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Conditioning on intermediates in perinatal epidemiology
Tyler J VanderWeele1, Sunni L Mumford, Enrique F Schisterman
1Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. tvanderw@hsph.harvard.edu
Epidemiology (Cambridge, Mass.)
|December 14, 2011
Summary
Researchers propose three methods to avoid bias when analyzing exposure effects on perinatal outcomes, especially when birth weight or gestational age is an intermediate factor. These approaches address issues like the birth-weight paradox.
Area of Science:
- Perinatal Epidemiology
- Biostatistics
- Causal Inference
Background:
- Common practice in perinatal epidemiology involves analyzing exposure-outcome associations conditional on intermediates like gestational age or birth weight.
- Conditioning on intermediates can lead to bias and paradoxical results, particularly when unmeasured common causes exist.
- The 'birth-weight paradox,' where certain exposures appear protective in low-birth-weight infants, highlights issues with standard methods.
Purpose of the Study:
- To propose and evaluate three novel approaches for valid causal inference when conditioning on a potential intermediate in perinatal epidemiology.
- To address biases and paradoxical findings arising from conditioning on intermediates like birth weight or gestational age.
- To provide methods for resolving the 'birth-weight paradox' and similar issues in exposure-outcome association studies.
Main Methods:
- Approach 1: Conditioning on the predicted risk of the intermediate.
- Approach 2: Conditioning on the intermediate with sensitivity analysis.
- Approach 3: Conditioning on a subgroup where the intermediate's occurrence is independent of exposure, requiring sensitivity analysis.
Main Results:
- The proposed methods facilitate valid inference when assessing effects conditional on an intermediate.
- Approaches 2 and 3 yield a range of estimates and necessitate sensitivity analysis.
- All three approaches can resolve the 'birth-weight paradox' and similar phenomena in perinatal research.
Conclusions:
- The study introduces three methodologically sound approaches to handle intermediates in perinatal epidemiological analyses.
- These methods offer solutions for bias and paradoxes encountered when conditioning on factors like birth weight or gestational age.
- The proposed techniques are broadly applicable to various research settings within perinatal epidemiology.
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