Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Contribution of arsenic and uranium in private wells and community water systems to urinary biomarkers in US adults: The Strong Heart Study and the Multi-Ethnic Study of Atherosclerosis



Chronic exposure to inorganic arsenic (As) and uranium (U) in the United States (US) occurs from unregulated private wells and federally regulated community water systems (CWSs). The contribution of water to total exposure is assumed to be low when water As and U concentrations are low.


We examined the contribution of water As and U to urinary biomarkers in the Strong Heart Family Study (SHFS), a prospective study of American Indian communities, and the Multi-Ethnic Study of Atherosclerosis (MESA), a prospective study of racially/ethnically diverse urban U.S. communities.


We assigned residential zip code-level estimates in CWSs (µg/L) and private wells (90th percentile probability of As >10 µg/L) to up to 1485 and 6722 participants with dietary information and urinary biomarkers in the SHFS (2001–2003) and MESA (2000–2002; 2010–2011), respectively. Urine As was estimated as the sum of inorganic and methylated species, and urine U was total uranium. We used linear mixed-effects models to account for participant clustering and removed the effect of dietary sources via regression adjustment.


The median (interquartile range) urine As was 5.32 (3.29, 8.53) and 6.32 (3.34, 12.48) µg/L for SHFS and MESA, respectively, and urine U was 0.037 (0.014, 0.071) and 0.007 (0.003, 0.018) µg/L. In a meta-analysis across both studies, urine As was 11% (95% CI: 3, 20%) higher and urine U was 35% (5, 73%) higher per twofold higher CWS As and U, respectively. In the SHFS, zip-code level factors such as private well and CWS As contributed 46% of variation in urine As, while in MESA, zip-code level factors, e.g., CWS As and U, contribute 30 and 49% of variation in urine As and U, respectively.

Impact statement

We found that water from unregulated private wells and regulated CWSs is a major contributor to urinary As and U (an estimated measure of internal dose) in both rural, American Indian populations and urban, racially/ethnically diverse populations nationwide, even at levels below the current regulatory standard. Our findings indicate that additional drinking water interventions, regulations, and policies can have a major impact on reducing total exposures to As and U, which are linked to adverse health effects even at low levels.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type



Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Percent change (95% confidence intervals, CIs) in urinary arsenic (As) or uranium (U) by twofold higher water As1,2 or U3,4 in the Strong Heart Family Study (SHFS) and the Multi-Ethnic Study of Atherosclerosis (MESA).

Data availability

Investigators interested in analyzing MESA data can submit a paper proposal for consideration by the Publications and Presentations (P&P) Committee. The only requirement on an outside investigator is that a MESA investigator be a sponsor. Once a paper proposal has been approved, the lead investigator may request a dataset from the Coordinating Center. Investigators interested in analyzing SHS data can apply to use the data according to established protocol for SHS Resource and Data Sharing, including community approval through formal application (

The statistical code for analysis is available upon reasonable request, please contact MS at


  1. International Agency for Research on Cancer, World Health Organization. Arsenic, metals, fibres and dusts. IARC monographs on the evaluation of carcinogenic risks to humans 2012.

  2. Sanders AP, Messier KP, Shehee M, Rudo K, Serre ML, Fry RC. Arsenic in North Carolina: public health implications. Environ Int. 2012;38:10–6.

    Article  CAS  PubMed  Google Scholar 

  3. Baris D, Waddell R, Beane Freeman LE, Schwenn M, Colt JS, Ayotte JD et al. Elevated bladder cancer in Northern New England: the role of drinking water and arsenic. J Natl Cancer Institute. 2016;108:djw099.

  4. Smith AH, Hopenhayn-Rich C, Bates MN, Goeden HM, Hertz-Picciotto I, Duggan HM, et al. Cancer risks from arsenic in drinking water. Environ Health Perspect. 1992;97:259–67.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Moon K, Guallar E, Navas-Acien A. Arsenic exposure and cardiovascular disease: an updated systematic review. Curr Atheroscler Rep. 2012;14:542–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Corlin L, Rock T, Cordova J, Woodin M, Durant JL, Gute DM, et al. Health effects and environmental justice concerns of exposure to uranium in drinking water. Curr Environ Health Rep. 2016;3:434–42.

