Correlates of emotional and social loneliness among community dwelling older adults in Rotterdam, the Netherlands.


Journal

Aging & mental health
ISSN: 1364-6915
Titre abrégé: Aging Ment Health
Pays: England
ID NLM: 9705773

Informations de publication

Date de publication:
02 2022
Historique:
pubmed: 28 1 2021
medline: 3 2 2022
entrez: 27 1 2021
Statut: ppublish

Résumé

Loneliness is seen as an important problem, contributing to serious health problems. As a baseline measurement for the evaluation of a community project aimed at reducing loneliness in Rotterdam, loneliness was measured, as well as potential correlates. This article describes models of social and emotional loneliness among older adults. This study was conducted among 3,821 randomly selected community dwelling citizens of 65 years and older. Loneliness was measured by using the Jong-Gierveld loneliness questionnaire/scale. As potential correlates demographic, health and psychological and social variables were included. Data were subjected to multiple hierarchically regression analysis. Emotional loneliness was reported by 60% and social loneliness by 47% of the sample. Women were more emotionally lonely than men , while men reported more social loneliness than women. Emotional social support and quality of life were strongest in predicting emotional loneliness and social capital in the neighbourhood, companionship and instrumental support were strongest predictors for social loneliness. Demographic variables predicted variability in emotional loneliness. The strength of the correlates differed between the two dimensions of loneliness. In the design of interventions to prevent and reduce loneliness among older adults, strategies should be developed aimed at the specific dimensions of loneliness.

Identifiants

pubmed: 33502244
doi: 10.1080/13607863.2021.1875191
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

355-367

Auteurs

Mireille E G Wolfers (MEG)

Department Research and Business Intelligence, Municipality of Rotterdam, Rotterdam, the Netherlands.

Bianca E Stam (BE)

Department Research and Business Intelligence, Municipality of Rotterdam, Rotterdam, the Netherlands.

Anja Machielse (A)

University for Humanistic Studies, Utrecht, the Netherlands.

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Classifications MeSH