| Titre : | Chemical Contaminant Exposure among Pregnant Women: Socio-Ecological Characteristics and the Role of Migration Status |
| Auteurs : | Ben Christopher Martella ; Ecole des hautes études en santé publique (EHESP) (Rennes, FRA) |
| Type de document : | Mémoire |
| Année de publication : | 2025 |
| Description : | 29p. |
| Langues: | Anglais |
| Classement : | MPH/ (Mémoires MPH à partir de 2024) |
| Mots-clés : | Femme enceinte ; Grossesse ; Exposition ; Produit chimique ; Migrant ; Facteur socioéconomique |
| Résumé : |
Background: Prenatal exposure to chemical contaminants is a public health concern, particularly for vulnerable populations such as pregnant women and immigrants. Social, behavioral, and environmental factors contribute to disparities in exposure patterns.
Methods: Data from the French ELFE birth cohort (n = 12,201) were used to assess exposure to 210 contaminants through diet during pregnancy. Exposure data were summarized into eight latent chemical mixture exposures using Sparse Non-negative Matrix Under-approximation (SNMU). A hierarchical regression framework was used to examine the socioecological characteristics (e.g., migration status, education, income, smoking) related to the exposure to chemical mixtures. Results: Migration status, income, and smoking were associated with variation in chemical mixture exposures. Immigrant women had higher scores for PCB-BFR-MeHg, Pest-3, and Mixt-4. Smoking was positively associated with TE-F-PAH; higher income was negatively associated with TE-F-PAH and positively with PCB-BFR-MeHg. In stratified models by migration status, education and income were associated with higher exposures among descendants of immigrants, while BMI and smoking were associated with higher exposures among non-immigrants. Among immigrants, only unemployment was consistently associated with exposure. Conclusion: Heterogeneous chemical mixture exposures during pregnancy were associated with indicators of social position and health behaviors. Applying a socioecological framework in combination with mixture modeling may help clarify how multilevel social factors shape environmental exposure patterns and support the development of targeted public health strategies. |
| Diplôme : | Master MPH of public health |
| Plan de classement simplifié : | Master of Public Health - master international de Santé Publique (MPH) |
| En ligne : | https://documentation.ehesp.fr/memoires/2025/mph/ben_christopher_martella.pdf |
Documents numériques (1)
Full text URL |
