1. DS Rohlman, T Moomey, K Galvin, M Fuchs, E Hohn, A Kirk, L Patterson 2011 National Symposium on Agriculture, Forestry, & Fishing Health & Safety June 26-30, 2011 CONFLICT OF INTEREST OHSU and Dr. Rohlman have a significant financial interest in Northwest Education Training and Assessment, LLC, a company that may have a commercial interest in the results of this research and technology. This potential conflict of interest was reviewed and a management plan approved by the OHSU Conflict of Interest in Research Committee was implemented. rohlmand@ohsu.edu

2. Previous work…  Adults may have occupational exposure to pesticides and their family may also get secondary exposure from pesticides transferred from work to home  Levels of pesticides found in dust in homes and urinary metabolites of children are higher in agricultural vs. non-agricultural communities  Pesticide residues are found in blood/urine of nearly all people sampled in US

3. ENVIRONMENT Living in AG community Proximity of homes to field Number of AG adults in home Time of year – spray season OCCUPATION Working in AG Type of job (thinning/applying) Type of crop WORK/HOME PRACTICES Use of PPE at work Home hygiene Residential use of pesticides Diet

4. Measuring Pesticide Exposure  Biological Samples: blood, urine, breast milk, hair, hand wipes, saliva (e.g., pesticide, metabolites, cholinesterase inhibition)  Environmental Monitoring: indoor air, dust samples (vehicle/home), surface wipes  Surrogate Measures: pesticide use, occupational group, duration of exposure, proximity to agricultural field

5. Exposure Classification Exposure classification varies across studies ranges from residence in an agricultural community to occupational group to biomarkers of exposure Need to improve measure of exposure Most studies do not include a measurement of exposure Exposed vs. Controls Cost and Resources Need to be able to correlate current level of exposure with observed effects

6. Improving Self-Report  Farmworker populations may have complex work histories  Aid recall by incorporating memory aids – life events with in questionnaire (Hoppin et al., 1998; Engel et al., 2001; Zahm et al., 2001)  Can develop algorithms to calculate relative exposure scores  Weight activities based on relative exposure potential

7. Agricultural Children at Risk Previous work found OP residues in house dust in homes * Current Project: Identify and characterize pesticide exposures in the homes of agricultural workers, and Determine if there are neurodevelopmental changes by relating those exposures to neurobehavioral performance of children * Rothlein et al., 06

8. How do we measure exposure? Parents’ Job Classification applicators, general orchard workers, packers, non-agriculture Lifetime Exposure Questionnaire Opportunities for potential exposure across child’s lifetime Prenatal to current time Dust Samples Analyzed for Guthion, Phosmet, Chlorpyrifos, and Malathion

9. Non-Agricultural (N=28) Agricultural (N=44) Age of Child9.1 (2.6)8.1 (2.1) % Hispanic45%91% Housing House/Apartment Cabin/Trailer 93% 7% 70% 30% Ownership Own Rent Borrow 86% 14% -- 31% 36% 33% Live Next to Field48%72% Moved in Past Year1 family (4%)5 families (11%)

10. Job Classifications Working in Agriculture General Orchard Worker Mixer/Loader/Ap plicator Sorter/Packe r Nursery Work FATHER44%16%37%2% MOTHER49%6%43%3%

11. Life History Calendar (icon-based questionnaire) - History of child: prenatal to present - Use life events to assist recall - Summary score = lifetime exposure Pilot tested with families living in agricultural vs. Urban areas Differences found between the groups Lifetime Exposure Questionnaire

12. Non-AgriculturalAgricultural Mean186 (108)342 (149) Range47-49590-766 Living next to an orchard Number of people working in agriculture Pesticide use at work and home p < 0.01

13. Dust Samples Majority of homes had at least one detectable pesticide level – although levels were low (80% of Non-Agricultural and 90% of Agricultural) However, majority of Agricultural homes (82%) had 2 or more detectable levels of pesticides compared to Non-Agricultural homes (45%)

14. GuthionMalathionPhosmetChlorpyrifos Farmworkers 1999 5.3 (0.30-16.0) 0.18 (0.05-1.4) 4.4 (0.16-22.0) 0.13 (0.01-1.2) Agricultural 2008 0.03 (0.01- 0.6) 0.03 (0.01-3.4) 0.02 (0.004-0.17) 0.02 (0.01-0.5) Non-Agricultural 2008 0.04 (0.01-0.05) 0.02 (0.01-0.13) 0.02 (0.005-0.4) 0.02 (0.01-0.95)

15. Conclusions  Multiple methods to characterize pesticide exposure in children living in agricultural community  Home dust samples and parental occupation – current exposure  Lower levels in homes consistent with reduction in use of OPs  Lifetime exposure questionnaire – exposure across life of child as well as current exposures  Both Agricultural and non-Agricultural children have opportunities for exposure

16. Conclusions  Correlation between home residues and scores (r = 0.37) indicate this questionnaire provides information about potential exposure opportunities  Provides an alternative, inexpensive measure of potential pesticide exposure – both quantitative and qualitative information

17. Acknowledgements UW and the PNASH Center (U50 OH007544; PI: Fenske) OHSU-CROET National Institute of Occupational Safety and Health (NIOSH) Advisory Board Members (Columbia Gorge Fruit Growers, OSU Ag Extension) Families that participated Research Team Silvia Huszar Tara Moomey Andrew Kirk Andrew Nilsen Elliot Hohn Martha Fuchs Lindsey Patterson Nick Classen Cassy Dinius Kendra Broadwater Gwen Schultz Lindsay Nakaishi Naima Laharnar Kendra Evans Kent Anger