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Intergenerational Associations Between Maternal Diet and Childhood Adiposity: A Bayesian Regularized Mediation Analysis

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  • Yu-Bo Wang

    (Clemson University)

  • Cuilin Zhang

    (Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health)

  • Zhen Chen

    (Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health)

Abstract

Growing evidence supports a positive association between childhood obesity and chronic diseases in later life. It is also suggested that childhood obesity is more prevalent for children born from pregnancies complicated by metabolic disorders such as gestational diabetes, and can be related to maternal dietary factors during gestation. Extending conventional analyses that report only the marginal associations within non-causal mediation frameworks, we present mediation analysis in the case of multiple exposures and multiple mediators using a regularized two-stage approach. By placing shrinkage priors on each parameter relating to direct and indirect effects, a parsimonious model can be obtained, and consequently, the most relevant pathways will be selected to inform the development of efficient prevention programs. We apply this method to data from the Danish site of the Diabetes & Women’s Health Study, Danish National Birth Cohort (DNBC), and find 6 significant maternal risk factors either directly or indirectly affecting childhood body mass index z score at age 7. Simulations with data-generating mechanisms similar to the DNBC data demonstrate good performance of the proposed model.

Suggested Citation

  • Yu-Bo Wang & Cuilin Zhang & Zhen Chen, 2021. "Intergenerational Associations Between Maternal Diet and Childhood Adiposity: A Bayesian Regularized Mediation Analysis," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(3), pages 524-542, December.
    • Handle: RePEc:spr:stabio:v:13:y:2021:i:3:d:10.1007_s12561-021-09305-7
    DOI: 10.1007/s12561-021-09305-7
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    References listed on IDEAS

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    1. Michael J. Daniels & Jason A. Roy & Chanmin Kim & Joseph W. Hogan & Michael G. Perri, 2012. "Bayesian Inference for the Causal Effect of Mediation," Biometrics, The International Biometric Society, vol. 68(4), pages 1028-1036, December.
    2. Park, Trevor & Casella, George, 2008. "The Bayesian Lasso," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 681-686, June.
    3. Yanyi Song & Xiang Zhou & Min Zhang & Wei Zhao & Yongmei Liu & Sharon L. R. Kardia & Ana V. Diez Roux & Belinda L. Needham & Jennifer A. Smith & Bhramar Mukherjee, 2020. "Bayesian shrinkage estimation of high dimensional causal mediation effects in omics studies," Biometrics, The International Biometric Society, vol. 76(3), pages 700-710, September.
    4. Yen-Tsung Huang & Wen-Chi Pan, 2016. "Hypothesis test of mediation effect in causal mediation model with high-dimensional continuous mediators," Biometrics, The International Biometric Society, vol. 72(2), pages 402-413, June.
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    Cited by:

    1. Li He & Yu-Bo Wang & William C. Bridges & Zhulin He & S. Megan Che, 2023. "Bayesian Framework for Causal Inference with Principal Stratification and Clusters," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(1), pages 114-140, April.

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