Bayesian modelling of effects of prenatal alcohol exposure on child cognition based on data from multiple cohorts

Author:

Dang Khue‐Dung1ORCID,Ryan Louise M.23,Akkaya Hocagil Tugba4,Cook Richard J.4,Richardson Gale A.5,Day Nancy L.5,Coles Claire D.6,Carmichael Olson Heather7,Jacobson Sandra W.8,Jacobson Joseph L.8

Affiliation:

1. School of Mathematics and Statistics University of Melbourne Parkville VIC 3010 Australia

2. School of Mathematical and Physical Sciences University of Technology Sydney Ultimo NSW 2007 Australia

3. Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers Parkville VIC 3010 Australia

4. Department of Statistics and Actuarial Science University of Waterloo Waterloo ON N2L 3G1 Canada

5. Department of Psychiatry University of Pittsburgh Pittsburgh PA 15213 USA

6. Department of Psychiatry and Behavioral Sciences Emory University Atlanta GA 30322 USA

7. Seattle Children's Research Institute Seattle WA 98105 USA

8. Wayne State University School of Medicine Detroit MI 48201 USA

Abstract

SummaryHigh levels of prenatal alcohol exposure (PAE) result in significant cognitive deficits in children, but the exact nature of the dose‐response relationship is less well understood. To investigate this relationship, data were assembled from six longitudinal birth cohort studies examining the effects of PAE on cognitive outcomes from early school age through adolescence. Structural equation models (SEMs) are a natural approach to consider, because of the way they conceptualise multiple observed outcomes as relating to an underlying latent variable of interest, which can then be modelled as a function of exposure and other predictors of interest. However, conventional SEMs could not be fitted in this context because slightly different outcome measures were used in the six studies. In this paper we propose a multi‐group Bayesian SEM that maps the unobserved cognition variable to a broad range of observed outcomes. The relation between these variables and PAE is then examined while controlling for potential confounders via propensity score adjustment. By examining different possible dose‐response functions, the proposed framework is used to investigate whether there is a threshold PAE level that results in minimal cognitive deficit.

Funder

Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers

National Institute on Alcohol Abuse and Alcoholism

Natural Sciences and Engineering Research Council of Canada

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

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