The present study showed that prenatal MeHg exposure adversely affected one of 16 neurodevelopmental endpoints. At 30 months of age the PDI decreased as MeHg increased. This association appeared to be significant only when both MeHg and nutritional indicators were included in the same statistical model, although the association between MeHg and the 30-month PDI was borderline significant when not adjusted for nutrient and dietary status indicators. Moreover, in separate models that included MeHg by itself together with covariates, no significant association was present, paralleling results of previous research involving similar cohorts (Davidson, et al., 1998
; Myers, et al., 2003
). The 30 Month PDI was the only outcome significantly related to MeHg exposure. No other associations were present at any other age on any of the 3 other primary or 12 other secondary endpoints. We found some direct evidence that prenatal exposure to iodine may exert a positive influence on at least one measure of early postnatal cognitive development but that association was unrelated to MeHg.
These results need to be confirmed, but could be of importance for two reasons. First, they suggest that nutritional status and MeHg exposure may simultaneously influence developmental outcomes in opposite directions, and these effects can be separated only by careful measurement and statistical modeling. Second, these results would help to clarify the apparently anomalous association between increasing prenatal MeHg exposure and better neurodevelopmental outcomes seen at age 66 months in the Seychelles Main Cohort (Davidson, et al., 1998
) and by the Faeroes study at age 1 year (Grandjean, et al., 1995
). Our findings suggest that the beneficial influence of nutrients derived from fish and the overall diet need to be considered in order to fully interpret the risk of a neurodevelopmental effect from prenatal MeHg exposure from fish consumption.
These results do not directly clarify which nutrients or dietary indicators may be exerting an influence on performance or what the mechanism or mechanisms of influence may be. Hibbeln and colleagues (2007)
in the ALSPAC study showed that fish consumption during pregnancy of >340 grams/ week was associated with beneficial effects on child development. In addition, Butz-Jørgensen and colleagues (2007)
reported that fish consumption in the Faeroese cohort, mainly as North Atlantic cod, correlated with cord blood mercury levels and was associated with beneficial effects on child development. They noted that when correction was made for the confounding due to fish consumption, the adverse association between MeHg and child development was more significant. They also noted that patterns of fish consumption may vary among different populations and that it might be preferable to measure specific nutrients from fish. This variation in consumption appears to occur in the Seychelles population, since we found no correlation of maternal hair MeHg concentration and fish consumption, but we did find correlations and confounding with specific nutritional indicators such as DHA. This is not surprising because fish species vary substantially in concentrations of both MeHg and nutrients. Consequently the mother’s nutritional status may not show a direct relationship with fish or nutrient intake because there are many intrinsic and extrinsic factors that are involved such as bioavailability and physiological state. These factors are not taken into account when measuring only fish meals. The results of this study suggest that there may be biological and neurodevelopmental consequences of the interplay between DHA, other nutrients, and MeHg when fish is consumed.
Although the DHA and AA effects did not reach statistical significance, the confidence intervals indicated improving performance on the BSID-II PDI at 30 months associated with increasing DHA and declining performance associated with increasing AA. There might be several reasons to explain the lack of significant p
values for DHA and AA effects. First, of course, our hypothesis that LCPUFA may counterbalance an effect of MeHg could be incorrect. But a lack of significance could also have resulted from underpowering. Indeed, the coefficients in the Nutrition Model associated with DHA and AA are in opposite directions and if the coefficients were the same in a larger study they would be significant. These associations are of potential importance and deserve further study. Several authors have suggested that Ω-3 LCPUFA may play a unique role in promoting central nervous system development (Gibson, et al., 2001
; O’Connor, et al., 2001
; Rioux, et al., 2006
; Strain, et al., 2004
). However, our finding that their influence on the developing brain may change in relation to prenatal MeHg exposure raises questions about the relationship between the two compounds. More data are needed before the underlying biological relationship between LCPUFA and MeHg can be clarified. Our statistical modeling also suggested that after accounting for DHA, AA may have an adverse effect on the BSID-II PDI. Recent studies in the non-human primate CNS have highlighted the importance of AA and DHA in the basal ganglia and brainstem and related them to changes in motor development (Diau, et al., 2005
). These findings could help explain the complex interplay between AA and DHA and why increasing AA was associated with decreasing PDI scores in the present study.