    Article  CAS  PubMed  Google Scholar 

  7. Zychowski KE, Kodali V, Harmon M, Tyler CR, Sanchez B, Ordonez Suarez Y, et al. Respirable uranyl-vanadate-containing particulate matter derived from a legacy uranium mine site exhibits potentiated cardiopulmonary toxicity. Toxicol Sci. 2018;164:101–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. O'Rourke MK, Rogan SP, Jin S, Robertson GL. Spatial distributions of arsenic exposure and mining communities from NHEXAS Arizona. J Exp Sci Environ Epidemiol. 1999;9:446–55.

    Article  CAS  Google Scholar 

  9. United States Environmental Protection Agency. Radionuclides Rule. Drinking Water Requirements for States and Public Water Systems, 2016. Available from:

  10. United States Environmental Protection Agency. Arsenic and Clarifications to Compliance and New Source Contaminants Monitoring: A Quick Reference Guide. 2001. Available from:

  11. World Health Organization. Arsenic. 2022. Available from:

  12. World Health Organization. Uranium in drinking-water: background document for development of WHO guidelines for drinking-water quality. 2004; No. WHO/SDE/WSH/03.04/118.

  13. Dieter CA, Maupin MA, Caldwell RR, Harris MA, Ivahnenko TI, Lovelace JK, et al. Estimated use of water in the United States in 2015. US Geological Survey Circular 1441 2018; 76.

  14. Johnson TD, Belitz K, Lombard MA. Estimating domestic well locations and populations served in the contiguous U.S. for years 2000 and 2010. Sci Total Environ. 2019;687:1261–73.

    Article  CAS  PubMed  Google Scholar 

  15. Ablah E, Marrow MW, Brown J, Honn A. Analysis of Kansas Water Well Policies and Proposal of Nonpublic Household Water Well Recommendations. Environ Health Perspect. 2020;128:025001.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Karagas MR, Stukel TA, Tosteson TD. Assessment of cancer risk and environmental levels of arsenic in New Hampshire. Int J Hyg Environ Health. 2002;205:85–94.

    Article  CAS  PubMed  Google Scholar 

  17. Zheng Y, Flanagan SV. The case for universal screening of private well water quality in the US and testing requirements to achieve it: Evidence from arsenic. Environ Health Perspect. 2017;125:085002.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Kurzius-Spencer M, Burgess JL, Harris RB, Hartz V, Roberge J, Huang S, et al. Contribution of diet to aggregate arsenic exposures—an analysis across populations. J Exp Sci Environ Epidemiol. 2014;24:156–62.

    Article  CAS  Google Scholar 

  19. Xue J, Zartarian V, Wang SW, Liu SV, Georgopoulos P. Probabilistic modeling of dietary arsenic exposure and dose and evaluation with 2003–2004 NHANES data. Environ Health Perspect. 2010;118:345–50.

    Article  CAS  PubMed  Google Scholar 

  20. Centers for Disease Control and Prevention. Arsenic Factsheet. National Biomonitoring Program. 2017. Available from:

  21. Ayotte JD, Medalie L, Qi SL, Backer LC, Nolan BT. Estimating the high-arsenic domestic-well population in the conterminous United States. Environ Sci Technol. 2017;51:12443–54.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Lombard MA, Bryan MS, Jones DK, Bulka C, Bradley PM, Backer LC, et al. Machine learning models of arsenic in private wells throughout the conterminous United States as a tool for exposure assessment in human health studies. Environ Sci Technol. 2021;

  23. Spaur M, Lombard MA, Ayotte JD, Harvey DE, Bostick BC, Navas-Acien A, et al. Associations between private well water and community water supply arsenic concentrations in the conterminous United States. Sci Total Environ. 2021;787:147555.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Nigra AE, Chen Q, Chillrud SN, Wang L, Harvey D, Mailloux B, et al. Inequalities in public water arsenic concentrations in counties and community water systems across the United States, 2006–2011. Environ Health Perspect. 2020;128:127001;

  25. Robinson CS, & Gott GB. Uranium Deposits of the Black Hills South Dakota and Wyoming. Vol. 723. Unites States Department of the Interior Geological Survey, 1958.

