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Semiparametric adjusted exposure-response curves.
Ashley I Naimi1, Erica E M Moodie, Nathalie Auger
1From the aDepartment of Obstetrics and Gynecology, McGill University, Montreal, Quebec, Canada; bDepartment of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada; and cInstitut national de santé publique du Québec, Montreal, Quebec, Canada.
This study introduces a novel method for plotting exposure-response curves using inverse probability weighting. This approach reveals the relationship between interpregnancy interval and preterm birth risk in a large cohort.
Area of Science:
- Epidemiology
- Biostatistics
Background:
- Exposure-response curves are crucial for understanding health outcomes related to continuous exposures.
- Traditional regression methods like fractional polynomials and regression splines have limitations.
Purpose of the Study:
- To illustrate semiparametric marginally adjusted exposure-response curves using inverse probability weighting (IPW).
- To examine the association between interpregnancy interval and preterm birth.
Main Methods:
- Utilized inverse probability weighting (IPW) for semiparametric marginal adjustment of exposure-response curves.
- Analyzed a large cohort of over 720,000 live births in Quebec (1989-2008).
- Provided supplementary material on mixed modeling and bootstrap confidence intervals.
Main Results:
- Demonstrated the application of IPW for robust exposure-response curve estimation.
- Quantified the relationship between interpregnancy interval and preterm birth risk.
Conclusions:
- Semiparametric IPW offers an advantageous alternative to traditional methods for exposure-response analysis.
- The findings contribute to understanding interpregnancy interval's impact on preterm birth.
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