Cited by 147Aging and Gerontology ResearchAging, Health, and DisabilityHealth disparities and outcomes

Longitudinal Selectivity in Aging Populations: Separating Mortality-Associated Versus Experimental Components in the Berlin Aging Study (BASE)

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Lindenberger, U., Singer, T., Baltes, P. B.·2002·The Journals of Gerontology Series B: Psychological Sciences and Social Sciences

Abstract

The authors examined 3.7-year selectivity in the Berlin Aging Study by comparing the T1 parent sample (N = 516) with the T3 sample (N = 206). Selectivity was partitioned into a mortality-associated component, reflecting the degree to which individuals still alive at T3 (T3 survivors, N = 313) differ from the T1 parent sample (N = 516) from which they originated, and an experimental component, reflecting the degree to which the T3 sample (N = 206) differed from T3 survivors (N = 313). Across 48 variables representing medical, sensorimotor, cognitive, personality-related, and socioeconomic domains, the mortality-associated component accounted for 64% of total selectivity, and the experimental component for 36% (0.18 vs 0.10 SD units; t = 7.20, p <.01). Except for age and intelligence, experimental selectivity effects regarding means and prevalence rates were generally small. Partitioning selectivity into mortality-associated and experimental components is a useful tool in the longitudinal study of aging populations.

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  • Individuals who drop out from a longitudinal study often differ from those who stay-they tend to be less healthy, less cognitively fit, and less engaged in stimulating activities-restricting observable variation and potentially biasing estimates of enrichment-cognition relations.

    “Individuals who drop out from a longitudinal study often differ from those who stay on dimensions of interest-they tend to be less healthy, less cognitively fit, and less engaged in stimulating activities, thereby restricting the observable range of variation (e.g., Ghisletta, McArdle, &amp; Lindenberger, 2006; Lindenberger, Singer, &amp; Baltes, 2002) and potentially biasing estimates of the rel”

    From Enrichment Effects on Adult Cognitive Development: Can the Functional Capacity of Older Adults Be Preserved and Enhanced? (2008) · cites this paper as Lindenberger, Singer, & Baltes, 2002

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  1. Hedges, L. V., & Olkin, I. (1985). Statistical methods for meta-analysis. Orlando, FL: Academic Press.
  2. Lindenberger, U., & Ghisletta, P. (in press). Modeling longitudinal changes in old age: From covariance structures to dynamic systems. In R. A. Dixon, L. Bäckman, & L.-G. Nilsson (Eds.), New frontiers in cognitive aging. Oxford, England: Oxford University Press.

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Authors
Lindenberger, U., Singer, T., & Baltes, P. B.
Affiliations
  • Max Planck Institute for Human Development (DE)
  • Max Planck Society (DE)
Corresponding author
Lindenberger, U.
Venue
The Journals of Gerontology Series B: Psychological Sciences and Social Sciences
Published
2002-11-01
Volume
57
Issue
6
Pages
P474-P482
ISSN
  • 1079-5014 (ISSN-L)
  • 1758-5368
OpenAlex
W2140385093
Cited by
147
References
24
Citations by year
2026: 6 · 2025: 8 · 2024: 1 · 2023: 1 · 2022: 5 · 2021: 6 · 2020: 3 · 2019: 6 · 2018: 8 · 2017: 2 · 2016: 6 · 2015: 13 · 2014: 7 · 2013: 7 · 2012: 6
FWCI
10.14
Type
journal article
Language
en
Open access
Locations
  • The Journals of Gerontology Series B (publishedVersion)
  • PubMed (publishedVersion)
  • Max Planck Institute for Plasma Physics (submittedVersion)
  • Max Planck Digital Library (submittedVersion, other-oa)
  • Max Planck Digital Library (submittedVersion)
  • MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
  • MPG.PuRe (Max Planck Society) (submittedVersion)
Funders
  • Universität des Saarlandes
  • Max-Planck-Institut für Bildungsforschung
Topics
  • Social Sciences › Psychology › Neuropsychology and Physiological Psychology › Aging and Gerontology Research
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Aging, Health, and Disability
  • Social Sciences › Health › Health disparities and outcomes
Keywords
population aging, Berlin Aging Study, older adults, cognitive aging, personality, socioeconomic status, intelligence, prevalence rates, sample attrition
MeSH terms
Aged, Aged, 80 and over, Aging, Attitude, Female, Geriatrics, Health Status, Humans, Longitudinal Studies, Male, Mortality, Personal Satisfaction, Personality, Population Surveillance, Social Support, Socioeconomic Factors, Geriatric Assessment, Consensus

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