PubMed search filters for the study of putative outdoor air pollution determinants of disease

Abstract

Objectives Several PubMed search filters have been developed in contexts other than environmental. We aimed at identifying efficient PubMed search filters for the study of environmental determinants of diseases related to outdoor air pollution. Methods We compiled a list of Medical Subject Headings (MeSH) and non-MeSH terms seeming pertinent to outdoor air pollutants exposure as determinants of diseases in the general population. We estimated proportions of potentially pertinent articles to formulate two filters (one more specific, one more sensitive'). Their overall performance was evaluated as compared with our gold standard derived from systematic reviews on diseases potentially related to outdoor air pollution. We tested these filters in the study of three diseases potentially associated with outdoor air pollution and calculated the number of needed to read (NNR) abstracts to identify one potentially pertinent article in the context of these diseases. Last searches were run in January 2016. Results The more specific filter was based on the combination of terms that yielded a threshold of potentially pertinent articles ≥40%. The more sensitive filter was based on the combination of all search terms under study. When compared with the gold standard, the more specific filter reported the highest specificity (67.4%; with a sensitivity of 82.5%), while the more sensitive one reported the highest sensitivity (98.5%; with a specificity of 47.9%). The NNR to find one potentially pertinent article was 1.9 for the more specific filter and 3.3 for the more sensitive one. Conclusions The proposed search filters could help healthcare professionals investigate environmental determinants of medical conditions that could be potentially related to outdoor air pollution.