Literature DB >> 24491214

Comparing changes in late-life depressive symptoms across aging, disablement, and mortality processes.

Elizabeth B Fauth1, Denis Gerstorf2, Nilam Ram3, Bo Malmberg4.   

Abstract

Developmental processes are inherently time-related, with various time metrics and transition points being used to proxy how change is organized with respect to the theoretically underlying mechanisms. Using data from 4 Swedish studies of individuals aged 70-100+ (N = 453) who were measured every 2 years for up to 5 waves, we tested whether depressive symptoms (according to the Center for Epidemiologic Studies Depression Scale; Radloff, 1977) are primarily driven by aging-, disablement-, or mortality-related processes, as operationally defined by time-from-birth, time-to/from-disability-onset (1st reported impairment in Personal Activities of Daily Living; Katz, Ford, Moskowitz, Jackson, & Jaffe, 1963), and time-to-death metrics. Using an approach based on Akaike weights, we tested whether developmental trajectories (for each time metric) of depressive symptoms in late life are more efficiently described as a single continuous process or as a 2-phase process. Comparing fits of linear and multiphase growth models, we found that 2-phase models demonstrated better fit than did single-phase models across all time metrics. Time-to-death and time-to/from-disability-onset models provided more efficient descriptions of changes in depressive symptoms than did time-from-birth models, with time-to-death models representing the best overall fit. Our findings support prior research that late-life changes in depressive symptoms are driven by disablement and, particularly, mortality processes, rather than advancing chronological age. From a practical standpoint, time-to/from-disability-onset and, particularly, time-to-death metrics may provide better "base" models from which to examine changes in late-life depressive symptoms and determine modifiable risk and protective factors. Developmental researchers across content areas can compare age with other relevant time metrics to determine if chronological age or other processes drive the underlying developmental change in their construct of interest. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

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Year:  2014        PMID: 24491214      PMCID: PMC4401032          DOI: 10.1037/a0035475

Source DB:  PubMed          Journal:  Dev Psychol        ISSN: 0012-1649


  40 in total

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Review 5.  Subsyndromal depression in the elderly: underdiagnosed and undertreated.

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Journal:  Metabolism       Date:  2005-05       Impact factor: 8.694

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7.  Late-life decline in well-being across adulthood in Germany, the United Kingdom, and the United States: Something is seriously wrong at the end of life.

Authors:  Denis Gerstorf; Nilam Ram; Guy Mayraz; Mira Hidajat; Ulman Lindenberger; Gert G Wagner; Jürgen Schupp
Journal:  Psychol Aging       Date:  2010-06

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Authors:  Denis Gerstorf; Nilam Ram; Ryne Estabrook; Jürgen Schupp; Gert G Wagner; Ulman Lindenberger
Journal:  Dev Psychol       Date:  2008-07
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  4 in total

1.  Historical improvements in well-being do not hold in late life: Birth- and death-year cohorts in the United States and Germany.

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Journal:  Dev Psychol       Date:  2015-07

2.  Self-esteem is relatively stable late in life: the role of resources in the health, self-regulation, and social domains.

Authors:  Jenny Wagner; Christiane Hoppmann; Nilam Ram; Denis Gerstorf
Journal:  Dev Psychol       Date:  2015-01

3.  Levels of and changes in life satisfaction predict mortality hazards: Disentangling the role of physical health, perceived control, and social orientation.

Authors:  Gizem Hülür; Jutta Heckhausen; Christiane A Hoppmann; Frank J Infurna; Gert G Wagner; Nilam Ram; Denis Gerstorf
Journal:  Psychol Aging       Date:  2017-09

4.  The association between nutritional status and functional limitations among centenarians: a cross-sectional study.

Authors:  Yang Song; Miao Liu; Wang-Ping Jia; Ke Han; Sheng-Shu Wang; Yao He
Journal:  BMC Geriatr       Date:  2021-06-21       Impact factor: 3.921

  4 in total

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