Trajectories of depression symptoms in Chinese elderly during widowhood: a secondary analysis.

Abstract:

:Objectives: This study aims to identify heterogeneous depressive symptom trajectories among the widowed elderly in China, to explore predictive variables of latent class membership, and to detect between-classes differences in life satisfaction across time.Method: Data of 198 individuals widowed between 2011 and 2013 were drawn from The China Health and Retirement Longitudinal Study (CHARLS), a nationally representative survey. Latent class growth analysis was employed to identify depressive symptom trajectories across 2011, 2013, and 2015, and a three-step auxiliary approach was applied to detect predictive variables of latent class membership. Mixed Analysis of Variances was followed to make between-class comparisons on life satisfaction across time.Results: Four grieving trajectories were identified: resilient (54.6%), chronic grief (23.7%), depressed-improved (11.6%), and chronic depression (10.1%). Older age, living exclusively with spouse before widowhood, and agricultural Hukou were significant predictors of depressed-improved, chronic grief, and chronic depression patterns, respectively. Life satisfaction in all groups except for the resilient one remained stable across time, and that of the chronic depression group was significantly lower than those of all the remaining groups.Conclusion: Consistent depressive symptom trajectories during late-life widowhood exist across nations while the specific culture, values, and resources in the Chinese context may have contributed to a particularly high proportion of the chronic grief trajectory. More efforts should be made to identify patterns with predictors before support are provided, and interventions need to be tailored to target specific needs in each subgroup of the elderly during their transitions to widowhood.

journal_name

Aging Ment Health

journal_title

Aging & mental health

authors

Chen C,Chow AYM,Tang S

doi

10.1080/13607863.2019.1603285

subject

Has Abstract

pub_date

2020-08-01 00:00:00

pages

1254-1262

issue

8

eissn

1360-7863

issn

1364-6915

journal_volume

24

pub_type

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