Depression is important issue with aging of global population. Previously we have proposed a method to evaluate the mental health status of a person by his or her voice and developed a smartphone-based system to monitor mental health from voice during a call. Although the system has excellent continuous monitoring capability, it has not enough specificity for screening. Therefore, in this study we propose an evaluation indicator to assess depression status in the elderly, based on multivariate analysis using the emotional components of the voice data collected in the aforementioned system and the BDI score. The voice emotion data on subjects was divided into two groups according to BDI score, one where doctor's diagnosis was deemed necessary and the other not so. A significant difference between the two groups was observed in t-Test when the mean of the evaluation indicator estimated using data of each group and applying logistic regression prediction equation was compared. Moreover, a performance corresponding to AUC of approximately 0.75 was achieved in the ROC curve of the derived evaluation indicator. The results suggest that a new method to evaluate depression using voice has likely been developed.