Volume 38 - Article 10 | Pages 233–246
Interdisciplinary Research on Healthy Aging: Introduction
|Date received:||10 May 2017|
|Date published:||17 Jan 2018|
|Keywords:||causal analysis, demography, healthy aging, multistate models|
|Weblink:||You will find all publications in this Special Collection on “Interdisciplinary Research on Healthy Aging” here.|
Background: This is an introduction to a Special Collection of Demographic Research on Interdisciplinary Research on Healthy Aging. The collection is an outcome of an international conference in China on biodemography and multistate modeling in healthy aging research. Causal analysis is the common theme of the papers. Healthy aging is an outcome of pathways of causally related distant and proximate determinants and intervening factors that mediate the effects of the determinants.
Objective: The objective is to introduce the papers in this SC and to highlight the place of multistate modeling in causal analysis.
Methods: We adopt the common distinction between structural causal modeling and dynamic causal modeling. The papers in the SC concentrate on structural causal modeling. Multistate models (and, more particularly, the continuous-time Markov process model) are oriented more toward dynamic causal modeling. In dynamic causal modeling the causal dependencies are defined in terms of events (outcomes), exposure time, and transition rates that relate exposures to events.
Results: The contributions to the SC illustrate the progress made in structural causal modeling in the study of healthy aging. Dynamic causal analysis, however, has progressed comparatively slowly.
Contribution: The papers in the SC and the brief introduction to multistate modeling in causal analysis pave the way to enhanced causal analysis in the study of healthy aging and in demography.
Frans Willekens - Nederlands Interdisciplinair Demografisch Instituut (NIDI), Netherlands
James R. Carey - University of California, Davis, United States of America
Qiang Li - East China Normal University, China
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