  26. United States Nuclear Regulatory Commission. In Situ Leach Mining Rules Question and Answer Sheet. Available from:

  27. Lewis J, Hoover J, MacKenzie D. Mining and environmental health disparities in Native American communities. Curr Environ Health Rep. 2017;4:130–41.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Hoover J, Gonzales M, Shuey C, Barney Y, & Lewis J. Elevated arsenic and uranium concentrations in unregulated water sources on the Navajo Nation, USA. Exp Health 2017;9:113–24.

  29. Ayotte JD, Gronberg JM, & Apodaca LE. Trace elements and radon in groundwater across the United States, 1992-2003. Reston, VA, USA: US Department of the Interior, US Geological Survey; 2011.

  30. Ravalli F, Yuanzhi Yu Y, Bostick BC, Chillrud SN, Schilling K, Basu A, et al. Sociodemographic inequalities in uranium and other metals in community water systems across the US, 2006–2011. Lancet Planetary Health. 2022;6:e320–e330.

  31. Balazs CL, Ray I. The drinking water disparities framework: on the origins and persistence of inequities in exposure. Am J Public Health. 2014;104:603–11.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Martinez-Morata I, Bostick BC, Conroy-Ben O, Duncan DT, Jones MR, Spaur M, et al. Nationwide geospatial analysis of county racial and ethnic composition and public drinking water arsenic and uranium. Nat Commun. 2022;13:7461.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. North KE, Howard BV, Welty TK, Best LG, Lee ET, Yeh JL, et al. Genetic and environmental contributions to cardiovascular disease risk in American Indians: the Strong Heart Family Study. Am J Epidemiol. 2003;157:303–14.

    Article  PubMed  Google Scholar 

  34. Bild DE, Bluemke DA, Burke GL, Detrano R, Diez Roux AV, Folsom AR, et al. Multi-ethnic study of atherosclerosis: objectives and design. Am J Epidemiol. 2002;156:871–81.

    Article  PubMed  Google Scholar 

  35. R Core Team. R: A language and environment for statistical computing 4.1.0. R Foundation for Statistical Computing, Vienna, Austria, 2021.

  36. Scheer J, Findenig S, Goessler W, Francesconi KA, Howard B, Umans JG, et al. Arsenic species and selected metals in human urine: validation of HPLC/ICPMS and ICPMS procedures for a long-term population-based epidemiological study. Analytical. Methods. 2012;4:406–13.

    CAS  Google Scholar 

  37. Centers for Disease Control and Prevention. Data Sources and Data Analysis: Blood, serum, and urine samples from NHANES. National Report on Human Exposure to Environmental Chemicals, 2022. Available from:

  38. Nigra AE. Inequalities in public water arsenic concentrations in counties and community water systems across the United States, 2006-2011. 2020. Available from:

  39. Lombard MA. Data used to model and map arsenic concentration exceedances in private wells throughout the conterminous United States for human health studies: U.S. Geological Survey data release. 2021. Available from:

  40. United States Geological Survey. National Uranium Resource Evaluation (NURE) Hydrogeochemical and Stream Sediment Reconnaissance data, 2004. Available from

  41. Pebesma E. Simple Features for R: Standardized Support for Spatial Vector Data. R J. 2018;10:439–46.

    Article  Google Scholar 

  42. South Dakota Association of Rural Water Systems. Rural water systems of South Dakota, 2021. Available from:

  43. Maryland Department of the Environment. Drinking Water Watch. Drinking Water Branch: City of Baltimore. Available from:

  44. Baltimore City of Public Works. Baltimore DPW: The Region’s Water Supplier, 2018. Available from:

  45. van Gerwen M, Alpert N, Lieberman-Cribbin W, Cooke P, Ziadkhanpour K, Liu B, et al. Association between uranium exposure and thyroid health: a National Health and Nutrition Examination Survey analysis and ecological study. Int J Environ Res Public Health. 2020;17:712.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Nigra AE, Olmedo P, Grau-Perez M, O’Leary R, O’Leary M, Fretts AM, et al. Dietary determinants of inorganic arsenic exposure in the Strong Heart Family Study. Environ Res. 2019;177:108616.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Jones MR, Tellez-Plaza M, Vaidya D, Grau-Perez M, Post WS, Kaufman JD, et al. Ethnic, geographic and dietary differences in arsenic exposure in the multi-ethnic study of atherosclerosis (MESA). J Exp Sci Environ Epidemiol. 2019;29:310–22.

    Article  CAS  Google Scholar 

  48. Bates D, Mächler M, Bolker B, Walker S. Fitting Linear Mixed-Effects Models Using lme4. J Stat Softw. 2015;67:1–48.

    Article  Google Scholar 

  49. Barton K. MuMIn: multi-model inference. R package version 0.13.17, 2010.

  50. Viechtbauer W. Conducting meta-analyses in R with the metafor package. J Stat Softw. 2010;36:1–48.

    Article  Google Scholar 

  51. Balduzzi S, Rücker G, & Schwarzer G. How to perform a meta-analysis with R: a practical tutorial. Evidence-Based Mental Health. 2019;22:153–60.

  52. United States Environmental Protection Agency. Exposure Assessment Tools by Routes - Ingestion. In: EPA ExpoBox, 2022. Available from:

  53. Sebastian RS, Wilkinson C, & Goldman JD. Drinking water intake in the US: what we eat in America, NHANES 2005–2008: Beltsville, MD, USA, 2011.

  54. Abuawad A, Goldsmith J, Herbstman JB, Parvez F, Islam T, LoIacono N, et al. Urine Dilution Correction Methods Utilizing Urine Creatinine or Specific Gravity in Arsenic Analyses: Comparisons to Blood and Water Arsenic in the FACT and FOX Studies in Bangladesh. Water. 2022;14:1477.

    Article  CAS  Google Scholar 

  55. Wood S. Generalized Additive Model Selection. R Documentation, 2022. Available from:

  56. Zuur AF, Ieno EN, Walker NJ, Saveliev AA, Smith GM. Mixed effects models and extensions in ecology with R. New York: Springer; 2009.

    Book  Google Scholar 

  57. Hunsicker ME, Kappel CV, Selkoe KA, Halpern BS, Scarborough C, Mease L, et al. Characterizing driver–response relationships in marine pelagic ecosystems for improved ocean management. Ecol Appl. 2016;26:651–63.

    Article  PubMed  Google Scholar 

  58. Mantha M, Yeary E, Trent J, Creed PA, Kubachka K, Hanley T, et al. Estimating inorganic arsenic exposure from US rice and total water intakes. Environ health Perspect. 2017;125:057005.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Jones MR, Tellez-Plaza M, Vaidya D, Grau M, Francesconi KA, Goessler W, et al. Estimation of inorganic arsenic exposure in populations with frequent seafood intake: evidence from MESA and NHANES. Am J Epidemiol. 2016;184:590–602.

    Article  PubMed  PubMed Central  Google Scholar 

  60. New Hampshire Department of Environmental Services. Review of the Drinking Water Maximum Contaminant Level (MCL) and Ambient Groundwater Quality Standard (AGQS) for Arsenic, 2018;1–71.

  61. New Jersey Department of Environmental Protection. N.J.A.C. 7:10 Safe Drinking Water Act Rules, 2020. Available from:

  62. Nigra AE, Cazacu-De Luca, A, & Navas-Acien A. Socioeconomic vulnerability and public water arsenic concentrations across the US. Environ Pollut. 2022:120113.

