Prediction Model for Demands of the Health Meteorological Information Using a Decision Tree Method

Abstract

Climate change affects human health and calls for health meteorological services. The purpose of this study is to find the significant predictors for the demands of the health meteorological information. This study used a descriptive design through structured self-report questionnaires. Data from 956 participants who were at least 18 years old and living in Busan, Korea, were collected from June 1 to July 31, 2009. The data was analyzed using a decision tree method, one of the data mining techniques by SAS 9.1 and Enterprise Miner 4.3 program. Two hundred and ninety participants (30.3%) demanded the information, and 505 of them (52.8%) perceived the necessity of health meteorological information. From the decision tree method, the predictors related to the demands of the health meteorological information were determined as "the perception of the necessity of health meteorological information," "the coping to the weather warnings" and "the importance of the weather forecasting in daily life." In Particular, the significant different variables in the perception of the necessity of health meteorological information were "female," "aged over 40" and "environmental diseases." Thus, the model derived in this study is considered for explaining and predicting the demands of health meteorological information. It can be effectively used as a reference model for future studies and is a suggested direction in health meteorological information service and policy development. We suggest health forecasting as a nursing service and a primary health care network for healthier and more comfortable life.