Univariate models of respiratory symptoms and environmental variables [Dataset]

Full description

This dataset represents spring and autumn results of Univariate General Linear Regression (GLM) significant predictors with alpha was set at .05. Positive and negative results are shown. Environmental measures on the same day, and up to 5 days of lag, predicted group mean respiratory symptom responses of 14 participants in S.E.Qld. Dependent measures were: SPEF, asthma score, wheeze, cough, difficulty breathing (dyspnea), reliever usage, preventer usage, itchy eyes, itchy nose, runny nose (rhinorrhea), sneezing, and blocked nose (congested nose). Air spora, compounds from air samples, pollutants and meteorological variables served as independent variables. They were: day length, mean atmospheric pressure, mean temperature, precipitation, mean windspeed, relative humidity at 9am, particulates < 10 microns (PM10), heard thunder, ozone (O3), nitrogen monoxide (NO), nitrogen dioxide (NO2), Myrtaceae pollen, Poaceae pollen, Pinus pollen, Asteraceae pollen, Casuarina pollen, Acacia pollen, "other" pollen, Cladosporium, Alternaria, "other" fungi, benzoic acid, benzaldehyde, alpha pinene, beta pinene, 1,8 cineole, camphor, limonene, linalyl acetate and linalool.