Prediction Model for Self-Assessed Health Status in Flood-Prone Area of Bangladesh

Abstract

Bangladesh is a frequently affected by river flood and flash flood because of its geographical location. Along with the number of vulnerabilities, flood is cause sever health related problems. Thus objective of this study was to develop a prediction model for self-assessed health for the people of flood-prone area of Bangladesh. A CHAID technique is applied to predict the self-assessed health status. Data was collected from 883 individuals who were selected applying multistage random from four selected flood affected districts - Sunamgonj, Chattogram, Jamalpur and Gaiandha of Bangladesh. It is observed that more than 54% people of the flood affected area had reported that they were in poor health condition. In addition, food scarcity, worried about future, health awareness, use of hygienic toilet and education level were found the influential factors for self-assessed health status. However, food scarcity was the most influential factors for the prediction model. Accuracy, Precision, Recall and F1 Score for the training model were found 75.1%, 82.01%, 74.5% and 78.1% respectively whereas for test model were 74.1%, 85.5%, 71.0% and 77.6% respectively. The prediction model would assist to identify people who might be under risk in the flood affected area and also can mitigate health related disaster in the area.