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Measuring Active and Healthy Ageing: Applying a GENERIC Interdisciplinary Assessment Model Incorporating ICF.

P Stute1, N Bitterlich, J Bousquet

  • 1Professor Dr. med. Petra Stute, M.D. Department of Gynecologic Endocrinology and Reproductive Medicine, University Clinic of Obstetrics and Gynecology, Inselspital Bern, Effingerstrasse 102, 3010 Bern, Switzerland, Telephone: (0)31-632-1303, Fax: (0)31-632-1332,

The Journal of Nutrition, Health & Aging
|October 31, 2017
PubMed
Summary
This summary is machine-generated.

This study compared bio-functional age (BFA) in two German cohorts 30 years apart, finding an accelerated aging process in the older cohort between ages 45-54. The developed BFA assessment tool is valuable for individual and population-level active and healthy aging strategies.

Keywords:
Bern Cohort Study 2014Disability and Health (ICF)European Innovation Partnership on Active and Healthy Ageing EIP-AHAInternational Classification of Functioningbio-functional agebio-functional statushealth resources

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Area of Science:

  • Gerontology and Aging Research
  • Biopsychosocial Health Assessment
  • Public Health and Epidemiology

Background:

  • Chronological age does not always reflect an individual's true aging process.
  • Bio-functional age (BFA) offers a more comprehensive measure of aging by integrating biopsychosocial factors.
  • Comparing aging trajectories across different cohorts can reveal societal and healthcare influences.

Purpose of the Study:

  • To compare chronological and bio-functional age between two German-speaking cohorts separated by 30 years.
  • To evaluate the utility of a comprehensive Active and Healthy Aging (AHA) assessment model incorporating the International Classification of Functioning, Disability and Health (ICF).
  • To analyze aging rates and identify factors influencing them across different adult life stages.

Main Methods:

  • A cross-sectional, observational study was conducted at a university women's hospital.
  • Participants underwent a standardized battery of biopsychosocial assessments, including bio-functional status (BFS) and bio-functional age (BFA) measures.
  • Validated psychometric questionnaires were used to supplement the assessments.

Main Results:

  • The BeCS-14 cohort showed a mean BFA lower than chronological age (regression coefficient 0.58).
  • The aging rate (BFA increase per year) was similar between cohorts in the 35-45 and 55-65 age groups.
  • A significantly accelerated aging rate was observed in the LeCS-84 cohort between ages 45-54 (13.02 year equivalents) compared to the BeCS-14 cohort (4.83 year equivalents).
  • In BeCS-14, younger age correlated with better cardiovascular performance, and social stress decreased with age.

Conclusions:

  • The aging process appeared accelerated in the older LeCS-84 cohort between ages 45-54, potentially due to differences in healthcare, political, or social systems.
  • The developed BFS/BFA assessment tool is suitable for both individual and population-level analysis of active and healthy aging (AHA).
  • Further development is needed to integrate the assessed health strengths and resources profile into AHA management strategies.