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Huang LS, Cory-Slechta DA, Cox C, et al. Analysis of Nonlinear Associations between Prenatal Methylmercury Exposure from Fish Consumption and Neurodevelopmental Outcomes in the Seychelles Main Cohort at 17 Years. Stoch Environ Res Risk Assess. 2017;32(4):893-904doi: 10.1007/s00477-017-1451-7.
Huang, L. S., Cory-Slechta, D. A., Cox, C., Thurston, S. W., Shamlaye, C. F., Watson, G. E., van Wijngaarden, E., Zareba, G., Strain, J. J., Myers, G. J., & Davidson, P. W. (2018). Analysis of Nonlinear Associations between Prenatal Methylmercury Exposure from Fish Consumption and Neurodevelopmental Outcomes in the Seychelles Main Cohort at 17 Years. Stochastic environmental research and risk assessment : research journal, 32(4), 893-904. https://doi.org/10.1007/s00477-017-1451-7
Huang, Li-Shan, et al. "Analysis of Nonlinear Associations between Prenatal Methylmercury Exposure from Fish Consumption and Neurodevelopmental Outcomes in the Seychelles Main Cohort at 17 Years." Stochastic environmental research and risk assessment : research journal vol. 32,4 (2018): 893-904. doi: https://doi.org/10.1007/s00477-017-1451-7
Huang LS, Cory-Slechta DA, Cox C, Thurston SW, Shamlaye CF, Watson GE, van Wijngaarden E, Zareba G, Strain JJ, Myers GJ, Davidson PW. Analysis of Nonlinear Associations between Prenatal Methylmercury Exposure from Fish Consumption and Neurodevelopmental Outcomes in the Seychelles Main Cohort at 17 Years. Stoch Environ Res Risk Assess. 2018 Apr;32(4):893-904. doi: 10.1007/s00477-017-1451-7. Epub 2017 Sep 06. PMID: 30323714; PMCID: PMC6183066.
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Stoch Environ Res Risk Assess. 2018 Apr;32(4):893-904. doi: 10.1007/s00477-017-1451-7. Epub 2017 Sep 06.

Analysis of Nonlinear Associations between Prenatal Methylmercury Exposure from Fish Consumption and Neurodevelopmental Outcomes in the Seychelles Main Cohort at 17 Years.

Stochastic environmental research and risk assessment : research journal

Li-Shan Huang, Deborah A Cory-Slechta, Christopher Cox, Sally W Thurston, Conrad F Shamlaye, Gene E Watson, Edwin van Wijngaarden, Grazyna Zareba, J J Strain, Gary J Myers, Philip W Davidson

Affiliations

  1. Institute of Statistics, National Tsing Hua University, TAIWAN.
  2. Department of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY.
  3. Department of Environmental Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY.
  4. Department of Pediatrics, University of Rochester School of Medicine and Dentistry, Rochester, NY.
  5. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
  6. Ministry of Health, Republic of Seychelles.
  7. Eastman Department of Dentistry, University of Rochester School of Medicine and Dentistry, Rochester, NY.
  8. Department of Community and Preventive Medicine, University of Rochester School of Medicine and Dentistry, Rochester, NY.
  9. University of Ulster, Coleraine, Northern Ireland.
  10. Department of Neurology, University of Rochester School of Medicine and Dentistry, Rochester, NY.

PMID: 30323714 PMCID: PMC6183066 DOI: 10.1007/s00477-017-1451-7

Abstract

BACKGROUND: The Seychelles Child Development Study has been examining the relationship between prenatal methylmercury (MeHg) exposure from consuming fish during pregnancy and child development. This study re-analyzes seven outcomes in the 17 year Main Cohort data to determine if there are nonlinear or non-homogeneous (subgroup) associations that were not identified in the linear analysis.

METHODS: We adopted two statistical approaches. First, we carried out an additive nonlinear analysis assuming homogeneous prenatal MeHg-outcome relationships to explore overall associations. Second, we applied the regression tree to the Woodcock-Johnson Calculation subtest (it was significantly associated in earlier analyses) and identified 4 clusters based on covariates. Then we used additive models to assess the prenatal MeHg association in each of the four clusters for all seven outcomes. This approach assumes nonlinear associations in each cluster and non-homogeneous associations between clusters.

RESULTS: The additive nonlinear analysis yielded prenatal MeHg curves similar to the linear analysis. For the regression tree analysis, the curves relating prenatal MeHg to outcomes between the 4 clusters differed and some crossed at higher prenatal MeHg levels, suggesting non-homogeneity in the upper range of exposure. Additionally, some of the curves suggested a possible non-linear relationship within the range of exposure we studied.

CONCLUSION: This non-linear analysis supports the findings from the linear analysis. It shows little evidence to support an adverse association of prenatal MeHg exposure through maternal consumption of fish contaminated with natural background levels. However, the tree analysis suggests that the prenatal exposure/outcome relationship may not be homogeneous across all individuals and that some subpopulations may have an adverse association in the upper range of the exposures studied. More robust data in the higher levels of exposure in this cohort are needed to confirm this finding.

Keywords: Child development; generalized additive models; methylmercury; prenatal exposure; regression tree

Conflict of interest statement

Conflicts of Interest: We wish to confirm that there are no known conflicts of interest associated with this paper and there has been no significant financial support for this work that could have inf

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