Literature DB >> 22135008

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

Chien-Ti Lee1, Jeannie-Marie Leoutsakos, Constantine G Lyketsos, David C Steffens, John C S Breitner, Maria C Norton.   

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.
Copyright © 2011 John Wiley & Sons, Ltd.

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Year:  2011        PMID: 22135008      PMCID: PMC3419796          DOI: 10.1002/gps.2824

Source DB:  PubMed          Journal:  Int J Geriatr Psychiatry        ISSN: 0885-6230            Impact factor:   3.485


  24 in total

1.  Prevalence of depression and its treatment in an elderly population: the Cache County study.

Authors:  D C Steffens; I Skoog; M C Norton; A D Hart; J T Tschanz; B L Plassman; B W Wyse; K A Welsh-Bohmer; J C Breitner
Journal:  Arch Gen Psychiatry       Date:  2000-06

2.  Multiplex PCR amplification from the CFTR gene using DNA prepared from buccal brushes/swabs.

Authors:  B Richards; J Skoletsky; A P Shuber; R Balfour; R C Stern; H L Dorkin; R B Parad; D Witt; K W Klinger
Journal:  Hum Mol Genet       Date:  1993-02       Impact factor: 6.150

3.  National Institute of Mental Health Diagnostic Interview Schedule. Its history, characteristics, and validity.

Authors:  L N Robins; J E Helzer; J Croughan; K S Ratcliff
Journal:  Arch Gen Psychiatry       Date:  1981-04

4.  Stroke, vascular risk factors and depression: Cross-sectional study in a UK Caribbean-born population.

Authors:  R Stewart; M Prince; A Mann; M Richards; C Brayne
Journal:  Br J Psychiatry       Date:  2001-01       Impact factor: 9.319

5.  Understanding the heterogeneity of depression through the triad of symptoms, course and risk factors: a longitudinal, population-based study.

Authors:  L Chen; W W Eaton; J J Gallo; G Nestadt
Journal:  J Affect Disord       Date:  2000-07       Impact factor: 4.839

6.  DSM-III major depressive disorder in the community. A latent class analysis of data from the NIMH epidemiologic catchment area programme.

Authors:  W W Eaton; A Dryman; A Sorenson; A McCutcheon
Journal:  Br J Psychiatry       Date:  1989-07       Impact factor: 9.319

7.  Prevalence of depression and its correlates in older adults.

Authors:  S A Murrell; S Himmelfarb; K Wright
Journal:  Am J Epidemiol       Date:  1983-02       Impact factor: 4.897

8.  Association of apolipoprotein E allele epsilon 4 with late-onset familial and sporadic Alzheimer's disease.

Authors:  A M Saunders; W J Strittmatter; D Schmechel; P H George-Hyslop; M A Pericak-Vance; S H Joo; B L Rosi; J F Gusella; D R Crapper-MacLachlan; M J Alberts
Journal:  Neurology       Date:  1993-08       Impact factor: 9.910

Review 9.  Depression in late life: review and commentary.

Authors:  Dan G Blazer
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2003-03       Impact factor: 6.053

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  5 in total

Review 1.  Towards a new conceptualization of depression in older adult cancer patients: a review of the literature.

Authors:  Rebecca M Saracino; Barry Rosenfeld; Christian J Nelson
Journal:  Aging Ment Health       Date:  2015-08-27       Impact factor: 3.658

2.  Latent Profile Analyses of Depressive Symptoms in Younger and Older Oncology Patients.

Authors:  Rebecca M Saracino; Heining Cham; Barry Rosenfeld; Christian J Nelson
Journal:  Assessment       Date:  2018-06-27

3.  Network structure of time-varying depressive symptoms through dynamic time warp analysis in late-life depression.

Authors:  Denise C R van Zelst; Eveline M Veltman; Didi Rhebergen; Paul Naarding; Almar A L Kok; Nathaly Rius Ottenheim; Erik J Giltay
Journal:  Int J Geriatr Psychiatry       Date:  2022-09       Impact factor: 3.850

4.  Subtypes of depression in cancer patients: an empirically driven approach.

Authors:  Lei Zhu; Adelita V Ranchor; Marije van der Lee; Bert Garssen; Robbert Sanderman; Maya J Schroevers
Journal:  Support Care Cancer       Date:  2015-09-05       Impact factor: 3.603

5.  Refining our understanding of depressive states and state transitions in response to cognitive behavioural therapy using latent Markov modelling.

Authors:  Ana Catarino; Jonathan M Fawcett; Michael P Ewbank; Sarah Bateup; Ronan Cummins; Valentin Tablan; Andrew D Blackwell
Journal:  Psychol Med       Date:  2020-06-29       Impact factor: 7.723

  5 in total

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