ArticleJournal of exposure science & environmental epidemiology2026
Determinants of residential pesticide contamination in vineyard regions: a structural equation modeling approach.
Article in Journal of exposure science & environmental epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundPrevious studies have associated pesticide exposure among people living near fields with adverse health outcomes. However, the factors influencing residential contamination by agricultural pesticides remain unclear.
objectiveThis study aims to assess the effect of the local environment, home characteristics, and occupant behaviors on residential contamination.
methodsIn 2021, wipe samples from outdoor and indoor surfaces were collected in 28 homes in Bordeaux vineyard region during peak pesticide spraying. Eight fungicides were analyzed by LC-MS/MS or GC-MS/MS. Environmental, residential, and occupant-related data were gathered through questionnaires and databases. Using multilevel structural equation modeling, we simultaneously examined the effects of multiple factors on pesticide contamination outdoors (Model 1, n = 227 samples) and indoors (Model 2, n = 543 samples), reporting standardized β coefficients.
resultsOutdoor pesticide contamination was positively associated with local vineyard areas (β = 0.79, p = <0.001) and the probability of a recent pesticide application (β = 0.34, p = 0.09). In contrast, daily wind speed (β = -0.54, p = 0.001), cumulative rainfall over the past month (β = -0.32, p = 0.03), and cleaning (β = -0.37, p < 0.001) were negatively associated with outdoor contamination. Indoor contamination was significantly associated with the annual local purchases of pesticides (β = 0.79, p < 0.001) and pesticide track-in by occupants (β = 0.16, p < 0.001). Conversely, households with active adults and children (β = -0.49, p < 0.01), cleaning (β = -0.40, p < 0.001), and surface contact frequency (β = -0.30, p < 0.001) showed significant negative associations. Air exchange exhibited only a weak suggestive association (β = 0.07, p = 0.09). Both models demonstrated good fit indices. SIGNIFICANCE: These results improve our understanding of residential pesticide contamination and could help inform the design of strategies to reduce exposure in rural populations. IMPACT STATEMENT: Residential pesticide contamination from agricultural field drift may represent an important exposure pathway in rural communities. Our study identifies key factors driving this contamination through comprehensive surface sampling both inside and outside homes near vineyards, using advanced statistical methods, such as structural equation modeling. We found that the main contributors include outdoor pesticide applications, meteorological conditions, track-in, and air exchange, while factors, such as cleaning practices and frequent contact with surfaces help mitigate contamination. These findings provide useful insights for designing targeted interventions to reduce exposure and inform public health strategies in agricultural regions.
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