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Can smartphone data identify the local environmental drivers of respiratory disease?
Environmental Research ( IF 7.7 ) Pub Date : 2020-01-07 , DOI: 10.1016/j.envres.2020.109118
Penelope J Jones 1 , Iain S Koolhof 2 , Amanda J Wheeler 3 , Grant J Williamson 4 , Christopher Lucani 4 , Sharon L Campbell 5 , David M J S Bowman 4 , Fay H Johnston 5
Affiliation  

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.

中文翻译:

智能手机数据能否识别出当地呼吸系统疾病的驱动因素?

哮喘和过敏性鼻炎(或花粉症)是普遍存在的慢性健康状况,季节性影响着相当一部分人口。两者通常都由包括空气过敏原,空气质量和天气在内的环境条件触发或加剧。通过允许大规模,实时收集日常症状,智能手机技术提供了识别环境驱动因素的新机会。然而,到目前为止,很少有研究探索该技术的潜力,以提供有关环境-症状关系的有用的流行病学数据。在这里,我们使用来自智能手机应用程序“ AirRater”的数据来检查哮喘和过敏性鼻炎症状与天气,空气质量和澳大利亚塔斯马尼亚州霍巴特的花粉负荷之间的关系。我们利用三年内应用程序用户记录的症状数据,并使用时间序列分析来评估症状与环境协变量之间的关系。症状与颗粒物(IRR 1.06,95%CI:1.04-1.08),最高温度(IRR 1.28,95%CI:1.13-1.44)和包括桦木的花粉类群有关(IRR 1.04,95%CI:1.02-1.07)。 ,柏科(IRR 1.02,95%CI:1.01-1.04),桃金娘科(IRR 1.06,95%CI:1.02-1.10)和禾本科(IRR 1.05,95%CI:1.01-1.09)。这些花粉类群的重要性随季节变化,与哮喘(肺)症状相比,与过敏性鼻炎(眼/鼻)相关的类群更多。我们的结果与已建立的流行病学证据相吻合,同时提供了重要的本地见解,包括症状与桃金娘科花粉之间的关联。
更新日期:2020-01-07
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