OBJECTIVES: Longitudinal research on loneliness in old age has rarely considered loneliness separately for men and women, despite gender differences in life experiences. The objective of this study was to examine the extent to which older women and men (70+) report feelings of loneliness with a focus on: (a) changes in reported loneliness as people age, and (b) which factors predict loneliness. METHOD: Data from the 2004 and 2011 waves of SWEOLD, a longitudinal national survey, was used (n = 587). The prediction of loneliness in 2011 by variables measured in 2004 and 2004-2011 variable change scores was examined in three logistic regression models: total sample, women and men. Variables in the models included: gender, age, education, mobility problems, depression, widowhood and social contacts. RESULTS: Older people moved into and out of frequent loneliness over time, although there was a general increase in loneliness with age. Loneliness at baseline, depression increment and recent widowhood were significant predictors of loneliness in all three multivariable models. Widowhood, depression, mobility problems and mobility reduction predicted loneliness uniquely in the model for women; while low level of social contacts and social contact reduction predicted loneliness uniquely in the model for men. CONCLUSION: This study challenges the notion that feelings of loneliness in old age are stable. It also identifies important gender differences in prevalence and predictors of loneliness. Knowledge about such differences is crucial for the development of effective policy and interventions to combat loneliness in later life.
OBJECTIVES: Longitudinal research on loneliness in old age has rarely considered loneliness separately for men and women, despite gender differences in life experiences. The objective of this study was to examine the extent to which older women and men (70+) report feelings of loneliness with a focus on: (a) changes in reported loneliness as people age, and (b) which factors predict loneliness. METHOD: Data from the 2004 and 2011 waves of SWEOLD, a longitudinal national survey, was used (n = 587). The prediction of loneliness in 2011 by variables measured in 2004 and 2004-2011 variable change scores was examined in three logistic regression models: total sample, women and men. Variables in the models included: gender, age, education, mobility problems, depression, widowhood and social contacts. RESULTS: Older people moved into and out of frequent loneliness over time, although there was a general increase in loneliness with age. Loneliness at baseline, depression increment and recent widowhood were significant predictors of loneliness in all three multivariable models. Widowhood, depression, mobility problems and mobility reduction predicted loneliness uniquely in the model for women; while low level of social contacts and social contact reduction predicted loneliness uniquely in the model for men. CONCLUSION: This study challenges the notion that feelings of loneliness in old age are stable. It also identifies important gender differences in prevalence and predictors of loneliness. Knowledge about such differences is crucial for the development of effective policy and interventions to combat loneliness in later life.
Authors: Joan Domènech-Abella; Elvira Lara; Maria Rubio-Valera; Beatriz Olaya; Maria Victoria Moneta; Laura Alejandra Rico-Uribe; Jose Luis Ayuso-Mateos; Jordi Mundó; Josep Maria Haro Journal: Soc Psychiatry Psychiatr Epidemiol Date: 2017-02-02 Impact factor: 4.328
Authors: Ellen E Lee; Colin Depp; Barton W Palmer; Danielle Glorioso; Rebecca Daly; Jinyuan Liu; Xin M Tu; Ho-Cheol Kim; Peri Tarr; Yasunori Yamada; Dilip V Jeste Journal: Int Psychogeriatr Date: 2019-10 Impact factor: 3.878
Authors: Å von Berens; A Koochek; M Nydahl; R A Fielding; T Gustafsson; D R Kirn; T Cederholm; M Södergren Journal: J Nutr Health Aging Date: 2018 Impact factor: 4.075
Authors: Laura Alejandra Rico-Uribe; Francisco Félix Caballero; Natalia Martín-María; María Cabello; José Luis Ayuso-Mateos; Marta Miret Journal: PLoS One Date: 2018-01-04 Impact factor: 3.240