|dc.description.abstract||Pesticides are widely used in the world due to their importance in agricultural production, especially in developing countries, where their use is high. Different health effects such as adverse reproductive outcomes, neurological disorders and cancers have been associated with pesticide exposure. Populations can be exposed to pesticides via different pathways, such as their occupation or via the environment, when pesticides applied to agricultural fields are transported from their intended treatment sites to neighboring residential areas. Environmental exposure to pesticides can occur through several pathways, such as spray drift, volatilization and dispersion, while take-home pathway and personal use can also contribute to pesticide exposure within the living environment. There are different methods and techniques described in the literature, which are used to assess environmental exposure to pesticides. Measurement techniques, such as bio-monitoring and the collection of environmental samples have been used to determine environmental exposure to pesticides. The main advantage of bio-monitoring is that the actual total pesticide exposure (the dose) of a subject is measured, but short half-lives of most biomarkers limit their application to short-term health effects and small study populations due to high costs. Modelling techniques, making use of geographic information systems, have been developed recently and have become one of the preferred techniques when researchers want to study long-term health outcomes related to environmental pesticide exposure in large study populations. However, validation studies are generally lacking for these models, which represents a problem for the use of these techniques.
Currently, a new prospective cohort study in the city of Molina, Chile, has been initiated to study chronic health effects related to environmental factors (such as pesticides). The aim of the Maule Cohort (MAUCO) is to enroll 10,000 subjects aged 38 to 74 years living in the city of Molina and follow them up for 10 years. As this region is heavily involved
in agricultural activities and this cohort focusses on chronic, long-term health effects, past environment exposure to pesticides is one of the main interests. Geospatial modelling, making use of the subjects’ residential history, data on agricultural land-use, and (historical) pesticide use would be the most suitable in this context to determine (past) environmental exposure to pesticides. In addition, a sub-study, making use of biomarkers and environmental samples, is recommended to determine validity of the modelled environmental pesticide exposures.||