IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2021i1p425-d715346.html
   My bibliography  Save this article

Prenatal Metal Exposures and Infants’ Developmental Outcomes in a Navajo Population

Author

Listed:
  • Sara S. Nozadi

    (Health Sciences Center, College of Pharmacy, University of New Mexico, Albuquerque, NM 87131, USA)

  • Li Li

    (Department of Mathematics and Statistics, University of New Mexico, Albuquerque, NM 87131, USA)

  • Li Luo

    (Department of Internal Medicine, UNM Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87131, USA)

  • Debra MacKenzie

    (Health Sciences Center, College of Pharmacy, University of New Mexico, Albuquerque, NM 87131, USA)

  • Esther Erdei

    (Health Sciences Center, College of Pharmacy, University of New Mexico, Albuquerque, NM 87131, USA)

  • Ruofei Du

    (Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA)

  • Carolyn W. Roman

    (Health Sciences Center, College of Pharmacy, University of New Mexico, Albuquerque, NM 87131, USA)

  • Joseph Hoover

    (Social Science and Cultural Studies, Montana State University Billing, Billings, MT 59101, USA)

  • Elena O’Donald

    (Health Sciences Center, College of Pharmacy, University of New Mexico, Albuquerque, NM 87131, USA)

  • Courtney Burnette

    (Munroe-Meyer Institute, University of Nebraska Medical Services, Omaha, NE 68106, USA)

  • Johnnye Lewis

    (Health Sciences Center, College of Pharmacy, University of New Mexico, Albuquerque, NM 87131, USA)

Abstract

Early-life exposure to environmental toxicants can have detrimental effects on children’s neurodevelopment. In the current study, we employed a causal modeling framework to examine the direct effect of specific maternal prenatal exposures on infants’ neurodevelopment in the context of co-occurring metals. Maternal metal exposure and select micronutrients’ concentrations were assessed using samples collected at the time of delivery from mothers living across Navajo Nation with community exposure to metal mixtures originating from abandoned uranium mines. Infants’ development across five domains was measured at ages 10 to 13 months using the Ages and Stages Questionnaire Inventory (ASQ:I), an early developmental screener. After adjusting for effects of other confounding metals and demographic variables, prenatal exposure to lead, arsenic, antimony, barium, copper, and molybdenum predicted deficits in at least one of the ASQ:I domain scores. Strontium, tungsten, and thallium were positively associated with several aspects of infants’ development. Mothers with lower socioeconomic status (SES) had higher lead, cesium, and thallium exposures compared to mothers from high SES backgrounds. These mothers also had infants with lower scores across various developmental domains. The current study has many strengths including its focus on neurodevelopmental outcomes during infancy, an understudied developmental period, and the use of a novel analytical method to control for the effects of co-occurring metals while examining the effect of each metal on neurodevelopmental outcomes. Yet, future examination of how the effects of prenatal exposure on neurodevelopmental outcomes unfold over time while considering all potential interactions among metals and micronutrients is warranted.

