Factors explaining the use of leisure time by older adults living in community in Spain in the context of their quality of life

Saturday, October 29, 2011
Hall 1-2 (San Jose Convention Center)
Brenda C. Torres Velásquez, M.Sc. , School of Sciences and Technology, University of Turabo, Gurabo, PR
Gloria Fernández-Mayoralas, PhD , Institute of Economics, Geography and Demography (IEGD), Spanish National Research Council (CSIC), Madrid, Spain
Fermina Rojo-Pérez, PhD , Institute of Economics, Geography and Demography (IEGD), Spanish National Research Council (CSIC), Madrid, Spain
José Manuel Rojo-Abuin, M.Sc. , Statistical Analysis Unit (CCHS), Spanish National Research Council (CSIC), Madrid, Spain
Introduction. Leisure activities, particularly those practiced after retirement, when individuals have more spare time, can be an important source of satisfaction and personal wellbeing.

Aims. To obtain a typology of older adults according to the leisure activities they perform, and to identify the objective factors explaining the use of leisure time in the context of their quality of life.

Data and methods. Data come from a survey carried out in a nationally representative sample of 1,106 adults aged 60 years and over living in community-dwelling in Spain (CadeViMa-Spain, 2008, MICINN SEJ2006-15122-C02-01/02). The 32 leisure activities questioned were grouped into active (physical), passive, cultural and social leisure, and travel and tourism. Cluster Analysis was run on these variables after standardized to obtain a typology of people according to the way they spend their leisure time. Discriminant Analysis was implemented in order to validate the clusters obtained. Multinomial regressions models were applied to identify main characteristics that affect the probability of an individual of belonging to a specific group of leisure activities.

Results. The typology of people obtained was formed by 4 clusters: Inactive (48.32%), Active and Social (23.34%), Passive and Cultural (22.16%), and Very Active and Tourist people (6.18%). The Discriminant Analysis presented an 81.9% of cases assigned correctly to their group. The final multinomial regression model was determined with eleven variables.

Conclusions. The factors that predispose the trend of an individual to be classified in a specific group of leisure activities depend on the type of leisure activities performed.