title: Estimation of health effects of prenatal methylmercury exposure using structural equation models.
abstract: BACKGROUND
  Observational studies in epidemiology always involve concerns regarding validity, especially measurement error, confounding, missing data, and other problems that may affect the study outcomes. Widely used standard statistical techniques, such as multiple regression analysis, may to some extent adjust for these shortcomings. However, structural equations may incorporate most of these considerations, thereby providing overall adjusted estimations of associations. This approach was used in a large epidemiological data set from a prospective study of developmental methyl-mercury toxicity.
  
  
  RESULTS
  Structural equation models were developed for assessment of the association between biomarkers of prenatal mercury exposure and neuropsychological test scores in 7 year old children. Eleven neurobehavioral outcomes were grouped into motor function and verbally mediated function. Adjustment for local dependence and item bias was necessary for a satisfactory fit of the model, but had little impact on the estimated mercury effects. The mercury effect on the two latent neurobehavioral functions was similar to the strongest effects seen for individual test scores of motor function and verbal skills. Adjustment for contaminant exposure to poly chlorinated biphenyls (PCBs) changed the estimates only marginally, but the mercury effect could be reduced to non-significance by assuming a large measurement error for the PCB biomarker.
  
  
  CONCLUSIONS
  The structural equation analysis allows correction for measurement error in exposure variables, incorporation of multiple outcomes and incomplete cases. This approach therefore deserves to be applied more frequently in the analysis of complex epidemiological data sets.
authors.affiliation: Department of Biostatistics, University of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen, Denmark. ebj@biostat.ku.dk
authors.forename: Esben
authors.initials: E
authors.lastname: Budtz-Jørgensen
authors.forename: Niels
authors.initials: N
authors.lastname: Keiding
authors.forename: Philippe
authors.initials: P
authors.lastname: Grandjean
authors.forename: Pal
authors.initials: P
authors.lastname: Weihe
mesh_terms: D015415:Biomarkers / Q000097:blood; D002648:Child; D015331:Cohort Studies; D003718:Denmark / Q000453:epidemiology; D002658:Developmental Disabilities / Q000139:chemically induced* / Q000453:epidemiology*; D005260:Female; D005312:Fetal Blood / Q000737:chemistry / Q000187:drug effects; D005396:Fish Products / Q000633:toxicity*; D006801:Humans; D016013:Likelihood Functions; D018811:Maternal Exposure / Q000009:adverse effects*; D008431:Maternal-Fetal Exchange; D020262:Mercury Poisoning, Nervous System / Q000150:complications / Q000453:epidemiology*; D008767:Methylmercury Compounds / Q000097:blood* / Q000633:toxicity*; D015999:Multivariate Analysis; D009420:Nervous System / Q000187:drug effects / Q000254:growth & development*; D009483:Neuropsychological Tests; D011247:Pregnancy; D018570:Risk Assessment
chemical_list: D015415:Biomarkers; D008767:Methylmercury Compounds