Suggested Citation

  • Sara S. Nozadi & Li Li & Li Luo & Debra MacKenzie & Esther Erdei & Ruofei Du & Carolyn W. Roman & Joseph Hoover & Elena O’Donald & Courtney Burnette & Johnnye Lewis, 2021. "Prenatal Metal Exposures and Infants’ Developmental Outcomes in a Navajo Population," IJERPH, MDPI, vol. 19(1), pages 1-24, December.
  • Handle: RePEc:gam:jijerp:v:19:y:2021:i:1:p:425-:d:715346
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/1/425/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/1/425/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Brugge, D. & Goble, R., 2002. "The history of uranium mining and the Navajo people," American Journal of Public Health, American Public Health Association, vol. 92(9), pages 1410-1419.
    2. Lauren Hund & Edward J. Bedrick & Curtis Miller & Gabriel Huerta & Teddy Nez & Sandy Ramone & Chris Shuey & Miranda Cajero & Johnnye Lewis, 2015. "A Bayesian framework for estimating disease risk due to exposure to uranium mine and mill waste on the Navajo Nation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 1069-1091, October.
    3. Katherine von Stackelberg & Elizabeth Guzy & Tian Chu & Birgit Claus Henn, 2015. "Exposure to Mixtures of Metals and Neurodevelopmental Outcomes: A Multidisciplinary Review Using an Adverse Outcome Pathway Framework," Risk Analysis, John Wiley & Sons, vol. 35(6), pages 971-1016, June.
    4. Tyler J. VanderWeele & Ilya Shpitser, 2011. "A New Criterion for Confounder Selection," Biometrics, The International Biometric Society, vol. 67(4), pages 1406-1413, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Olivia J. Lindly & Davis E. Henderson & Christine B. Vining & Candi L. Running Bear & Sara S. Nozadi & Shannon Bia, 2023. "“Know Your Children, Who They Are, Their Weakness, and Their Strongest Point”: A Qualitative Study on Diné Parent Experiences Accessing Autism Services for Their Children," IJERPH, MDPI, vol. 20(8), pages 1-22, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tommy Rock & Lindsey Jones & Jani C. Ingram, 2021. "Approaches for Disseminating Environmental Research Findings to Navajo Communities," IJERPH, MDPI, vol. 18(13), pages 1-8, June.
    2. Jonathan Credo & Jaclyn Torkelson & Tommy Rock & Jani C. Ingram, 2019. "Quantification of Elemental Contaminants in Unregulated Water across Western Navajo Nation," IJERPH, MDPI, vol. 16(15), pages 1-15, July.
    3. Tingting Zhou & Michael R. Elliott & Roderick J. A. Little, 2021. "Robust Causal Estimation from Observational Studies Using Penalized Spline of Propensity Score for Treatment Comparison," Stats, MDPI, vol. 4(2), pages 1-21, June.
    4. Eric TC Lai & Ruby Yu & Jean Woo, 2020. "The Associations of Income, Education and Income Inequality and Subjective Well-Being among Elderly in Hong Kong—A Multilevel Analysis," IJERPH, MDPI, vol. 17(4), pages 1-14, February.
    5. Xun Lu, 2015. "A Covariate Selection Criterion for Estimation of Treatment Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 506-522, October.
    6. Leonard Henckel & Emilija Perković & Marloes H. Maathuis, 2022. "Graphical criteria for efficient total effect estimation via adjustment in causal linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(2), pages 579-599, April.
    7. Lefebvre, Geneviève & Atherton, Juli & Talbot, Denis, 2014. "The effect of the prior distribution in the Bayesian Adjustment for Confounding algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 227-240.
    8. Hao, Meiling & Su, Pingfan & Hu, Liyuan & Szabo, Zoltan & Zhao, Qianyu & Shi, Chengchun, 2024. "Forward and backward state abstractions for off-policy evaluation," LSE Research Online Documents on Economics 124074, London School of Economics and Political Science, LSE Library.
    9. Christine Samuel-Nakamura & Wendie A. Robbins & Felicia S. Hodge, 2017. "Uranium and Associated Heavy Metals in Ovis aries in a Mining Impacted Area in Northwestern New Mexico," IJERPH, MDPI, vol. 14(8), pages 1-17, July.
    10. Jie Gao & Haiyan Qu & Keith M. McGregor & Amrej Singh Yadav & Hon K. Yuen, 2022. "Associations between Duration of Homelessness and Cardiovascular Risk Factors: A Pilot Study," IJERPH, MDPI, vol. 19(22), pages 1-10, November.
    11. Agboola, Oluwagbenga David & Yu, Han, 2023. "Neighborhood-based cross fitting approach to treatment effects with high-dimensional data," Computational Statistics & Data Analysis, Elsevier, vol. 186(C).
    12. Caubet, Miguel & Samoilenko, Mariia & Drouin, Simon & Sinnett, Daniel & Krajinovic, Maja & Laverdière, Caroline & Marcil, Valérie & Lefebvre, Geneviève, 2023. "Bayesian joint modeling for causal mediation analysis with a binary outcome and a binary mediator: Exploring the role of obesity in the association between cranial radiation therapy for childhood acut," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
    13. Edward H. Kennedy & Sivaraman Balakrishnan, 2018. "Discussion of “Data†driven confounder selection via Markov and Bayesian networks†by Jenny Häggström," Biometrics, The International Biometric Society, vol. 74(2), pages 399-402, June.
    14. Yongnam Kim, 2019. "The Causal Structure of Suppressor Variables," Journal of Educational and Behavioral Statistics, , vol. 44(4), pages 367-389, August.
    15. Joseph Antonelli & Matthew Cefalu & Nathan Palmer & Denis Agniel, 2018. "Doubly robust matching estimators for high dimensional confounding adjustment," Biometrics, The International Biometric Society, vol. 74(4), pages 1171-1179, December.
    16. Anna Zaytseva & Pierre Verger & Bruno Ventelou, 2023. "Better together? A mediation analysis of general practitioners' performance in multi-professional group practice," AMSE Working Papers 2325, Aix-Marseille School of Economics, France.
    17. Christine Samuel-Nakamura, 2020. "Using Traditional Methods for Collaborative Fieldwork in a Uranium Food Chain Study on Diné Lands in the US Southwest," Sustainability, MDPI, vol. 12(17), pages 1-12, August.
    18. Benjamin A. Jones, 2017. "The social costs of uranium mining in the US Colorado Plateau cohort, 1960–2005," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 62(4), pages 471-478, May.
    19. Contreras, Hugo Alejandro & Candia, Cristian & Olchevskaia, Rodrigo Vladislav Troncoso & Ferres, Leo & Celedón, María Loreto Bravo & Lepri, Bruno & Rodriguez-Sickert, Carlos, 2023. "Linking Physical Violence to Women's Mobility in Chile," SocArXiv uad59, Center for Open Science.
    20. Thomas S. Richardson & James M. Robins & Linbo Wang, 2018. "Discussion of “Data†driven confounder selection via Markov and Bayesian networks†by Häggström," Biometrics, The International Biometric Society, vol. 74(2), pages 403-406, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2021:i:1:p:425-:d:715346. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.