Our results indicating improved performance on VEXP Overall Percentage Anticipatory Saccades at 5 months with better maternal iodine status are consistent with previous studies of iodine supplementation (O’Donnell, et al., 2002
The suggestion of combined effects of MeHg and nutritional status indicators occurred primarily on an endpoint measuring psychomotor rather than cognitive development. The reasons for this result are unclear. It may be that the principal impact of beneficial effects of many of the nutritional status indicators we measured occurs on visually mediated behaviors, as has been reported (Dunstan, et al., 2006
; Gibson, et al., 2001
; Helland, et al., 2003
; O’Connor, et al., 2001
; Willatts, 2002
The drop in BSID-II scores from 9 months to 30 months was not expected for normal infants and toddlers (Harris, et al., 2005
; Niccols and Latchman, 2002
) and may be important. This finding does not appear to be related to administration of the test as scoring reliabilities were uniformly high and the variability around the BSID-II means was similar to what would have been expected if US children had been examined. The drop in mean scores from 9 to 30 months might have been the result of cultural bias. At 30 months, the Mental Scale is comprised of more language based itmes than at earlier ages, perhaps creating a disparity between the Seychellois cohort and the normative population. Such a circumstance would not explain the comparable drop in the PDI, which measures fine and gross motor skills and perceptual motor responses. This finding deserves further study.
The premise tested in this study was that prenatal co-exposures to MeHg and nutrients in fish are confounded and if separated, might reveal different effects on developmental outcomes. The study was not designed to consider also the influence of postnatal exposures to either MeHg or nutrients because the focus of public health concern has been on prenatal MeHg exposure. Postnatal MeHg exposure was therefore not measured. Measuring postnatal MeHg exposure presents many challenges. There is no agreed upon metric aside from the convenience measure of recent exposure (usually amounting to hair or blood MeHg measured at the time of a particular postnatal developmental evaluation). In the Main Cohort Study (Davidson, et al., 1998
; Myers, et al., 2003
) we adjusted for postnatal MeHg first at 5.5 years. By that age, the children in the Seychelles appear top have established their own pattern of fish consumption. We also know from previous work that prenatal and postnatal MeHg levels are not correlated (r=0.08, Myers, et al., 2003
). We expected that any effects of nutrients were likely to be mainly prenatal (Strain et al, 2004
Our study has some important strengths and limitations. We were able to measure specific nutrients including LCPUFA, iodine, and other nutritional parameters during pregnancy and examine their associations with the children’s developmental outcomes. Some but not all psychosocial covariates known to influence child development had the expected effect on our developmental endpoints. However, the sample size of the study was smaller than we had planned. About half of the subjects with complete data did have hair MeHg levels ≥5 ppm but the difference in mean BSID-II scores between the low and high MeHg groups was small and ranged from 0 for the 30-month MDI to 2.7 for the 30-month PDI. Although we selected a number of nutrients known to affect neurodevelopment, other nutrients may be influential in determining developmental outcomes in a fish consuming population. Direct assessment of choline in maternal blood might have been important, but logistic and technical problems precluded this. Finally, the study involved multiple examinations at several different ages using several different endpoints. We found only one statistical association with MeHg and the four primary endpoints. Follow-up examinations of our cohort at later ages may reveal different results. A larger scale confirmatory study may be needed to further explore some of these issues.
In conclusion, this study suggests that nutrients present in fish and maternal diets may act as confounders in detecting associations between prenatal MeHg exposure from fish consumption and child development. These results suggest that MeHg and nutrition have competing roles in relationship to child development. Nutrients may protect the developing brain from the toxic action of MeHg or alternatively MeHg exposure from fish consumption may diminish the efficacy of the beneficial action of nutrients. These competing explanations of our findings deserve further study and if confirmed could have important public health implications.