IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i16p5839-d398106.html
   My bibliography  Save this article

Associations Between School Characteristics and Classroom Radon Concentrations in Utah’s Public Schools: A Project Completed by University Environmental Health Students

Author

Listed:
  • Elizabeth A. Davis

    (Department of Public Health, Brigham Young University, Provo, UT 84602, USA)

  • Judy Y. Ou

    (Cancer Control and Population Sciences, Huntsman Cancer Institute at the University of Utah School of Medicine, Salt Lake City, UT 84112, USA)

  • Cheyenne Chausow

    (Department of Public Health, Brigham Young University, Provo, UT 84602, USA)

  • Marco A. Verdeja

    (Department of Public Health, Brigham Young University, Provo, UT 84602, USA)

  • Eleanor Divver

    (Radon Program, Utah Department of Environmental Quality, Salt Lake City, UT 84116, USA)

  • James D. Johnston

    (Department of Public Health, Brigham Young University, Provo, UT 84602, USA)

  • John D. Beard

    (Department of Public Health, Brigham Young University, Provo, UT 84602, USA)

Abstract

Radon (²²²Rn), a radioactive gas, is the second leading cause of lung cancer deaths in the U.S. Classroom radon concentrations in public schools in our target area had never been measured or had not been measured in many years. We had university students, primarily enrolled in environmental health courses, measure radon concentrations in 2289 classrooms in 66 of Utah’s public schools and identify school characteristics associated with classroom radon concentrations. The geometric mean (GM) classroom radon concentration was 31.39 (95% confidence interval (CI): 27.16, 36.28) Bq/m 3 (GM: 0.85; 95% CI: 0.72, 0.98 pCi/L). Thirty-seven (2%) classrooms in 13 (20%) schools had radon concentrations at or above the U.S. Environmental Protection Agency’s (EPA) recommended action level of 148 Bq/m 3 (4.0 pCi/L). Number of classrooms had a u-shaped association with classroom radon concentrations. The year the heating, ventilation, and air conditioning (HVAC) system was installed was inversely associated with having classroom radon concentrations at or above the EPA’s recommended action level. Number of classrooms and number of students had u-shaped associations with having classroom radon concentrations at or above the EPA’s recommended action level. Classroom radon concentrations decreased when schools’ HVAC systems were on. Replacing HVAC systems and turning/keeping them on may be effective radon mitigation strategies to prevent radon-associated lung cancer, especially for small and large schools.

Suggested Citation

  • Elizabeth A. Davis & Judy Y. Ou & Cheyenne Chausow & Marco A. Verdeja & Eleanor Divver & James D. Johnston & John D. Beard, 2020. "Associations Between School Characteristics and Classroom Radon Concentrations in Utah’s Public Schools: A Project Completed by University Environmental Health Students," IJERPH, MDPI, vol. 17(16), pages 1-17, August.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:16:p:5839-:d:398106
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/16/5839/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/16/5839/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wei Pan, 2001. "Akaike's Information Criterion in Generalized Estimating Equations," Biometrics, The International Biometric Society, vol. 57(1), pages 120-125, March.
    2. Kelsey Gordon & Paul D. Terry & Xingxing Liu & Tiffany Harris & Don Vowell & Bud Yard & Jiangang Chen, 2018. "Radon in Schools: A Brief Review of State Laws and Regulations in the United States," IJERPH, MDPI, vol. 15(10), pages 1-9, September.
    Full references (including those not matched with items on IDEAS)

