Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia.
Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia; School of Natural Sciences, University of Tasmania, Hobart, TAS, 7001, Australia.
Environ Res. 2020 Mar;182:109118. doi: 10.1016/j.envres.2020.109118. Epub 2020 Jan 7.
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.
哮喘和过敏性鼻炎（或花粉症）是普遍存在的慢性健康问题，季节性地影响相当一部分人群。两者通常由环境条件触发或加重，包括气传过敏原、空气质量和天气。智能手机技术通过允许大规模实时收集日常症状，为识别环境驱动因素提供了新的机会。然而，迄今为止，很少有研究探讨这项技术在提供有关环境-症状关系的有用流行病学数据方面的潜力。在这里，我们使用来自智能手机应用程序“AirRater”的数据，来研究澳大利亚塔斯马尼亚州霍巴特的哮喘和过敏性鼻炎症状与天气、空气质量和花粉负荷之间的关系。我们借鉴了应用程序用户在三年期间记录的症状数据，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）和花粉类群有关，包括桦树（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因季节而异，与过敏性鼻炎（眼/鼻）症状相关的类群比与哮喘（肺）症状相关的类群更多。我们的结果与既定的流行病学证据一致，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。我们得出结论，智能手机数据可以成为环境流行病学的有用工具。
