131.7
Determinants of Social Activities Among Older People in China: An Analysis of Family Factors and Community Factors

Saturday, July 19, 2014: 4:00 PM
Room: 413
Distributed Paper
Pei-Chun KO , SOCLIFE PhD training group, University of Cologne, Cologne, Germany
Objectives: The study investigates the extent of family factors and community factors affecting engagement in social activities (non-market productive activities and leisure activities) by older people in China.

Conceptual framework: Given filial piety and Chinese “quanxi” value the importance of family in Chinese culture, family factors, including older people’s household size, composition and number of financial supporters are tested. In line with opportunity structure arguments, the impacts of community factors (public facilities, community offices and urban/rural communities) on the likelihood of social activities are examined. Research hypotheses are summarized here:

H1: Older people living with more family members are less likely to engage in social activities than are older people living with few or no family members.

H2: Older people living alone are less likely to engage in social activities than are older people living with partners.

H3: Older people with more financial supporters from within their family are less likely to engage in social activities than are older people with few or no financial supporters from within their family.

H4: A community with more public facilities increases individuals’ propensity to participate social activities.

H5: A community with a longer office increases individuals’ propensity to participate social activities.

H6: Individuals living in an urban community have a higher propensity to participate in social activities than do individuals living in a rural community.

H6: Individuals living in an urban community have a higher propensity to participate in social activities than do individuals living in a rural community.

Methods and data: The first wave of the China Health and Retirement Longitudinal Study (CHARLS) is used. The analytic sample is composed of respondents above 50 years old (n= 7,813). Multilevel models for dichotomous data are employed (first level: individual characteristics and family factors; second level: community factors).