Environmental factors associated with general practitioner consultations for allergic rhinitis in London, England: a retrospective time series analysis. Issue 12 (4th December 2020) - Todkill, Dan; de Jesus Colon Gonzalez, Felipe; Morbey, Roger; Charlett, Andre; Hajat, Shakoor; Kovats, Sari; Osborne, Nicholas J; McInnes, Rachel; Vardoulakis, Sotiris; Exley, Karen; Edeghere, Obaghe; Smith, Gillian; et al.
Abstract : Objectives: To identify key predictors of general practitioner (GP) consultations for allergic rhinitis (AR) using meteorological and environmental data. Design: A retrospective, time series analysis of GP consultations for AR. Setting: A large GP surveillance network of GP practices in the London area. Participants: The study population was all persons who presented to general practices in London that report to the Public Health England GP in-hours syndromic surveillance system during the study period (3 April 2012 to 11 August 2014). Primary measure: Consultations for AR (numbers of consultations). Results: During the study period there were 186 401 GP consultations for AR. High grass and nettle pollen counts (combined) were associated with the highest increases in consultations (for the category 216-270 grains/m 3, relative risk (RR) 3.33, 95% CI 2.69 to 4.12) followed by high tree (oak, birch and plane combined) pollen counts (for the category 260–325 grains/m 3, RR 1.69, 95% CI 1.32 to 2.15) and average daily temperatures between 15°C and 20°C (RR 1.47, 95% CI 1.20 to 1.81). Higher levels of nitrogen dioxide (NO2 ) appeared to be associated with increased consultations (for the category 70–85 µg/m 3, RR 1.33, 95% CI 1.03 to 1.71), but a significant effect was not found with ozone. Higher daily rainfall was associated with fewer consultations (15–20 mm/day; RR 0.812, 95% CI 0.674 to 0.980). Conclusions: Changes in grass, nettle or tree pollen counts, temperatures between 15°C and 20°C, and (to a lesser extent) NO2 concentrations were found to be associated with increased consultations for AR. Rainfall has a negative effect. In the context of climate change and continued exposures to environmental air pollution, intelligent use of these data will aid targeting public health messages and plan healthcare demand.