Literature DB >> 30345800

Depressive symptoms predict increased social and emotional loneliness in older adults.

Joanna McHugh Power1,2,3, Caoimhe Hannigan2, Philip Hyland1, Sabina Brennan2, Frank Kee3, Brian A Lawlor2.   

Abstract

Objectives: Explorations of relationships between loneliness and depression have focused on loneliness as a uni-dimensional construct. We hypothesised that reciprocal relationships may exist between depressive symptomatology and social and emotional subtypes of loneliness.
Methods: Using data from 373 adults aged over 50, who participated in an observational cohort study, we employed a cross-lagged approach within a Structural Equation Modelling framework, to investigate reciprocal links between depressive symptomatology, and social and emotional loneliness, across two waves of data collection, two years apart (controlling for age, sex, education, comorbidities, social network index, and perceived stress).
Results: Both depressive symptomatology and loneliness decreased slightly between waves. Auto-regressive effects were strong for all three variables of interest. Cross-lagged pathways were evident, such that depressive symptomatology at baseline predicted both emotional (β = 0.26, p < 0.05) and social (β = 0.17, p < 0.05) loneliness at follow-up. Neither emotional (β = 0.07, p > 0.05) nor social (β = 0.05, p > 0.05) loneliness at baseline predicted depressive symptomatology at follow-up.Conclusions: Results challenge existing understanding of the associations between loneliness and depression. Further investigation of emotional and social loneliness in individuals with depressive disorders is warranted. Findings are discussed in relation to mechanisms that may explain the relationships observed, and possible implications.

Entities:  

Keywords:  Emotional loneliness; ageing; cross-lagged path modelling; depressive symptomatology; social loneliness; structural equation modelling

Year:  2018        PMID: 30345800     DOI: 10.1080/13607863.2018.1517728

Source DB:  PubMed          Journal:  Aging Ment Health        ISSN: 1360-7863            Impact factor:   3.658


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