Back to Annual Meeting Page		American Public Health Association 133rd Annual Meeting & Exposition December 10-14, 2005 Philadelphia, PA

Abstract #109223

Eva Blozik, MD¹, James E. Lubben, DSW, MPH², Gerhard Gillmann, MSc³, Jan T. Wagner, MD¹, John C. Beck, MD⁴, and Andreas E. Stuck, MD¹. (1) Department of Geriatrics and Rehabilitation, University of Bern, Morillonstr. 75-91, Bern, 3007, Switzerland, 0041-31-631-3528, eva.blozik@spitalbern.ch, (2) Louise McMahon Ahearn University Chair, Boston College School of Social Work, McGuinn Hall 315, 140 Commonwealth Avenue, Chestnut Hill, MA 02467, (3) Institute of Social and Preventive Medicine, University of Bern, Finkenhubelweg 11, Bern, 3012, Switzerland, (4) School of Medicine, UCLA, BOX 951687, 2339 PVUB, Los Angeles, CA 90095-1687

Introduction: Social support networks are highly correlated with mortality rates and health status in older persons. Information on modifiable factors that enhance or weaken social support networks in older people might be useful for developing health promotion interventions. Methods: Cross-sectional survey of 2842 community-dwelling persons aged 65 or older from a mixed rural and urban setting in Switzerland. All persons a self-administered multidimensional questionnaire (Health Risk Appraisal for Older People), including a short instrument to assess social support networks (6-item version of the Lubben Social Network Scale (LSNS-6)). Bivariate and multivariate linear and logistic regression models were calculated. Results: Gender and co-morbidity were significant (p<0.05) correlates in bivariate associations, but these factors were statistically insignificant in multivariate models. In multivariate models, depressive mood, living in urban area and poor self-perceived health status were the most important factors correlated with low levels of social support. Factors correlated with family network (p<0.05 for living area, living with partner, self-rated health status) differed from factors correlated with friendship and neighbourhood network (p<0.05 for age, educational level, functional health). The adjusted odds for being isolated was 2.0 (95%CI [1.4, 2.7], p<0.001) in the presence of depressive mood. Conclusion: Factors contributing to low levels of family network differ in part from those contributing to low levels of friendship network. The presence of depressive mood is related with all aspects of social network. These data may help to better understand the origin of social isolation, and to reduce the prevalence of social isolation among older people.

Learning Objectives: At the end of the session, the participant in this session will be able to

• describe a short screening tool for social isolation in older people.
• list three modifiable factors associated with social isolation.
• discuss the impact of gender and age on social isolation.

Presenting author's disclosure statement:

I wish to disclose that I have NO financial interests or other relationship with the manufactures of commercial products, suppliers of commercial services or commercial supporters.