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Prevalence of exposure to solvents, metals, grain dust, and other hazards among farmers in the Agricultural Health Study

Journal of Exposure Science & Environmental Epidemiology volume 12, pages 418–426 (2002)Cite this article

Abstract

Exposures to multiple chemical, physical, and biological agents in agricultural work environments can result in confounding that may obscure or distort risks observed in epidemiologic studies. The Agricultural Health Study (AHS) is a large epidemiology study being conducted to investigate health risks among pesticide applicators and their families. During enrollment in the AHS, questionnaires were administered to over 52,000 licensed pesticide applicators from North Carolina and Iowa, who were mostly farmers. Questions about the frequency of various farming tasks were used to estimate the prevalence of exposure to solvents (25%), metals (68%), grain dusts (65%), diesel exhaust fumes (93%), and other hazards, including exposure to pesticides. Most of the farmers in the AHS reported performing routine maintenance tasks at least once a month, such as painting (63%), welding (64%), and repair of pesticide equipment (58%). The majority of farmers (74% in North Carolina; 59% in Iowa) reported holding nonfarm jobs, of which the most frequent were construction and transportation. The majority of the farmers enrolled in the AHS (55%) also reported that they mixed or applied pesticides on 10 or more days per year. The associations between the use of pesticides and the frequency with which the farmers in the AHS reported performing various types of specific farming activities were assessed to evaluate potential confounding. Confounding risk ratios calculated for these activities suggest that the magnitude of bias due to confounding is likely to be minimal.

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Authors and Affiliations

  1. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Occupational Epidemiology Branch, 6120 Executive Boulevard, EPS8110, Rockville, 20892-7240, Maryland, USA

    JOSEPH COBLE, LAWRENCE ENGEL, OMUR CINAR ELCI, MUSTAFA DOSEMECI & MICHAEL ALAVANJA

  2. National Institute of Environmental Health Sciences, Epidemiology Branch, MD A3-05, PO Box 12233, Research Triangle Park, 27709, North Carolina, USA

    JANE A HOPPIN

  3. Department of Epidemiology, The University of Iowa, C 21-L GH, Iowa City, 52242, Iowa, USA

    CHARLES F LYNCH

Authors
  1. JOSEPH COBLE
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  2. JANE A HOPPIN
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  3. LAWRENCE ENGEL
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  4. OMUR CINAR ELCI
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  5. MUSTAFA DOSEMECI
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  6. CHARLES F LYNCH
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  7. MICHAEL ALAVANJA
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Correspondence to JOSEPH COBLE.

Appendix: CRR

Appendix: CRR

The CRR (Table 10) is defined as the ratio of the risk estimate obtained when ignoring confounding divided by the risk estimate obtained after adjustment for confounding. The CRR provides a general measure to estimate the magnitude of bias from a confounding factor (Breslow and Day, 1980). The CRR is calculated from the prevalence of exposure to the confounding factor among subjects who are exposed to the agent of interest (p1), the prevalence of exposure to the confounding factor among subjects who are not exposed to the agent of interest (p2), and the strength of the association between the confounding factor and the disease (ORc). Interestingly, the CRR is not affected by the strength of the association between the exposure and outcome of interest. Given an exposure of interest (E), and a confounding factor (C), the CRR is calculated from Eq. (1):

Table 10 CRRs for different risks from confounding exposure (ORc) and prevalences of exposure to confounding variable among subjects exposed to E (p1) and not exposed to E (p2)
Full size table

where:

ORa=odds ratio after stratification by C (adjusted);

ORp=odds ratio ignoring C (crude or pooled);

ORc=odds ratio for confounder C after stratification by exposure E;

p1=prevalence of exposure to C among those exposed to E;

p2=prevalence of exposure to C among those not exposed to E.

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COBLE, J., HOPPIN, J., ENGEL, L. et al. Prevalence of exposure to solvents, metals, grain dust, and other hazards among farmers in the Agricultural Health Study. J Expo Sci Environ Epidemiol 12, 418–426 (2002). https://doi.org/10.1038/sj.jea.7500248

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