Environment International (Dec 2018)

Urinary metals and metal mixtures in Bangladesh: Exploring environmental sources in the Health Effects of Arsenic Longitudinal Study (HEALS)

  • Tiffany R. Sanchez,
  • Vesna Slavkovich,
  • Nancy LoIacono,
  • Alexander van Geen,
  • Tyler Ellis,
  • Steven N. Chillrud,
  • Olgica Balac,
  • Tarique Islam,
  • Faruque Parvez,
  • Habib Ahsan,
  • Joseph H. Graziano,
  • Ana Navas-Acien

Journal volume & issue
Vol. 121
pp. 852 – 860

Abstract

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Introduction: Environmental exposure to toxic metals and metalloids is pervasive and occurs from multiple sources. The Health Effects of Arsenic Longitudinal Study (HEALS) is an ongoing prospective study predominantly focused on understanding health effects associated with arsenic exposure from drinking water. The goal of this project was to measure a suite of elements in urine to better understand potential exposure patterns and to identify common environmental sources of exposure among this semi-rural Bangladeshi population. Methods: In a random sample of 199 adult HEALS participants (50% female), the concentrations of 15 urinary elements (As, Ba, Cd, Co, Cs, Cu, Mn, Mo, Ni, Pb, Se, Sr, Tl, W, Zn) were assessed by Inductively-Coupled Plasma Mass Spectrometry (ICP-MS) to assess commonalities with sociodemographic characteristics and potential sources of exposure. We used principal component analysis (PCA) with varimax normalized rotations, and hierarchical cluster analysis (CA), using Ward's method with Euclidean distances, to evaluate these relationships. Results: PCA and CA showed similar patterns, suggesting 6 principal components (PC) and 5 clusters: 1)PC: Sr-Ni-Cs/ CA: Sr-Ni-Co; 2) Pb-Tl/Pb-Tl-Se-Cs; 3) As-Mo-W/As-Mo-W; 4) Ba-Mn/Ba-Mn; 5) Cu-Zn/Cu-Zn-Cd; and 6) Cd. There was a strong significant association between the As-Mo-W PC/cluster and water arsenic levels (p < 0.001) and between the Cd PC and betel nut use (p = 0.003). The Sr-Ni-Cs PC was not related to any of the socio-demographic characteristics investigated, including smoking status and occupation. The first PC, Sr-Ni-Cs, explained 21% of the variability; the third PC, As-Mo-W, explained 12.5% of the variability; and the sixth PC, Cd, explained 10% of the variability. Day laborers appeared to have the highest exposure. Conclusions: Groundwater and betel nut use are likely important sources of metal and metalloid exposure in this population. These findings will guide future exposure assessment research in Bangladesh and future epidemiologic research investigating the degree to which metal mixtures play a role in disease development. Keywords: Metals, Metalloids, Metal mixtures, Biomonitoring, Groundwater, Betel nut use, Air pollution