IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i23p4672-d290205.html
   My bibliography  Save this article

Effects of Personal Exposures to Micro- and Nano-Particulate Matter, Black Carbon, Particle-Bound Polycyclic Aromatic Hydrocarbons, and Carbon Monoxide on Heart Rate Variability in a Panel of Healthy Older Subjects

Author

Listed:
  • Chin-Sheng Tang

    (Department of Public Health, College of Medicine, Fu Jen Catholic University, New Taipei City 24205, Taiwan)

  • Kai-Jen Chuang

    (School of Public Health, College of Public Health, Taipei Medical University, Taipei 11031, Taiwan
    Department of Public Health, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan)

  • Ta-Yuan Chang

    (Department of Occupational Safety and Health, College of Public Health, China Medical University, Taichung 40402, Taiwan)

  • Hsiao-Chi Chuang

    (School of Respiratory Therapy, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
    Cell Physiology and Molecular Image Research Center, Wan Fang Hospital, Taipei Medical University, Taipei 11696, Taiwan
    Division of Pulmonary Medicine, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City 23561, Taiwan)

  • Li-Hsin Chen

    (Department of Public Health, College of Medicine, Fu Jen Catholic University, New Taipei City 24205, Taiwan)

  • Shih-Chun Candice Lung

    (Research Center for Environmental Changes, Academia Sinica, Taipei 11529, Taiwan)

  • Li-Te Chang

    (Department of Environmental Engineering and Science, Feng Chia University, Taichung 40724, Taiwan)

Abstract

As a non-invasive method, heart rate variability (HRV) has been widely used to study cardiovascular autonomous control. Environmental epidemiological studies indicated that the increase in an average concentration of particulate matter (PM) would result in a decrease in HRV, which was related to the increase of cardiovascular mortality in patients with myocardial infarction and the general population. With rapid economic and social development in Asia, how air pollutants, such as PM of different sizes and their components, affect the cardiovascular health of older people, still need to be further explored. The current study includes a 72 h personal exposure monitoring of seven healthy older people who lived in the Taipei metropolitan area. Mobile equipment, a portable electrocardiogram recorder, and the generalized additive mixed model (GAMM) were adopted to evaluate how HRV indices were affected by size-fractionated PM, particle-bound polycyclic aromatic hydrocarbons ( p -PAHs), black carbon (BC), and carbon monoxide (CO). Other related confounding factors, such as age, sex, body mass index (BMI), temperature, relative humidity (RH), time, and monitoring week were controlled by fixed effects of the GAMM. Statistical analyses of multi-pollutant models showed that PM 2.5–10 , PM 1 , and nanoparticle (NP) could cause heart rate (HR), time-domain indices, and frequency-domain indices to rise; PM 1–2.5 and BC would cause the frequency-domain index to rise; p -PAHs would cause HR to rise, and CO would cause time-domain index and frequency-domain index to decline. In addition, the moving average time all fell after one hour and might appear at 8 h in HRVs’ largest percentage change caused by each pollutant, results of which suggested that size-fractionated PM, p -PAHs, BC, and CO exposures have delayed effects on HRVs. In conclusion, the results of the study showed that the increase in personal pollutant exposure would affect cardiac autonomic control function of healthy older residents in metropolitan areas, and the susceptibility of cardiovascular effects was higher than that of healthy young people. Since the small sample size would limit the generalizability of this study, more studies with larger scale are warranted to better understand the HRV effects of simultaneous PM and other pollution exposures for subpopulation groups.

Suggested Citation

  • Chin-Sheng Tang & Kai-Jen Chuang & Ta-Yuan Chang & Hsiao-Chi Chuang & Li-Hsin Chen & Shih-Chun Candice Lung & Li-Te Chang, 2019. "Effects of Personal Exposures to Micro- and Nano-Particulate Matter, Black Carbon, Particle-Bound Polycyclic Aromatic Hydrocarbons, and Carbon Monoxide on Heart Rate Variability in a Panel of Healthy ," IJERPH, MDPI, vol. 16(23), pages 1-25, November.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:23:p:4672-:d:290205
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/23/4672/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/16/23/4672/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Simon N. Wood, 2011. "Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(1), pages 3-36, January.
    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. Diana Saadi & Emanuel Tirosh & Izhak Schnell, 2021. "The Relationship between City Size and Carbon Monoxide (CO) Concentration and Their Effect on Heart Rate Variability (HRV)," IJERPH, MDPI, vol. 18(2), pages 1-13, January.
    2. Borut Jereb & Brigita Gajšek & Gregor Šipek & Špela Kovše & Matevz Obrecht, 2021. "Traffic Density-Related Black Carbon Distribution: Impact of Wind in a Basin Town," IJERPH, MDPI, vol. 18(12), pages 1-17, June.
    3. Ismail Anil & Omar Alagha, 2020. "Source Apportionment of Ambient Black Carbon during the COVID-19 Lockdown," IJERPH, MDPI, vol. 17(23), pages 1-22, December.

