title: Latent class-derived subgroups of depressive symptoms in a community sample of older adults: the Cache County Study.
abstract: 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.
authors.affiliation: Department of Community and Family Medicine, Duke University Medical Center, Durham, NC, USA.
authors.forename: Chien-Ti
authors.initials: CT
authors.lastname: Lee
authors.forename: Jeannie-Marie
authors.initials: JM
authors.lastname: Leoutsakos
authors.forename: Constantine G
authors.initials: CG
authors.lastname: Lyketsos
authors.forename: David C
authors.initials: DC
authors.lastname: Steffens
authors.forename: John C S
authors.initials: JC
authors.lastname: Breitner
authors.forename: Maria C
authors.initials: MC
authors.lastname: Norton
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D003863:Depression / Q000145:classification / Q000175:diagnosis*; D039721:Diagnostic and Statistical Manual of Mental Disorders; D005260:Female; D006304:Health Status; D006801:Humans; D016013:Likelihood Functions; D008297:Male