Variability and predictors of weekly pesticide exposure in applicators from organic, sustainable and conventional smallholder farms in Costa Rica

Samuel Fuhrimann, Philipp Staudacher, Christian Lindh, Berna Van Wendel De Joode, Ana M. Mora, Mirko S. Winkler, Hans Kromhout

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskriftPeer review

8 !!Citations (SciVal)


Objective: Estimates of pesticide exposure among applicators from low- and middle-income countries (LMICs) are scarce, and exposure assessment methods are sometimes costly or logistically unfeasible. We examined the variability in weeklong pesticide exposure among applicators in Costa Rica and its predictors.

Methods:  We conducted a cross-sectional survey among 221 pesticide applicators from organic, sustainable and conventional farms in 2016. We administered structured questionnaires to assess pesticide application practices at two time points (4-6 weeks apart). We adapted an existing algorithm to fit the context of smallholders and derive weekly pesticide exposure scores. We used linear mixed-effect models to examine within-worker and between-worker score variability. We then identified sociodemographic and occupational predictors of weekly pesticide exposure scores. 

Results: We observed high within-worker and between-worker variability in weekly pesticide exposures (eg, up to 180-fold and 70-fold differences in average weekly exposures within and between workers, respectively; intraclass correlation coefficient=0.4). Applicators working on conventional and sustainable farms had exposure scores twofold and 1.5-fold higher than those working in organic farms, respectively. Farm workers who received training on pesticide use had weekly pesticide exposure scores of 33% (95% CI 1% to 55%) lower than those who did not receive any training. 

Conclusions: In this study of applicators from smallholder farms in Costa Rica, we determined the importance of collecting questionnaire data on self-reported pesticide use repeatedly due to its high variability within workers and absence of application records. Our questionnaire-based exposure algorithm could allow the calculation of semiquantitative estimates of average pesticide exposure for applicators from other LMICs.

Sidor (från-till)40-47
Antal sidor8
TidskriftOccupational and environmental medicine
StatusPublished - 2019 dec 12

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