Capturing the Diversity of Successful Aging: An Operational Definition Based on 16-Year Trajectories of Functioning

Research output: Contribution to journalArticleAcademicpeer-review

62 Citations (Scopus)


Purpose of the Study : To determine the prevalence and extent of successful aging (SA) when various suggestions proposed in the previous literature for improving models of SA are incorporated into one holistic operational definition. These suggestions include defining and measuring SA as a developmental process, including subjective indicators alongside more objective ones, and expressing SA on a continuum.

Design and Methods : Data were used from 2,241 respondents in the Longitudinal Aging Study Amsterdam, a multidisciplinary study in a nationally representative sample of older adults in the Netherlands. Latent class growth analysis was used to identify successful 16-year trajectories within nine indicators of physical, cognitive, emotional, and social functioning. SA was quantified as the number of indicators in which individual respondents showed successful trajectories (range 0-9).

Results : Successful trajectories were characterized by stability, limited decline, or even improvement of functioning over time. Of the respondents, 39.6% of men and 29.3% of women were successful in at least seven indicators; 7% of men and 11% of women were successful in less than three indicators. Proportions of successful respondents were largest in life satisfaction (>85%) and smallest in social activity (<25%). Correlations of success between separate indicators were low to moderate (range r = .02-.37).

Implications : Many older adults age relatively successfully, but the character of successful functioning over time varies between indicators, and the combinations of successful indicators vary between individuals.

Original languageEnglish
Pages (from-to)240-251
Number of pages12
JournalThe Gerontologist
Issue number2
Early online date1 Sept 2015
Publication statusPublished - 1 Apr 2017


  • Heterogeneity in aging
  • Latent class growth analysis
  • Longitudinal methods

Cite this