Depression in later life is one of the most prevalent conditions forecasted to rise to the second most burdensome health condition worldwide by 2020. Using data from the 2004 Study of Health Ageing and Retirement in Europe (SHARE: release 1) on 857 Greek males and 1,032 females aged 50 or higher this study explores, firstly, associations of socio-demographic and health related indicators with depressive symptoms (EURO-D) and, secondly, attempts to identify patterns and structures among them. To achieve the first objective, the 12-item summated EURO-D scale is used in binary form with a cut-off point clinically validated by the EURODEP. Use of logistic regression pinpoints strong associations with gender, years of education, co-morbidity, disability, cognitive function and past depression. Women, less educated persons, those with poor physical health, declining cognitive function and a history of depression are significantly more at risk of scoring higher than three at the EURO-D scale. The role of age is not as clear. To achieve the second objective, multiple correspondence analysis is used in the first instance and factor analysis for binary data subsequently; two components are identified within EURO-D and continuous factor scores are produced. These factors are called ''affective suffering'' and ''motivation''. Linear regression models reveal that the first component is responsible for the gender while the second for the age differentials in EURO-D; additionally we find that, apart from physical health indicators which are strongly related to both factors, other associations differ. Further exploration of this differentiation seems of interest, particularly as there is an indication that ''motivation'' may be an affectively neutral condition.