Loneliness in seniors: social network and the living environment

Social participation and integration of older adults are important aspects of healthy aging, as they are positively associated with better health, well-being and quality of life. However, in general, older adults have smaller social networks due to changes in their life cycle stage such as retirement, or age-related losses such as death of a partner or friends, along with a declining health and increasing mobility limitations. As a consequence, there is an increasing percentage of seniors that experience feelings of loneliness and social isolation.
Previous studies observed factors that explain differences in social participation and loneliness, such as personal characteristics and the social and physical living environment. However, existing knowledge is often based on bivariate relationships between these factors or studies only including a limited number of variables. Therefore, the aim of this study is to bring all these factors together into a more comprehensive framework to explain the (direct and indirect) relationships between socio-demographics, living environmental characteristics, social participation and loneliness.
Data was collected by a survey among 182 adults aged 65 years and over living in the West Brabant region in the Netherlands. Questions were asked about personal- and household characteristics, health status and the respondent’s Activities of Daily Living (ADL) and mobility. Social environmental characteristics were asked with questions about the feeling of safety in the neighborhood, neighborhood attachment, and satisfaction with facilities. Also information about social network size, satisfaction with the network, and feelings of loneliness was collected. Furthermore, the respondents were asked about their social activities. Based on the postal code of the residence the urban density level and distance to facilities were defined.
For the analysis, a Bayesian belief network (BBN) modeling approach was used that derives and represents all direct and indirect relations between the variables. The BBN is estimated from the database by using a network learning algorithm. A major advantage of a BBN is that the network structure takes direct and indirect relationships between the variables into account.
The resulting BBN shows that feelings of loneliness are directly related to satisfaction with one’s social network and neighborhood attachment, and that they are indirectly related to perceived safety of the living environment and satisfaction with local facilities and services. Furthermore, a number of other interesting relationships were found. This knowledge is relevant to urban planners and policy makers who focus on creating livable and healthy social neighborhoods for the aging population.