Bibliometric analysis of cardiometabolic disorders studies involving NO2, PM2.5 and noise exposure - Yu-Kai Huang; Rosie Hanneke; Rachael M. Jones (BMC, 2019)
Abstract Background This study uses bibliometric analysis to describe the state of research about the association of NO2, PM2.5 and noise exposures - three traffic-related pollutants - with cardiometabolic disorders. Methods We retrieved references published 1994-2017 from Scopus and classified references with respect to exposure, health outcome and study design using index keywords. Temporal trend, top cited references, used index keywords and the number of hypothesis testing and non-hypothesis testing study design for each group were identified. Results Results show PM2.5 is the most frequently studied exposure (47%), followed by both NO2 and PM2.5 exposure (29%). Only 3% of references considered multiple exposures between NO2 and/or PM2.5 and noise, and these were published after 2008. While we observed a growing trend in studies with NO2 and/or PM2.5 and noise and diabetes in the last decade, there is a diminishing trend in studies with noise and diabetes. Different patterns of study designs were found through H/NH ratio, the number of references classified as having a hypothesis (H)-testing design relative to the number of references classified as having a non-hypothesis (NH)-testing design. Studies with NO2 and/or PM2.5 exposure are more likely to have a H-testing design, while those with noise exposure are more likely to have a NH-testing design, such as cross-sectional study design. Conclusions We conclude with three themes about research trends. First, the study of simultaneous exposures to multiple pollutants is a current trend, and likely to continue. Second, the association between traffic-related pollutants and diabetes and metabolic symptoms is an area for growth in research. Third, the transition to the use of H-testing study designs to explore associations between noise and cardiometabolic outcomes may be supported by improved understanding of the mechanism of action, and/or improvements to the accuracy and precision of air pollution and noise exposure assessments for environmental health research.