Causal mediation analysis between resistance exercise and reduced risk of cardiovascular disease based on the Aerobics Center Longitudinal Study
Jiasheng Huang,
Yehua Li,
Angelique G. Brellenthin,
Duck-chul Lee,
Xuemei Sui and
Steven N. Blair
Journal of Applied Statistics, 2022, vol. 49, issue 14, 3750-3767
Abstract:
Health benefits of resistance exercise (RE), particularly in lowering cardiovascular disease (CVD) risks, are less understood in comparison to aerobic exercise (AE). Motivated by big data from the Aerobics Center Longitudinal Study (ACLS), we study the direct and indirect effects of RE on CVD risks. The primary outcome in our study, total CVD events (CVD morbidity and mortality combined), is modeled as a survival outcome. To investigate the pathway from RE to CVD outcome through potential mediators, we first conduct causal mediation analysis based on marginal structural models (MSMs). To fully account the information from repeated measurements of the mediators, we also adopt a joint model of the CVD survival outcome and multiple longitudinal trajectories of the mediators. Results show statistically significant direct effects of RE and AE on lowering the risk of total CVD events under each pathway. The causal effect of RE and AE on CVD risk is also studied across different age and gender groups. Furthermore, we produce a ranking for the relative importance of the potential risk factors for CVD, with total cholesterol ranking the highest.
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/02664763.2021.1962260 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:49:y:2022:i:14:p:3750-3767
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20
DOI: 10.1080/02664763.2021.1962260
Access Statistics for this article
Journal of Applied Statistics is currently edited by Robert Aykroyd
More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().