Asthma and allergic rhinitis (or hay fever) are ubiquitous, chronic health conditions that seasonally affect a sizeable proportion of the population. Both are commonly triggered or exacerbated by environmental conditions including aeroallergens, air quality and weather. Smartphone technology offers new opportunities to identify environmental drivers by allowing large-scale, real-time collection of day-to-day symptoms. As yet, however, few studies have explored the potential of this technology to provide useful epidemiological data on environment- symptom relationships. Here, we use data from the smartphone app ‘AirRater’ to examine relationships between asthma and allergic rhinitis symptoms and weather, air quality and pollen loads in Hobart, Tasmania, Australia. We draw on symptom data logged by app users over a three-year period and use time-series analysis to assess the relationship between symptoms and environmental co-variates. Symptoms are associated with particulate matter (IRR 1.06, 95% CI: 1.04–1.08), maximum temperature (IRR 1.28, 95% CI: 1.13–1.44) and pollen taxa including Betula (IRR 1.04, 95% CI: 1.02–1.07), Cupressaceae (IRR 1.02, 95% CI: 1.01–1.04), Myrtaceae (IRR 1.06, 95% CI: 1.02–1.10) and Poaceae (IRR 1.05, 95% CI: 1.01–1.09). The importance of these pollen taxa varies seasonally and more taxa are associated with allergic rhinitis (eye/nose) than asthma (lung) symptoms. Our results are congruent with established epidemiological evidence, while providing important local insights including the association between symptoms and Myrtaceae pollen. We conclude that smartphone-sourced data can be a useful tool in environmental epidemiology.

Item Type:	Refereed Article
Keywords:	pollen, asthma, allergic rhinitis, Tasmania, smartphone, m-health, epidemiology
Research Division:	Health Sciences
Research Group:	Epidemiology
Research Field:	Environmental epidemiology
Objective Division:	Health
Objective Group:	Public health (excl. specific population health)
Objective Field:	Public health (excl. specific population health) not elsewhere classified
UTAS Author:	Jones, PJ (Dr Penelope Jones)
UTAS Author:	Koolhof, IS (Mr Iain Koolhof)
UTAS Author:	Wheeler, AJ (Dr Amanda Wheeler)
UTAS Author:	Williamson, GJ (Dr Grant Williamson)
UTAS Author:	Lucani, C (Mr Christopher Lucani)
UTAS Author:	Campbell, SL (Dr Sharon Campbell)
UTAS Author:	Bowman, DMJS (Professor David Bowman)
UTAS Author:	Johnston, FH (Professor Fay Johnston)
ID Code:	136663
Year Published:	2020
Web of Science® Times Cited:	16
Deposited By:	Menzies Institute for Medical Research
Deposited On:	2020-01-13
Last Modified:	2020-04-20
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