  63. Pontius FW, Brown KG, Chen CJ. Health implications of arsenic in drinking water. J‐Am Water Works Assoc. 1994;86:52–63.

    Article  CAS  Google Scholar 

  64. Buchet JP, Lauwerys R, Roels H. Comparison of the urinary excretion of arsenic metabolites after a single oral dose of sodium arsenite, monomethylarsonate, or dimethylarsinate in man. Int Arch Occup Environ health. 1981;48:71–9.

    Article  CAS  PubMed  Google Scholar 

  65. Leggett RW, Harrison JD. Fractional absorption of ingested uranium in humans. Health Phys. 1995;68:484–98.

    Article  CAS  PubMed  Google Scholar 

  66. Brugge D, deLemos JL, Oldmixon B. Exposure pathways and health effects associated with chemical and radiological toxicity of natural uranium: a review. Rev Environ health. 2005;20:177–94.

    Article  CAS  PubMed  Google Scholar 

  67. Konietzka R. Gastrointestinal absorption of uranium compounds–A review. Regul Toxicol Pharmacol. 2015;71:125–33.

    Article  CAS  PubMed  Google Scholar 

  68. Centers for Disease Control and Prevention. Public Water Systems, 2021. Available from:

  69. Navas-Acien A, Umans JG, Howard BV, Goessler W, Francesconi KA, Crainiceanu CM, et al. Urine arsenic concentrations and species excretion patterns in American Indian communities over a 10-year period: the Strong Heart Study. Environ Health Perspect. 2009;117:1428–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Nigra AE, Sanchez TR, Nachman KE, Harvey DE, Chillrud SN, Graziano JH, et al. The effect of the Environmental Protection Agency maximum contaminant level on arsenic exposure in the USA from 2003 to 2014: an analysis of the National Health and Nutrition Examination Survey (NHANES). Lancet Public Health. 2017;2:e513–e521.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Ayotte JD, Belaval M, Olson SA, Burow KR, Flanagan SM, Hinkle SR, et al. Factors affecting temporal variability of arsenic in groundwater used for drinking water supply in the United States. Sci Total Environ. 2015;505:1370–9.

    Article  CAS  PubMed  Google Scholar 

  72. Levitt JP, Degnan JR, Flanagan SM, Jurgens BC. Arsenic variability and groundwater age in three water supply wells in southeast New Hampshire. Geosci Front. 2019;10:1669–83.

    Article  CAS  Google Scholar 

  73. Croghan CA & Egeghy PP. Methods of dealing with values below the limit of detection using SAS. Southeastern SAS User Group; St. Petersburg, FL, 2003:22–24.

  74. New Jersey Department of Environmental Protection. Policy Directive 2003-06, Subject: Drinking Water Standard for Arsenic, 2003. Available from:,billion)%2C%20effective%20in%202006.

Download references


This study was supported by NIEHS grants P42ES033719 and P30ES009089, R01ES028758, R01ES032638 and by the NIH Office Of The Director and National Institute Of Dental & Craniofacial Research (DP5OD031849). Research reported in this publication was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development under grant number P2CHD058486, awarded to the Columbia Population Research Center. MS is also supported by NIEHS grant F31ES034284. We would like to acknowledge Joseph Ayotte for his contributions to this study. The Strong Heart Study has been funded in whole or in part with federal funds from the National Heart, Lung, and Blood Institute, National Institute of Health, Department of Health and Human Services, under contract numbers 75N92019D00027, 75N92019D00028, 75N92019D00029, and 75N92019D00030. The study was previously supported by research grants: R01HL109315, R01HL109301, R01HL109284, R01HL109282, and R01HL109319 and by cooperative agreements: U01HL41642, U01HL41652, U01HL41654, U01HL65520, U01HL65521, R01HL090863, R01ES025216, and R01ES021367. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the Indian Health Service (IHS). The Multi-Ethnic Study of Atherosclerosis (MESA) was supported by contracts 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163, 75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168 and N01-HC-95169 from the National Heart, Lung, and Blood Institute, and by grants UL1-TR-000040, UL1-TR-001079, and UL1-TR-001420 from the National Center for Advancing Translational Sciences (NCATS). The authors thank the other investigators, the staff, and the participants of the MESA study for their valuable contributions. A full list of participating MESA investigators and institutions can be found at This paper has been reviewed and approved by the MESA Publications and Presentations Committee. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Author information

