OBJECTIVES: to produce a methodology for the risk ranking of farms located around proven or potential sources of contamination to prioritize the monitoring procedures in food production. DESIGN: environmental factors that can favour the risk of contamination of products of animal origin (POAO) around a pollutant source were identified. A scale of standardized scores was produced for each risk factor (RF) in order to obtain a risk-based classification. Subsequently, an algorithm was developed to obtain a relative risk assessment (RRA). SETTING AND PARTICIPANTS: in order to validate the proposed methodology, data of 80 livestock farms in a polluted area, enrolled in a previous study, were subjected to the RRA. Results of RRA were compared with contamination data. MAIN OUTCOME MEASURES: seven RFs were included in a mathematical formula used to classify each farm. RESULTS: a scoring system was produced for each RFs and an algorithm was developed to obtain RRA which is an estimate of the farm probability of having POAO contamination in comparison to other farms located in the same area potentially affected by chemical pollution based exclusively on site-specific environmental characteristics. In the case study used for validation, a significant relationship between RRA and contamination data was found. CONCLUSIONS: the proposed methodology is a useful tool to support the authorities responsible for the food safety in carrying out the monitoring of POAO in areas subject to environmental risks. It helps to rationalize resources and make controls more effective.
OBJECTIVES: to produce a methodology for the risk ranking of farms located around proven or potential sources of contamination to prioritize the monitoring procedures in food production. DESIGN: environmental factors that can favour the risk of contamination of products of animal origin (POAO) around a pollutant source were identified. A scale of standardized scores was produced for each risk factor (RF) in order to obtain a risk-based classification. Subsequently, an algorithm was developed to obtain a relative risk assessment (RRA). SETTING AND PARTICIPANTS: in order to validate the proposed methodology, data of 80 livestock farms in a polluted area, enrolled in a previous study, were subjected to the RRA. Results of RRA were compared with contamination data. MAIN OUTCOME MEASURES: seven RFs were included in a mathematical formula used to classify each farm. RESULTS: a scoring system was produced for each RFs and an algorithm was developed to obtain RRA which is an estimate of the farm probability of having POAO contamination in comparison to other farms located in the same area potentially affected by chemical pollution based exclusively on site-specific environmental characteristics. In the case study used for validation, a significant relationship between RRA and contamination data was found. CONCLUSIONS: the proposed methodology is a useful tool to support the authorities responsible for the food safety in carrying out the monitoring of POAO in areas subject to environmental risks. It helps to rationalize resources and make controls more effective.