TY - JOUR
T1 - Environmental factors associated with general practitioner consultations for allergic rhinitis in London, England
T2 - A retrospective time series analysis
AU - Todkill, Dan
AU - De Jesus Colon Gonzalez, Felipe
AU - Morbey, Roger
AU - Charlett, Andre
AU - Hajat, Shakoor
AU - Kovats, Sari
AU - Osborne, Nicholas J.
AU - Mcinnes, Rachel
AU - Vardoulakis, Sotiris
AU - Exley, Karen
AU - Edeghere, Obaghe
AU - Smith, Gillian
AU - Elliot, Alex J.
N1 - Publisher Copyright:
© Author(s) (or their employer(s)) 2020.
PY - 2020/12/4
Y1 - 2020/12/4
N2 - 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/m3, 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/m3, 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 (NO 2) appeared to be associated with increased consultations (for the category 70-85 μg/m3, 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) NO 2 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.
AB - 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/m3, 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/m3, 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 (NO 2) appeared to be associated with increased consultations (for the category 70-85 μg/m3, 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) NO 2 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.
KW - allergy
KW - epidemiology
KW - primary care
KW - public health
UR - http://www.scopus.com/inward/record.url?scp=85097310734&partnerID=8YFLogxK
U2 - 10.1136/bmjopen-2019-036724
DO - 10.1136/bmjopen-2019-036724
M3 - Article
SN - 2044-6055
VL - 10
JO - BMJ Open
JF - BMJ Open
IS - 12
M1 - e036724
ER -