    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. Gerhard Tutz & Moritz Berger, 2018. "Tree-structured modelling of categorical predictors in generalized additive regression," 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(3), pages 737-758, September.
    2. Tommaso Luzzati & Angela Parenti & Tommaso Rughi, 2017. "Spatial error regressions for testing the Cancer-EKC," Discussion Papers 2017/218, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    3. Davide Fiaschi & Andrea Mario Lavezzi & Angela Parenti, 2020. "Deep and Proximate Determinants of the World Income Distribution," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 66(3), pages 677-710, September.
    4. Conor Waldock & Bernhard Wegscheider & Dario Josi & Bárbara Borges Calegari & Jakob Brodersen & Luiz Jardim de Queiroz & Ole Seehausen, 2024. "Deconstructing the geography of human impacts on species’ natural distribution," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    5. Longhi, Christian & Musolesi, Antonio & Baumont, Catherine, 2014. "Modeling structural change in the European metropolitan areas during the process of economic integration," Economic Modelling, Elsevier, vol. 37(C), pages 395-407.
    6. Sihvonen, Markus, 2021. "Yield curve momentum," Research Discussion Papers 15/2021, Bank of Finland.
    7. Roberto Basile & Luigi Benfratello & Davide Castellani, 2012. "Geoadditive models for regional count data: an application to industrial location," ERSA conference papers ersa12p83, European Regional Science Association.
    8. Dillon T. Fogarty & Caleb P. Roberts & Daniel R. Uden & Victoria M. Donovan & Craig R. Allen & David E. Naugle & Matthew O. Jones & Brady W. Allred & Dirac Twidwell, 2020. "Woody Plant Encroachment and the Sustainability of Priority Conservation Areas," Sustainability, MDPI, vol. 12(20), pages 1-15, October.
    9. E. Zanini & E. Eastoe & M. J. Jones & D. Randell & P. Jonathan, 2020. "Flexible covariate representations for extremes," Environmetrics, John Wiley & Sons, Ltd., vol. 31(5), August.
    10. Daniel Melser & Robert J. Hill, 2019. "Residential Real Estate, Risk, Return and Diversification: Some Empirical Evidence," The Journal of Real Estate Finance and Economics, Springer, vol. 59(1), pages 111-146, July.
    11. Ji, Shujuan & Liu, Xiaojie & Wang, Yuanqing, 2024. "The role of road infrastructures in the usage of bikeshare and private bicycle," Transport Policy, Elsevier, vol. 149(C), pages 234-246.
    12. Maciej Berȩsewicz & Dagmara Nikulin, 2021. "Estimation of the size of informal employment based on administrative records with non‐ignorable selection mechanism," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 667-690, June.
    13. repec:grz:wpaper:2014-05 is not listed on IDEAS
    14. Cathrine Ulla Jensen & Toke Emil Panduro, 2016. "PanJen: A test for functional form with continuous variables," IFRO Working Paper 2016/08, University of Copenhagen, Department of Food and Resource Economics.
    15. Ronald E. Gangnon & Natasha K. Stout & Oguzhan Alagoz & John M. Hampton & Brian L. Sprague & Amy Trentham-Dietz, 2018. "Contribution of Breast Cancer to Overall Mortality for US Women," Medical Decision Making, , vol. 38(1_suppl), pages 24-31, April.
    16. Yuko Araki & Atsushi Kawaguchi & Fumio Yamashita, 2013. "Regularized logistic discrimination with basis expansions for the early detection of Alzheimer’s disease based on three-dimensional MRI data," 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. 7(1), pages 109-119, March.
    17. Weishampel, Anthony & Staicu, Ana-Maria & Rand, William, 2023. "Classification of social media users with generalized functional data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    18. Megan K. Jennings & Emily Haeuser & Diane Foote & Rebecca L. Lewison & Erin Conlisk, 2020. "Planning for Dynamic Connectivity: Operationalizing Robust Decision-Making and Prioritization Across Landscapes Experiencing Climate and Land-Use Change," Land, MDPI, vol. 9(10), pages 1-18, September.
    19. Robert J. Hill & Alicia N. Rambaldi & Michael Scholz, 2021. "Higher frequency hedonic property price indices: a state-space approach," Empirical Economics, Springer, vol. 61(1), pages 417-441, July.
    20. Adam R. Pines & Bart Larsen & Zaixu Cui & Valerie J. Sydnor & Maxwell A. Bertolero & Azeez Adebimpe & Aaron F. Alexander-Bloch & Christos Davatzikos & Damien A. Fair & Ruben C. Gur & Raquel E. Gur & H, 2022. "Dissociable multi-scale patterns of development in personalized brain networks," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    21. Marra, Giampiero & Wood, Simon N., 2011. "Practical variable selection for generalized additive models," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2372-2387, July.

    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:16:y:2019:i:23:p:4672-:d:290205. 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.