Use of advanced cluster analysis to characterize seafood consumption patterns and methyle mercury exposures among pregnant women

François Pouzaud (1) , Assia Ibbou (2, 3) , Sandrine Blanchemanche (1) , Philippe Grandjean (4) , Michel Krempf (5) , Philippe Verger (1)

1 MET@RISK - Méthodologies d'Analyse de Risque Alimentaire
2 SAMOS - Statistique Appliquée et MOdélisation Stochastique
3 CES - Centre d'économie de la Sorbonne
4 LST - Laboratoire de Sciences de la Terre
5 Biologie et physiopathologie intestinales. Pharmacologie nutritionnelle

Because of the variability in food contamination and nutrient contents, consumers must balance the risks and benefits of fish consumption through their choice of species, meal size and frequency. The objectives of this study were to characterize the risk of MeHg exposure in French pregnant women consuming fish, and to explore the use of unsupervised statistical learning as an advanced type of cluster analysis to identify patterns of fish consumption that could predict exposure to MeHg and the coverage of the Recommended Daily Allowance for n-3 PUFA. The proportion of pregnant women exposed at levels higher than the Tolerable Weekly Intake (PTWI) for MeHg is similar to that observed amongst women of childbearing age in previous French studies. At the same time, only about 50% of the women reached the recommended intake of 500 mg/day n-3 PUFA. Cluster analysis of the fish consumption showed that they could be grouped in five major clusters that are largely predictable of the intake of both MeHg and n-3 PUFA. This study provides demonstrates that a global increase in seafood consumption could lead to MeHg exposure above the toxicological limits, thereby questioning the potential beneficial effects of n-3 PUFA intakes.

Mots clés: nonsupervised clustering; Methylmercury; pregnancy; fish; dietary exposure; biomarker; nonsupervised clustering.

Domaines: Statistiques [math.ST]; Théorie [stat.TH]

François Pouzaud, Assia Ibbou, Sandrine Blanchemanche, Philippe Grandjean, Michel Krempf, et al.. Use of advanced cluster analysis to characterize seafood consumption patterns and methyle mercury exposures among pregnant women. 2008. ⟨hal-00264941⟩