Miguel García-Villarino1, Antonio J Signes-Pastor2, Margaret R Karagas3, Isolina Riaño-Galán4, Cristina Rodríguez-Dehli5, Joan O Grimalt6, Eva Junqué6, Ana Fernández-Somoano7, Adonina Tardón1. 1. Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Monforte de Lemos Avenue 3-5, 28029, Madrid, Spain; Unidad de Epidemiología Molecular Del Cáncer, Instituto Universitario de Oncología Del Principado de Asturias (IUOPA) - Departamento de Medicina, Universidad de Oviedo, Julián Clavería Street S/n, 33006, Oviedo, Asturias, Spain; Instituto de Investigación Sanitaria Del Principado de Asturias (ISPA), Roma Avenue S/n, 33001, Oviedo, Spain. 2. Department of Epidemiology, Geisel School of Medicine, Dartmouth College, 1 Medical Center Dr., Lebanon, NH, 03756, USA; Department of Public Health. Universidad Miguel Hernández, Avenida de Alicante KM 87, 03550, Sant Joan D'Alacant, Spain. 3. Department of Epidemiology, Geisel School of Medicine, Dartmouth College, 1 Medical Center Dr., Lebanon, NH, 03756, USA. 4. Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Monforte de Lemos Avenue 3-5, 28029, Madrid, Spain; Servicio de Pediatría, Endocrinología Pediátrica, HUCA, Roma Avenue S/n, 33001, Oviedo, Asturias, Spain. 5. Servicio de Pediatría, Hospital San Agustín, Heros Street 4, 33410, Avilés, Asturias, Spain. 6. Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Jordi Girona Street 18-26, 08034, Barcelona, Cataluña, Spain. 7. Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Monforte de Lemos Avenue 3-5, 28029, Madrid, Spain; Unidad de Epidemiología Molecular Del Cáncer, Instituto Universitario de Oncología Del Principado de Asturias (IUOPA) - Departamento de Medicina, Universidad de Oviedo, Julián Clavería Street S/n, 33006, Oviedo, Asturias, Spain; Instituto de Investigación Sanitaria Del Principado de Asturias (ISPA), Roma Avenue S/n, 33001, Oviedo, Spain. Electronic address: fernandezsana@uniovi.es.
Abstract
BACKGROUND: Exposure to toxic and non-toxic metals impacts childhood growth and development, but limited data exists on exposure to metal mixtures. Here, we investigated the effects of exposure to individual metals and a mixture of barium, cadmium, cobalt, lead, molybdenum, zinc, and arsenic on growth indicators in children 4-5 years of age. METHODS: We used urine metal concentrations as biomarkers of exposure in 328 children enrolled in the Spanish INMA-Asturias cohort. Anthropometric measurements (arm, head, and waist circumferences, standing height, and body mass index) and parental sociodemographic variables were collected through face-to-face interviews by trained study staff. Linear regressions were used to estimate the independent effects and were adjusted for each metal in the mixture. We applied Bayesian kernel machine regression to examine non-linear associations and potential interactions. RESULTS: In linear regression, urinary levels of cadmium were associated with reduced arm circumference (βadjusted = -0.44, 95% confidence interval [CI]: -0.73, -0.15), waist circumference (βadjusted = -1.29, 95% CI: -2.10, -0.48), and standing height (βadjusted = -1.09, 95% CI: -1.82, -0.35). Lead and cobalt concentrations were associated with reduced standing height (βadjusted = -0.64, 95% CI: -1.20, -0.07) and smaller head circumference (βadjusted = -0.29, 95% CI: -0.49, -0.09), respectively. However, molybdenum was positively associated with head circumference (βadjusted = 0.22, 95% CI: 0.01, 0.43). BKMR analyses showed strong linear negative associations of cadmium with arm and head circumference and standing height. BKMR analyses also found lead and cobalt in the metal mixture were related to reduce standing height and head circumference, and consistently found molybdenum was related to increased head circumference. CONCLUSION: Our findings suggest that exposure to metal mixtures impacts growth indicators in children.
BACKGROUND: Exposure to toxic and non-toxic metals impacts childhood growth and development, but limited data exists on exposure to metal mixtures. Here, we investigated the effects of exposure to individual metals and a mixture of barium, cadmium, cobalt, lead, molybdenum, zinc, and arsenic on growth indicators in children 4-5 years of age. METHODS: We used urine metal concentrations as biomarkers of exposure in 328 children enrolled in the Spanish INMA-Asturias cohort. Anthropometric measurements (arm, head, and waist circumferences, standing height, and body mass index) and parental sociodemographic variables were collected through face-to-face interviews by trained study staff. Linear regressions were used to estimate the independent effects and were adjusted for each metal in the mixture. We applied Bayesian kernel machine regression to examine non-linear associations and potential interactions. RESULTS: In linear regression, urinary levels of cadmium were associated with reduced arm circumference (βadjusted = -0.44, 95% confidence interval [CI]: -0.73, -0.15), waist circumference (βadjusted = -1.29, 95% CI: -2.10, -0.48), and standing height (βadjusted = -1.09, 95% CI: -1.82, -0.35). Lead and cobalt concentrations were associated with reduced standing height (βadjusted = -0.64, 95% CI: -1.20, -0.07) and smaller head circumference (βadjusted = -0.29, 95% CI: -0.49, -0.09), respectively. However, molybdenum was positively associated with head circumference (βadjusted = 0.22, 95% CI: 0.01, 0.43). BKMR analyses showed strong linear negative associations of cadmium with arm and head circumference and standing height. BKMR analyses also found lead and cobalt in the metal mixture were related to reduce standing height and head circumference, and consistently found molybdenum was related to increased head circumference. CONCLUSION: Our findings suggest that exposure to metal mixtures impacts growth indicators in children.
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