Living alone, limited personal social networks are, according to theliterature, factors that contribute to experience loneliness. It is known thatthe last stage of the life cycle is strongly marked by generational loss, beingmarked in this phase, beyond the network shrinkage, reducing opportunities forrenewal along with lower energy to activate, mobilize and maintain active linksof the network (Sluzki, 1996).

To determine the predictors of loneliness in a resident population in centralPortugal.

300 elderly people (mean age = 74.03/SD = ± 8.511) were surveyed. The sample wasassessed with the UCLA Loneliness scale, EQ5D, Lubben social networks and asmall sociodemographic questionnaire. The UCLA Loneliness presentedreliability, measured by the Cronbach's alpha coefficient (0.905).

To determine loneliness predictors a binary logistic regression was performed, with seven independent variables “age”, “sex”, “seeyour family”, “having spouse”, “Lubben socialnetworks”, “level of education” and “EQ5 health”. Thefull model containing all predictors was statistically significant, c2(15, N = 300) = 86.801, p <0.001. The model as a whole explained 26.1% (Cox and Snell R2) and 39.2% (R2 Nagelkerke) variation and correctly classified84.3% of cases. Logistic regression showed that “age” (p = 0.055), “sex” (p = 0.091), “sees his family”(p = 0.023), “spouse” (p <0.001), “Lubben socialnetworks”(p = 0.027),“level of education ”(p = 0.038)and“ health EQ5 ”(p<0.001) were loneliness predictors.

Given these results social intervention for active citizenship, networked, withthe elderly population is suggested.