Research Article: Examining individual and geographic factors associated with social isolation and loneliness using Canadian Longitudinal Study on Aging (CLSA) data

Date Published: February 1, 2019

Publisher: Public Library of Science

Author(s): Verena H. Menec, Nancy E. Newall, Corey S. Mackenzie, Shahin Shooshtari, Scott Nowicki, Kenzie Latham-Mintus.

http://doi.org/10.1371/journal.pone.0211143

Abstract

A large body of research shows that social isolation and loneliness have detrimental health consequences. Identifying individuals at risk of social isolation or loneliness is, therefore, important. The objective of this study was to examine personal (e.g., sex, income) and geographic (rural/urban and sociodemographic) factors and their association with social isolation and loneliness in a national sample of Canadians aged 45 to 85 years.

The study involved cross-sectional analyses of baseline data from the Canadian Longitudinal Study on Aging that were linked to 2016 census data at the Forward Sortation Area (FSA) level. Multilevel logistic regression analyses were conducted to examine the association between personal factors and geographic factors and social isolation and loneliness for the total sample, and women and men, respectively.

The prevalence of social isolation and loneliness was 5.1% and 10.2%, respectively, but varied substantially across personal characteristics. Personal characteristics (age, sex, education, income, functional impairment, chronic diseases) were significantly related to both social isolation and loneliness, although some differences emerged in the direction of the relationships for the two measures. Associations also differed somewhat for women versus men. Associations between some geographic factors emerged for social isolation, but not loneliness. Living in an urban core was related to increased odds of social isolation, an effect that was no longer significant when FSA-level factors were controlled for. FSAs with a higher percentage of 65+ year old residents with low income were consistently associated with higher odds of social isolation.

The findings indicate that socially isolated individuals are, to some extent, clustered into areas with a high proportion of low-income older adults, suggesting that support and resources could be targeted at these areas. For loneliness, the focus may be less on where people live, but rather on personal characteristics that place individuals at risk.

Partial Text

A large body of research shows that social isolation and loneliness have detrimental health consequences [1–4]. For example, social isolation has been shown to be associated with an increased risk of coronary heart disease and stroke [5], dementia [6], and mortality [2]. Similarly, loneliness is associated with a wide range of physical and mental health outcomes, such as physiological measures like increased blood pressure and depressed immune system [7,8], reduced cognitive function [9] and mortality [3]. Both social isolation and loneliness are related to increased health care use [10–13]. That social isolation and loneliness are serious concerns is increasingly being recognized by policy makers. For example, in the United Kingdom, the “Campaign to End Loneliness” is tackling loneliness by providing service organizations with information on how to approach the issue [14].

Sample characteristics are displayed in Table 1.

Several key findings emerged in the present study. Overall, using our definitions, the prevalence of social isolation and loneliness was 5.1% and 10.2%, respectively, but there was substantial variation across personal characteristics in prevalence rates. Being older, male, having a low income, functional impairment and more chronic conditions were all associated with increased odds of being socially isolated, as was, somewhat counter-intuitively, a higher education level. The finding for education is consistent with a Swedish study that showed that individuals with higher education, compared to those with less education had less dense local family networks, which may be due to migration patterns [47]. A similar issue may be at play in the present study in that more highly educated younger individuals, as compared to those with less education, may be more likely to move for job opportunities or, conversely, more highly educated older individuals may be more likely to move to retirement communities. Both scenarios would result in individuals having less direct contact with family members.

 

Source:

http://doi.org/10.1371/journal.pone.0211143

 

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