PubMed search strings for the study of agricultural workers' diseases

BACKGROUND: Several optimized search strategies have been developed in Medicine, and more recently in Occupational Medicine. The aim of this study was to identify efficient PubMed search strategies to retrieve articles regarding putative occupational determinants of agricultural workers' diseases. METHODS: We selected the Medical Subjects Heading (MeSH) term agricultural workers' diseases and six MeSH terms describing farm work (agriculture, agrochemicals NOT pesticides, animal husbandry, pesticides, rural health, rural population) alongside 61 other promising terms. We estimated proportions of articles containing potentially pertinent information regarding occupational etiology to formulate two search strategies (one "more specific," one "more sensitive"). We applied these strategies to retrieve information on the possible occupational etiology among agricultural workers of kidney cancer, knee osteoarthritis, and multiple sclerosis. We evaluated the number of needed to read (NNR) abstracts to identify one potentially pertinent article in the context of these pathologies. RESULTS: The "more specific" search string was based on the combination of terms that yielded the highest proportion (40%) of potentially pertinent abstracts. The "more sensitive" string was based on use of broader search fields and additional coverage provided by other search terms under study. Using the "more specific" string, the NNR to find one potentially pertinent article were: 1.1 for kidney cancer; 1.4 for knee osteoarthritis; 1.2 for multiple sclerosis. Using the sensitive strategy, the NNR were 1.4, 3.6, and 6.3, respectively. CONCLUSION: The proposed strings could help health care professionals explore putative occupational etiology for agricultural workers' diseases (even if not generally thought to be work related).