Authors and Affiliations



RAG, KS, VI, OB, and CI conducted the urine arsenic and uranium measurements. MS, MG-F, WL-C, CH, and AEN contributed data preparation, management, and statistical code. MAL, BCB, QC, AN-A, and AEN contributed to conceptualization and writing-review & editing. RAG and KS contributed to writing-original draft & editing. KP, AB, and TS contributed to conceptualization. MS conducted writing-original draft & editing, visualization, and statistical analysis.

Corresponding author

Correspondence to Maya Spaur.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval

This research was approved by the Institutional Review Boards at the participating institutions, and written informed consent was given by all participants. This paper has been cleared by the respective Tribal Research Review Boards and area Indian Health Service IRBs for the SHFS and by the Publications and Presentations Committee for MESA.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information



Water assignment

For participants in New York, we matched residential zip code to the corresponding community water system (CWS) based on town name (all New York City, NYC, residents were assigned to the NYC Public Water System, PWSID NY7003493). While CWS arsenic (As) data was available for Multi-Ethnic Study of Atherosclerosis (MESA) participants residing in New York City and nearby, corresponding CWS uranium (U) data were not available. We assigned the 2000–2011 CWS U estimate for a neighboring water system (Westchester County Water District #1, CWS U = 0.63 µg/L30) to New York City participants, based on personal communication from the Westchester County Department of Health (Alex Sciacchitano, oral communication, November 2022) that the Water District has the same aqueduct/source water supply as New York City.

Though Maryland did not provide adequate data to the US Environmental Protection Agency’s (EPA’s) Six Year Review of Contaminant Occurrence Database, water quality data for Baltimore City are publicly available online [43]. We assigned participants residing in Baltimore City, and areas of the surrounding counties that are expected to be served by the City of Baltimore CWS [44], to the As estimate for the City of Baltimore CWS (concentration was <reporting level so imputed as 0.35 µg/L, according to previously published methods) [24, 43]. There were no U data reported for the City of Baltimore CWS

Sensitivity Analyses

We performed several sensitivity analyses. To make our findings available to inform future risk assessments, we repeated our analyses after transforming assigned water As and U into estimated average daily dose using a standard exposure assessment framework used by the US EPA [52]. We calculated average daily dose (mg/kg body weight (BW)-day) of As and U consumed from tap water using the following equation from the exposure assessment framework:

$${\it{Dose}} = \left( {{\it{Concentration}} \ast {\it{Intake}}\,{\it{Rate}}} \right)/{\it{Bodyweight}}$$

We used standard intake rate estimates of water consumption in US populations surveyed for NHANES [53]. The dose intake rates (cups/day) for females were: 1.6, 2.5, 2.7, and 2.6, aged 12–19 years, 20–39 years, 40–59 years, and ≥60 years, respectively [53]. The dose intake rates (cups/day) for males were: 2.3, 2.9, 2.8, and 2.1, aged 12–19 years, 20–39 years, 40–59 years, and ≥60 years, respectively.

Finally, we compared findings using area-weighted ZCTA-level CWS As and U estimates (instead of population-weighted ZCTA-level CWS estimates), also with similar results. Area weights were generated for each CWS within a ZCTA using the area of overlap between CWS service areas and ZCTAs. Area weights were applied using the “weighted.mean” function in R to create area-weighted average estimates of CWS As and U grouped at the ZCTA level.

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Spaur, M., Glabonjat, R.A., Schilling, K. et al. Contribution of arsenic and uranium in private wells and community water systems to urinary biomarkers in US adults: The Strong Heart Study and the Multi-Ethnic Study of Atherosclerosis. J Expo Sci Environ Epidemiol (2023).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI:



Quick links