1. Modeling the Causal Effects of Assisted Reproductive Technology (ART)
on Neurodevelopmental Impairment
Edwina Yeung1, Candace Robledo1, Nansi Boghossian1, Aijun Ye1, Erin Bell2, Enrique Schisterman1
1 Epidemiology Branch, Division of Intramural Population Health Research, NICHD, Bethesda, MD
2 Department of Environmental Health Sciences, School of Public Health, State University of New York at Albany, Albany, New York
Background
Results
Conflicting findings across studies investigating ART on childhood neurodevelopmental impairment (NDI) may be due to inappropriate causal modeling.
Confounding versus mediation not always clearly distinguished and properly treated in analyses.
Concern that adjustment for birth outcomes in analyses biases effect estimates through collider stratification.
Figure 1. Causal diagram capturing the association between ART and childhood neurodevelopmental impairment (NDI).
Figure 2. Bias from adjustment of preterm birth
Objectives
Present the causal model using a directed acyclic graph (DAG) to illustrate the underlying association between ART and childhood NDI.
Determine the minimal model for unbiased estimation of causal effects based on the DAG.
Estimate the bias to the odds ratio (OR) for the association between ART and NDI when incorrectly adjusting for a birth outcome mediator such as preterm birth.
Parameter Estimates as Odds Ratios
True OR
Bias Estimates A B E D C
Bias SE
% Bias
Adjusted OR (95% CI)
0.5
1.6
1.4 1
-0.034
0.095
-3.4%
0.97 (0.81,1.17)
1.5
0.021
0.091
2.1%
1.02 (0.85,1.21) 2
0.034
0.088
3.4%
1.03 (0.87,1.23)
0.027
2.7%
1.03 (0.86,1.21)
-0.013
-1.3%
0.99 (0.83,1.20)
-0.029
0.093
-2.9%
0.97 (0.82,1.17)
1.2
-0.057
0.094
-4.8%
1.14 (0.95,1.38)
0.018
1.5%
1.22 (1.01,1.45)
0.089
1.8%
1.22 (1.02,1.46)
0.015
1.3%
-0.024
0.092
-2.0%
1.18 (0.99,1.42)
-0.053
-4.4%
1.15 (0.97,1.37)
-0.117
0.097
-7.3%
1.48 (1.22,1.80)
0.004
0.3%
1.60 (1.33,1.93)
-0.009
-0.6%
1.59 (1.34,1.88)
-0.019
-1.2%
1.58 (1.32,1.88)
-0.045
0.096
-2.8%
1.55 (1.29,1.87)
-0.108
-6.8%
1.49 (1.25,1.82)
2.0
-0.158
0.099
-9.9%
1.44 (1.20,1.77)
0.098
1.63 (1.34,1.97)
0.041
2.6%
1.64 (1.37,1.96)
0.029
1.63 (1.34,1.94)
-0.072
-4.5%
1.53 (1.27,1.86)
-0.151
0.101
-9.4%
1.45 (1.17,1.76)
† Maternal age, maternal BMI, race/ethnicity, SES
¥ Pre-existing maternal conditions such as mental health, infectious disease, chronic hypertension, etc
€ Paternal age and BMI
£ Lead exposure and other environmental pollutants
§ Alcohol, smoking, vitamin use
‡ Pregnancy complications such as gestational diabetes, preeclampsia, etc.
Minimal Model
Set #1
Set #2
Duration of Infertility
Infertility Diagnosis
Maternal age
Maternal BMI
Race/ethnicity
Socioeconomic status
Paternal age
Paternal BMI
Maternal mental health
Maternal chronic hypertension
Infectious disease
Maternal thyroid
Maternal preexisting diabetes
Alcohol intake
Lead exposure
Smoking
Environmental Pollutants
Vitamin use
Methods
Literature review for evidence explaining paths between all relevant variables in the association between ART and NDI.
Used DAGitty 2.0, a free online program ( to identify a minimum set of factors (i.e. confounders) for unbiased estimation of ART effects on NDI.
Simulation conducted to quantify the bias resulting from adjusting for a dichotomous collider (i.e., preterm birth).
Simulation of a sample of 1000 ART children and 1000 non-ART children in which the ORs of NDI among ART children ranged from , risks of NDI resulting from preterm birth ranged from and risks of preterm birth resulting from ART ranged from
Conclusions
We identified two sets of factors that can be adjusted for to determine the causal association between ART and offspring neurodevelopmental outcomes. These sets of confounding factors should also be largely relevant for studying effects of other infertility treatments apart from ART.
Even as adjusting for birth outcomes such as preterm birth induces bias, the magnitude of the bias is not large.
Contact: Edwina Yeung
6100 Executive Blvd, 7B07
Bethesda, MD 20892
Acknowledgment: Supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH.