1. A principal factor analysis to characterize agricultural exposures among Nebraska veterans.
- Author
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Weissenburger-Moser L, Meza J, Yu F, Shiyanbola O, Romberger DJ, and LeVan TD
- Subjects
- Adult, Aged, Aged, 80 and over, Agricultural Workers' Diseases epidemiology, Agrochemicals adverse effects, Agrochemicals analysis, Air Pollutants, Occupational adverse effects, Air Pollutants, Occupational analysis, Animals, Cross-Sectional Studies, Dust, Factor Analysis, Statistical, Farmers, Female, Humans, Livestock, Male, Middle Aged, Nebraska epidemiology, Occupational Exposure adverse effects, Pulmonary Disease, Chronic Obstructive epidemiology, Surveys and Questionnaires, Agricultural Workers' Diseases etiology, Agriculture, Environmental Monitoring methods, Occupational Exposure analysis, Pulmonary Disease, Chronic Obstructive etiology, Veterans
- Abstract
Agricultural workers are at an increased risk of developing chronic respiratory disorders. Accurate estimation of long-term agricultural exposures based on questionnaires has been used to improve the validity of epidemiologic investigations and subsequent evaluation of the association between agricultural exposures and chronic diseases. Our aim was to use principal factor analysis (PFA) to distill exposure data into essential variables characterizing long-term agricultural exposures. This is a cross-sectional study of veterans between the ages of 40 and 80 years and who worked on a farm for ≥2 years. Participant characteristics were: 98.1% were white males with a mean age 65±8 (SD) years and 39.8% had chronic obstructive pulmonary disease. The final model included four factors and explained 16.6% of the variance in the exposure data. Factor 1 was a heterogeneous factor; however, Factor 2 was exclusively composed of exposure to livestock such as hogs, dairy and poultry. Factor 3 included exposures from jobs on or off the farm such as wood dust, mineral dust, asbestos and spray paint. Crop exposure loaded exclusively in Factor 4 and included lifetime hours of exposure and maximum number of acres farmed in the participants' lifetime. The factors in the final model were interpretable and consistent with farming practices.
- Published
- 2017
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