|
Activity Number:
|
97
- Mediation in the Presence of Post-Treatment Common Causes of the Mediator and the Outcome
|
|
Type:
|
Invited
|
|
Date/Time:
|
Monday, July 31, 2017 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
ENAR
|
|
Abstract #322255
|
View Presentation
|
|
Title:
|
Parametric Mediational G-Formula Approach to Mediation Analysis with Time-Varying Exposures, Mediators, and Confounders: An Application for Smoking, Weight, and Blood Pressure
|
|
Author(s):
|
Sheng-Hsuan Lin*
|
|
Companies:
|
Columbia Mailman School of Public Health
|
|
Keywords:
|
mediation analysis ;
causal inference ;
time-varying ;
g-formula ;
parametrically
|
|
Abstract:
|
The assessment of direct and indirect effects with time-varying mediators and confounders is a common but challenging problem, and standard mediation analysis approaches are generally not applicable in this context. The mediational g-formula (mgf) was recently proposed to address this problem, paired with a semi-parametric estimation approach. In this paper, we develop a parametric estimation approach to the mgf, including a feasible algorithm implemented in a freely available SAS macro. In the Framingham Heart Study data, we apply this method to estimate the interventional analogues of natural direct and indirect effects of smoking behaviors sustained over a 10-year period on blood pressure when considering weight change as a time-varying mediator. Compared with non-smoking, smoking 20 cigarettes per day for 10 years was estimated to increase blood pressure by 1.18 mm-Hg. The direct and indirect effects was 1.52 mm-Hg and -0.34 mm-Hg, respectively. These results show that weight change partially conceals the detrimental effects of cigarette smoking on blood pressure. Our work represents the first application of the parametric mgf in an epidemiologic cohort study.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2017 program
|
