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    Comparison of GAM and DLNM Methods for Disease Modeling in Environmental Epidemiology
    (2021) Karadağ, Mehmet; Kul, Seval; Yologlu, Saim; Boğan, Mustafa; Al, Behcet
    ABSTRACT Objective: In this study, it was aimed to compare the performance results of the methods modeled by using generalized additive models (GAM) and distributed lag non-linear models (DLNM) methods from real data of three different outcome variables of three separate diseases related to air pollution. Material and Methods: The data were retrospectively obtained from three hospitals under the General Secretariat of Gaziantep province public hospitals for a total of 1,916 days between 01 January 2009 and 31 March 2014. Response variables were number of the emergency unit admission, hospitalization and mortality due to asthma, chronic obstructive pulmonary disease (COPD) and pneumonia. The response variables were estimated by GAM and DLNM methods by building four different models and the performances of the models were compared. Results: When the estimation performances of GAM and DLNM methods are compared for each of the dependent variables in the prediction of hospitalizations due to asthma, GAM model IV [Akaike Information Criteria (AIC) (4,280.63)] values were found to perform the best. It was observed that DLNM method performed better than GAM in models established for the prediction of almost all other dependent variables. For when compare the odds ratio (OR) plot estimated on particulate matter (PM10); it was seen that GAM method made predictions with lower standard error compared to DLNM methods. Conclusion: When the models created with each dependent variable were compared; it was generally observed that superior performance was obtained from the DLNM method. However, the lowest standard error in the OR charts were observed in the models using the GAM method.