Application of log-linear models to malaria patients in Thailand

Abstract

Malaria is a common infectious disease in many tropical countries, including Thailand. The country is located geographically in a tropical zone and the transmission of malaria is particularly common in some regions, for instance in Tak province. The objective of this study is to identify risk factors causing malaria in Tak province in the rainy season by using log- linear models. Tests of independence are used (chi-square and Cramer's V- value tests) to find out the relationships between any two variables. In addition two- and three-dimensional log-linear models are used to obtain estimated parameters and expected frequencies for these models. Amongst the models fitted, the best are chosen based on the analysis of deviance. The results of this study show that most observed variables are significantly related with p-values < 0.05. Causes of migration and reasons for staying overnight are highly related to personal variables. Thus, it can be concluded that two of the risk factors for malaria are causes of migration and reasons for staying overnight. Knowledge of prevention is also related to personal variables. Therefore, knowledge of prevention was concluded to be a risk factor affecting prevalence of malaria. For each set of three variables, the best model shows interaction terms of variables that have a relationship but there are no interactions of three effects in these best models. Copyright (C) 2000 John Wiley and Sons, Ltd.