國家衛生研究院 NHRI:Item 3990099045/13337
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    Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/13337


    Title: Prenatal exposure to air pollutants and childhood atopic dermatitis and allergic rhinitis adopting machine learning approaches: 14-year follow-up birth cohort study
    Authors: Huang, Y;Wen, HJ;Guo, YLL;Wei, TY;Wang, WC;Tsai, SF;Tseng, VS;Wang, SLJ
    Contributors: National Institute of Environmental Health Sciences
    Abstract: The incidence of childhood atopic dermatitis (AD) and allergic rhinitis (AR) is increasing. This warrants development of measures to predict and prevent these conditions. We aimed to investigate the predictive ability of a spectrum of data mining methods to predict childhood AD and AR using longitudinal birth cohort data. We conducted a 14-year follow-up of infants born to pregnant women who had undergone maternal examinations at nine selected maternity hospitals across Taiwan during 2000–2005. The subjects were interviewed using structured questionnaires to record data on basic demographics, socioeconomic status, lifestyle, medical history, and 24-h dietary recall. Hourly concentrations of air pollutants within 1 year before childbirth were obtained from 76 national air quality monitoring stations in Taiwan. We utilized weighted K-nearest neighbour method (k = 3) to infer the personalized air pollution exposure. Machine learning methods were performed on the heterogeneous attributes set to predict allergic diseases in children. A total of 1439 mother-infant pairs were recruited in machine learning analysis. The prevalence of AD and AR in children up to 14 years of age were 6.8% and 15.9%, respectively. Overall, tree-based models achieved higher sensitivity and specificity than other methods, with areas under receiver operating characteristic curve of 83% for AD and 84% for AR, respectively. Our findings confirmed that prenatal air quality is an important factor affecting the predictive ability. Moreover, different air quality indices were better predicted, in combination than separately. Combining heterogeneous attributes including environmental exposures, demographic information, and allergens is the key to a better prediction of children allergies in the general population. Prenatal exposure to nitrogen dioxide (NO2) and its concatenation changes with time were significant predictors for AD and AR till adolescent.
    Date: 2021-07-10
    Relation: Science of the Total Environment. 2021 Jul 10;777:Article number 145982.
    Link to: http://dx.doi.org/10.1016/j.scitotenv.2021.145982
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=0048-9697&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000655612500008
    Cited Times(Scopus): https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85102049936
    Appears in Collections:[Shu-Li Wang] Periodical Articles
    [Yue-Liang Guo] Periodical Articles
    [Hui-Ju Wen] Periodical Articles

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