Pesticide Exposure of Residents Living Close to Agricultural Fields in the Netherlands:Protocol for an Observational Study

Background: Application of pesticides in the vicinity of homes has caused concern regarding possible health effects in residents living nearby. However, the high spatiotemporal variation of pesticide levels and lack of knowledge regarding the contribution of exposure routes greatly complicates exposure assessment approaches. Objective: The objective of this paper was to describe the study protocol of a large exposure survey in the Netherlands assessing pesticide exposure of residents living close ( Methods: We performed an observational study involving residents living in the vicinity of agricultural fields and residents living more than 500 m away from any agricultural fields (control subjects). Residential exposures were measured both during a pesticide use period after a specific application and during the nonuse period for 7 and 2 days, respectively. We collected environmental samples (outdoor and indoor air, dust, and garden and field soils) and personal samples (urine and hand wipes). We also collected data on spraying applications as well as on home characteristics, participants' demographics, and food habits via questionnaires and diaries. Environmental samples were analyzed for 46 prioritized pesticides. Urine samples were analyzed for biomarkers of a subset of 5 pesticides. Alongside the field study, and by taking spray events and environmental data into account, we developed a modeling framework to estimate environmental exposure of residents to pesticides. Results: Our study was conducted between 2016 and 2019. We assessed 96 homes and 192 participants, including 7 growers and 28 control subjects. We followed 14 pesticide applications, applying 20 active ingredients. We collected 4416 samples: 1018 air, 445 dust (224 vacuumed floor, 221 doormat), 265 soil (238 garden, 27 fields), 2485 urine, 112 hand wipes, and 91 tank mixtures. Conclusions: To our knowledge, this is the first study on residents' exposure to pesticides addressing all major nondietary exposure sources and routes (air, soil, dust). Our protocol provides insights on used sampling techniques, the wealth of data collected, developed methods, modeling framework, and lessons learned. Resources and data are open for future collaborations on this important topic

Role of Virulence Factors in Resistance of Avian Pathogenic Escherichia coli to Serum and in Pathogenicity

In chickens, colibacillosis is caused by avian pathogenic Escherichia coli (APEC) via respiratory tract infection. Many virulence factors, including type 1 (F1A) and P (F11) fimbriae, curli, aerobactin, K1 capsule, and temperature-sensitive hemagglutinin (Tsh) and plasmid DNA regions have been associated with APEC. A strong correlation between serum resistance and virulence has been demonstrated, but roles of virulence factors in serum resistance have not been well elucidated. By using mutants of APEC strains TK3, MT78, and χ7122, which belong to serogroups O1, O2, and O78, respectively, we investigated the role of virulence factors in resistance to serum and pathogenicity in chickens. Our results showed that serum resistance is one of the pathogenicity mechanisms of APEC strains. Virulence factors that increased bacterial resistance to serum and colonization of internal organs of infected chickens were O78 lipopolysaccharide of E. coli χ7122 and the K1 capsule of E. coli MT78. In contrast, curli, type 1, and P fimbriae did not appear to contribute to serum resistance. We also showed that the iss gene, which was previously demonstrated to increase resistance to serum in certain E. coli strains, is located on plasmid pAPEC-1 of E. coli χ7122 but does not play a major role in resistance to serum for strain χ7122

Pesticide Exposure of Residents Living Close to Agricultural Fields in the Netherlands: Protocol for an Observational Study

Background: Application of pesticides in the vicinity of homes has caused concern regarding possible health effects in residents living nearby. However, the high spatiotemporal variation of pesticide levels and lack of knowledge regarding the contribution of exposure routes greatly complicates exposure assessment approaches. Objective: The objective of this paper was to describe the study protocol of a large exposure survey in the Netherlands assessing pesticide exposure of residents living close (<250 m) to agricultural fields; to better understand possible routes of exposure; to develop an integrative exposure model for residential exposure; and to describe lessons learned. Methods: We performed an observational study involving residents living in the vicinity of agricultural fields and residents living more than 500 m away from any agricultural fields (control subjects). Residential exposures were measured both during a pesticide use period after a specific application and during the nonuse period for 7 and 2 days, respectively. We collected environmental samples (outdoor and indoor air, dust, and garden and field soils) and personal samples (urine and hand wipes). We also collected data on spraying applications as well as on home characteristics, participants' demographics, and food habits via questionnaires and diaries. Environmental samples were analyzed for 46 prioritized pesticides. Urine samples were analyzed for biomarkers of a subset of 5 pesticides. Alongside the field study, and by taking spray events and environmental data into account, we developed a modeling framework to estimate environmental exposure of residents to pesticides. Results: Our study was conducted between 2016 and 2019. We assessed 96 homes and 192 participants, including 7 growers and 28 control subjects. We followed 14 pesticide applications, applying 20 active ingredients. We collected 4416 samples: 1018 air, 445 dust (224 vacuumed floor, 221 doormat), 265 soil (238 garden, 27 fields), 2485 urine, 112 hand wipes, and 91 tank mixtures. Conclusions: To our knowledge, this is the first study on residents' exposure to pesticides addressing all major nondietary exposure sources and routes (air, soil, dust). Our protocol provides insights on used sampling techniques, the wealth of data collected, developed methods, modeling framework, and lessons learned. Resources and data are open for future collaborations on this important topic