    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. Wei Pan, 2001. "Model Selection in Estimating Equations," Biometrics, The International Biometric Society, vol. 57(2), pages 529-534, June.
    2. Vens, Maren & Ziegler, Andreas, 2012. "Generalized estimating equations and regression diagnostics for longitudinal controlled clinical trials: A case study," Computational Statistics & Data Analysis, Elsevier, vol. 56(5), pages 1232-1242.
    3. Michael S. Rendall & Bonnie Ghosh-Dastidar & Margaret M. Weden & Zafar Nazarov, 2011. "Multiple Imputation for Combined-Survey Estimation With Incomplete Regressors In One But Not Both Surveys," Working Papers WR-887-1, RAND Corporation.
    4. Katrina N. Burns & Kan Sun & Julius N. Fobil & Richard L. Neitzel, 2016. "Heart Rate, Stress, and Occupational Noise Exposure among Electronic Waste Recycling Workers," IJERPH, MDPI, vol. 13(1), pages 1-16, January.
    5. Song Guo & Feng Ling & Juan Hou & Jinna Wang & Guiming Fu & Zhenyu Gong, 2014. "Mosquito Surveillance Revealed Lagged Effects of Mosquito Abundance on Mosquito-Borne Disease Transmission: A Retrospective Study in Zhejiang, China," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-8, November.
    6. Marc-Andreas Muendler & Sascha O. Becker, 2010. "Margins of Multinational Labor Substitution," American Economic Review, American Economic Association, vol. 100(5), pages 1999-2030, December.
    7. Laura Neumeyer & Anna Gründler & Anna-Luisa Stöber, 2023. "Don’t Worry, Be Happy—Does the CEO’s Personality Mitigate the Negative Effect of Financial Constraints on Employee Satisfaction?," Schmalenbach Journal of Business Research, Springer, vol. 75(1), pages 71-98, March.
    8. Amy Hinsley & William J Sutherland & Alison Johnston, 2017. "Men ask more questions than women at a scientific conference," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-14, October.
    9. Geraldo F Oliveira & Teresinha R R Oliveira & Adauto T Ikejiri & Mariela P Andraus & Tais F Galvao & Marcus T Silva & Maurício G Pereira, 2014. "Prevalence of Hypertension and Associated Factors in an Indigenous Community of Central Brazil: A Population-Based Study," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-6, January.
    10. Li, Gaorong & Lian, Heng & Feng, Sanying & Zhu, Lixing, 2013. "Automatic variable selection for longitudinal generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 61(C), pages 174-186.
    11. Beth A. Reboussin & Edward H. Ip & Mark Wolfson, 2008. "Locally dependent latent class models with covariates: an application to under‐age drinking in the USA," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(4), pages 877-897, October.
    12. Peng, Cheng & Yang, Yihe & Zhou, Jie & Pan, Jianxin, 2022. "Latent Gaussian copula models for longitudinal binary data," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    13. Sandy Shergill & Lindsay Forsman-Phillips & Anne-Marie Nicol, 2021. "Radon in Schools: A Review of Radon Testing Efforts in Canadian Schools," IJERPH, MDPI, vol. 18(10), pages 1-9, May.
    14. Mark Rooij, 2018. "Transitional modeling of experimental longitudinal data with missing values," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(1), pages 107-130, March.
    15. Tessa Recendes & Federico Aime & Aaron D. Hill & Oleg V. Petrenko, 2022. "Bargaining your way to success: The effect of Machiavellian chief executive officers on firm costs," Strategic Management Journal, Wiley Blackwell, vol. 43(10), pages 2012-2041, October.
    16. Bastian Rake, 2017. "Determinants of pharmaceutical innovation: the role of technological opportunities revisited," Journal of Evolutionary Economics, Springer, vol. 27(4), pages 691-727, September.
    17. Muhammad Adeel & Hung-Chou Chen & Bor-Shing Lin & Chien-Hung Lai & Chun-Wei Wu & Jiunn-Horng Kang & Jian-Chiun Liou & Chih-Wei Peng, 2022. "Oxygen Consumption (VO 2 ) and Surface Electromyography (sEMG) during Moderate-Strength Training Exercises," IJERPH, MDPI, vol. 19(4), pages 1-14, February.
    18. Aristides dos Santos, Anderson Moreira & Perelman, Julian & Jacinto, Paulo de Andrade & Tejada, Cesar Augusto Oviedo & Barros, Aluísio J.D. & Bertoldi, Andréa D. & Matijasevich, Alicia & Santos, Iná S, 2019. "Income-related inequality and inequity in children’s health care: A longitudinal analysis using data from Brazil," Social Science & Medicine, Elsevier, vol. 224(C), pages 127-137.
    19. Fischer, Caroline & Schott, Carina, 2020. "Why People Enter and Stay in Public Service Careers: The Role of Parental Socialization and an Interest in Politics," OSF Preprints yb8e3, Center for Open Science.
    20. Yuvraj Sunecher & Naushad Mamode Khan & Miroslav M. Ristić & Vandna Jowaheer, 2019. "BINAR(1) negative binomial model for bivariate non-stationary time series with different over-dispersion indices," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(4), pages 625-653, December.

    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:17:y:2020:i:16:p:5839-:d:398106. 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.