Indian food systems
The present study sought to identify household risk factors associated with aflatoxin contamination within and across diverse Indian food systems and to evaluate their utility in risk modeling. Samples (n = 595) of cereals, pulses, and oil seeds were collected from 160 households across four diverse...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7588076/ https://www.ncbi.nlm.nih.gov/pubmed/33104713 http://dx.doi.org/10.1371/journal.pone.0240565 |
Sumario: | The present study sought to identify household risk factors associated with aflatoxin contamination within and across diverse Indian food systems and to evaluate their utility in risk modeling. Samples (n = 595) of cereals, pulses, and oil seeds were collected from 160 households across four diverse districts of India and analyzed for aflatoxin B1 using enzyme-linked immunosorbent assay (ELISA). Demographic information, food and cropping systems, food management behaviors, and storage environments were profiled for each household. An aflatoxin detection risk index was developed based on household-level features and validated using a repeated 5-fold cross-validation approach. Across districts, between 30–80% of households yielded at least one contaminated sample. Aflatoxin B1 detection rates and mean contamination levels were highest in groundnut and maize, respectively, and lower in other crops. Landholding had a positive univariate effect on household aflatoxin detection, while storage conditions, product source, and the number of protective behaviors used by households did not show significant effects. Presence of groundnut, post-harvest grain washing, use of sack-based storage systems, and cultivation status (farming or non-farming) were identified as the most contributive variables in stepwise logistic regression and were used to generate a household-level risk index. The index had moderate classification accuracy (68% sensitivity and 62% specificity) and significantly correlated with village-wise aflatoxin detection rates. Spatial analysis revealed utility of the index for identifying at-risk localities and households. This study identified several key features associated with aflatoxin contamination in Indian food systems and demonstrated that household characteristics are substantially predictive of aflatoxin risk. |
---|