Prediction of symptomatic depression by discriminant analysis in Japanese community-dwelling elderly

Although a number of studies have examined depression risk factors for elderly persons, little attention has been paid to the prediction of individuals at risk. This study constructed a predictive model for discrimination between individuals at a higher risk of depression and normal subjects in Japanese community-dwelling elderly persons, using linear discriminant analysis. Data were collected from 754 non-institutionalized elderly men and women aged 65 years and older living in the community in Japan, using face-to-face interviews in 2002. Stepwise linear discrimination analysis was used to construct a predictive model to select individuals who have a higher risk of depression. The stepwise discriminant analysis selected the five predictor variables (frequent hearing problems, poor appetite, less financial leeway, low emotional support and less subjective usefulness) and yielded a statistically significant function (λ=0.816; χ2=113.0, df=5, p<0.001). This function showed that the rate of correct prediction was 78.2% for depressed. The calculated discriminate function based on the above five predictor variables (hearing problem, less appetite, less financial leeway, low emotional support and less subjective usefulness) is useful for detecting individuals at high risk of depression and preventing its development among community-dwelling elderly persons. Prospective studies are needed to confirm the validity and feasibility of the model for earlier screening for depression among such people.