What Changes First? Mapping the Temporal Ordering of Age-Related Functional Decline across Domains Using 30-Year
Gabriela Lunansky1,2, Marjolein Visser3,2, Martijn Huisman1,2,4
1Department of Epidemiology and Data Science, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
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Introduction: Age-related functional decline is assumed to be a complex process in which declines in one domain may trigger decline in others. Yet research empirically identifying the temporal ordering of age-related decline across emotional, cognitive, physical, and social functioning as well as health-behavioral factors is still scarce.
Methods:
We analyzed up to 10 waves of the Longitudinal Aging Study Amsterdam (LASA) cohort over 30 years (n = 1,560), covering fifteen indicators of physical, cognitive, emotional and social functioning, and health-behavioral factors. We used directed dynamic time warping to quantify the temporal ordering of within-person changes in these indicators. Average temporal relationships were visualized as a network graph and by rank-ordering indicators according to their tendency to precede (high out-strength) or follow (high in-strength) changes in other indicators.
Results:
Participants were on average 62.3 ± 5.50 years old at baseline, 53.8% female, with 14.8 ± 4.74 years of follow-up. Physical and cognitive declines (e.g., physical performance and episodic memory) tended to precede decline in other domains, while changes in social functioning (e.g., social participation) tended to follow. No clear temporal ordering was found between emotional functioning (e.g., depression and anxiety) and other domains.
Conclusion:
The study offers insights into early detection and prevention strategies for healthy aging. Assuming that physical and cognitive domains are primarily driven by age-related biological changes, our findings support theories proposing that biological changes precede functional decline and theories emphasizing the importance of psychosocial resilience. Moreover, this study highlights the potential of adopting a complex systems approach and innovative within-person analytical methods in gerontology.
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