Latent class-derived subgroups of depressive symptoms in a community sample of older adults: the Cache County Study.


Journal Article

OBJECTIVE: We sought to identify possible subgroups of elders that varied in depressive symptomatology and to examine symptom patterns and health status differences between subgroups. METHODS: The Cache County memory study is a population-based epidemiological study of dementia with 5092 participants. Depressive symptoms were measured with a modified version of the diagnostic interview schedule-depression. There were 400 nondemented participants who endorsed currently (i.e., in the past 2 weeks) experiencing at least one of the three "gateway" depressive symptoms and then completed a full depression interview. Responses to all nine current depressive symptoms were modeled using the latent class analysis. RESULTS: Three depression subgroups were identified: a significantly depressed subgroup (62%), with the remainder split evenly between a subgroup with low probability of all symptoms (21%), and a subgroup with primarily psychomotor changes, sleep symptoms, and fatigue (17%). Latent class analysis derived subgroups of depressive symptoms and Diagnostic and statistical manual of mental disorders, fourth edition depression diagnostic group were nonredundant. Age, gender, education, marital status, early or late onset, number of episodes, current episode duration, and functional status were not significant predictors of depression subgroup. The first subgroup was more likely to be recently bereaved and had less physical health problems, whereas the third subgroup were less likely to be using antidepressants compared with the second subgroup. CONCLUSIONS: There are distinct subgroups of depressed elders, which are not redundant with the Diagnostic and statistical manual of mental disorders, fourth edition classification scheme, offering an alternative diagnostic approach to clinicians and researchers. Future work will examine whether these depressive symptom profiles are predictive of incident dementia and earlier mortality.

Full Text

Duke Authors

Cited Authors

  • Lee, C-T; Leoutsakos, J-M; Lyketsos, CG; Steffens, DC; Breitner, JCS; Norton, MC

Published Date

  • October 2012

Published In

Volume / Issue

  • 27 / 10

Start / End Page

  • 1061 - 1069

PubMed ID

  • 22135008

Pubmed Central ID

  • 22135008

Electronic International Standard Serial Number (EISSN)

  • 1099-1166

Digital Object Identifier (DOI)

  • 10.1002/gps.2824


  • eng

Conference Location

  • England