Determinants of residential pesticide contamination in vineyard regions: an indoor surface-based structural equation modeling approach.

backgroundIndoor contamination by agricultural pesticides and its determinants remain poorly characterized.

objectiveThis study investigates the influence of outdoor environmental factors, residential characteristics, and occupant behaviors on pesticide contamination inside homes.

methodsIn 2020 and 2021, we collected surface wipe samples from 31 homes near vineyards during the peak pesticide spraying season, including dusty high surfaces (tops of doors, windows, shelves, furniture; n = 116), frequently touched surfaces (n = 272), and floors (n = 128). Eight fungicides were analyzed. Data on household characteristics and behaviors, home features and local environmental factors were gathered through questionnaires and databases. To capture some key processes of pesticide intrusion and removal, we developed specific scores from factors related to cleaning practices, air exchange, and track-in via residents and pets. We applied structural equation modeling to estimate both direct and indirect effects of potential determinants on indoor pesticide contamination for the three surface types. Three latent variables were included in the models: outdoor and indoor contamination, estimated through measured pesticide surface loadings, and household structure, estimated by socio-demographic data on occupants. Results were reported as standardized β coefficients.

resultsOnly two models achieved satisfactory fit levels (high surfaces and frequently touched surfaces). For high surfaces, pesticide contamination was significantly associated with local annual pesticide purchases (β = 0.48, p = 0.037), occupant track-in (β = 0.22, p = 0.033), and households with active adults and children (β = -0.48, p = 0.031), while air exchange in the room had no significant effect (β = -0.03, p = 0.74). For frequently touched surfaces, contamination was positively associated with local annual pesticide purchases (β = 0.79, p < 0.001), air exchange (β = 0.16, p = 0.02), and occupant track-in (β = 0.12, p = 0.06). In contrast, cleaning was negatively associated with contamination (β = -0.36, p < 0.001) while the presence of active adults and children was not (β = -0.11, p = 0.53). SIGNIFICANCE: These findings refine our understanding of indoor pesticide contamination sources and can inform targeted interventions to reduce exposure among rural populations. IMPACT: Our research provides new insights into residential pesticide contamination in agricultural areas through an extensive collection of surface samples from homes near vineyards. Our results suggest a spatial and temporal gradient of indoor contamination. High surfaces may accumulate long-term pesticide residues, while floors could reflect more recent contamination. Frequently touched surfaces showed intermediate contamination. Outdoor-indoor transfers, driven by air exchange and track-in, appear to affect these surfaces differently. Frequent cleaning seems to help reduce contamination, and household characteristics may influence pesticide distribution. These findings may guide further research efforts to better understand contamination pathways and help refine future mitigation strategies.