Background: Multidisciplinary efforts to prospectively collect and analyze symptoms of hay fever are limited. We aimed to identify the characteristics of nasal and ocular symptoms of hay fever, using the AllerSearch smartphone application. Methods: This mobile health-based prospective observational study using the AllerSearch smartphone application was conducted between February 1, 2018, and May 1, 2020. Individuals who downloaded AllerSearch from Japan and provided comprehensive self-assessments (including 17 items related to quality of life [QoL]-related items) were included. The characteristics and risk factors for allergic rhinitis (AR) and allergic conjunctivitis (AC) were identified using hierarchical heat maps and multivariate logistic regression. Results: Of the 9041 participants with hay fever, 58.8% had AR and AC, 22.2% had AR, and 5.7% had AC. The AR–AC comorbid cohort showed worse symptoms of hay fever and QoL scores than the other cohorts. Factors (odds ratio, 95% confidence interval) associated with AR–AC included a lower age (0.98, 0.97–0.98), female sex (1.31, 1.19–1.45), liver disease (1.58, 1.26–2.35), dry eye disease (1.45, 1.30–1.63), unknown dry eye disease status (1.46, 1.31–1.62), contact lens use discontinuation during the hay fever season (1.69, 1.28–2.23), and bedroom flooring material other than hardwood, carpet, tatami, or vinyl (1.91, 1.16–3.14). Conclusions: Analysis of medical big data for hay fever performed using a mobile health app helped identify risk factors and characteristics of AC, AR, and AR–AC. Phenotyping of highly variable symptoms of hay fever, such as nasal and ocular symptoms, can facilitate better-quality clinical care.
Full Text Finder