Data-Driven Environmental Health: Unraveling Particulate Matter Trends with Biometric Signals

Main Article Content

Bharana Ashen Fernando Shawhin Talebi Lakitha Wijeratne John Waczak Vinu Sooriyaarachchi Shisir Ruwali Prabuddha Hathurusinghe David J. Lary John Sadler Tatiana Lary Matthew Lary Adam Aker

Abstract

Human physiology is known to react to various environmental stimuli over different time frames. Prolonged exposure to elements such as heat, air pollution, and volatile organic compounds negatively affects health, as established in previous research. Our earlier work demonstrated that autonomic responses of the human body, recorded through biometric sensors on a single individual, could empirically predict levels of inhalable particulate matter in their immediate environment. This current study extends this finding to observations from multiple participants. Subjects cycled on stationary bikes outdoors, equipped with a range of biometric sensors, while environmental sensors simultaneously captured data on their surroundings. Using this expanded data set, machine learning models achieved a high degree of accuracy (R2=0.97) in predicting concentrations of particulate matter (PM2.5) using a few readily available biometric features, including skin temperature, heart rate, and respiration rate. This research underscores the importance of physiological responses as markers of exposure to particulate matter, laying the foundation for the use of biometric data in environmental health surveillance and real-time pollution assessment.

Keywords: particulate matter, autonomic responses, machine learning

Article Details

How to Cite
FERNANDO, Bharana Ashen et al. Data-Driven Environmental Health: Unraveling Particulate Matter Trends with Biometric Signals. Medical Research Archives, [S.l.], v. 12, n. 1, feb. 2024. ISSN 2375-1924. Available at: <https://esmed.org/MRA/mra/article/view/4899>. Date accessed: 24 feb. 2024. doi: https://doi.org/10.18103/mra.v12i1.4899.
Section
Research Articles

References

[1] K. A. Miller, D. S. Siscovick, L. Sheppard, K. Shepherd, J. H. Sullivan, G. L. Anderson, and J. D. Kaufman, “Long-term exposure to air pollution and incidence of cardiovascular events in women.,” The New England journal of medicine, vol. 356 5, pp. 447–58, 2007.
[2] J. O. Anderson, J. G. Thundiyil, and A. I. Stolbach, “Clearing the air: A review of the effects of particulate matter air pollution on human health,” Journal of Medical Toxicology, vol. 8, pp. 166–175, 2012.
[3] J. Hu, X. Xue, M. Xiao, W. Wang, Y. Gao, H. Kan, J. Ge, Z. Cui, and R. Chen, “The acute effects of particulate matter air pollution on ambulatory blood pressure: a multicenter analysis at the hourly level,” Environment International, vol. 157, p. 106859, 2021.
[4] H. Tian, R. Xu, J. G. Canadell, R. L. Thompson, W. Winiwarter, P. Suntharalingam, E. A. Davidson, P. Ciais, R. B. Jackson, G. Janssens-Maenhout, et al., “A comprehensive quantification of global nitrous oxide sources and sinks,” Nature, vol. 586, no. 7828, pp. 248–256, 2020.
[5] R. T. Burnett, H. Chen, M. Szyszkowicz, N. L. Fann, B. Hubbell, C. A. Pope, J. S. Apte, M. Brauer, A. J. Cohen, S. Weichenthal, J. S. Coggins, Q. Di, B. Brunekreef, J. J. Frostad, S. S. Lim, H. dong Kan, K. D. Walker, G. D. Thurston, R. B. Hayes, C. C. Lim, M. C. Turner, M. Jerrett, D. Krewski, S. M. Gapstur, W. R. Diver, B. Ostro, D. E. Goldberg, D. L. Crouse, R. V. Martin, P. Peters, L. L. Pinault, M. Tjepkema, A. van Donkelaar, P. J. Villeneuve, A. B. Miller, P. Yin, M. Zhou, L. Wang, N. A. H. Janssen, M. Marra, R. W. Atkinson, H. Tsang, T. Q. Thach, J. B. Cannon, R. T. Allen, J. E. Hart, F. Laden, G. Cesaroni, F. Forastiere, G. Weinmayr, A. Jaensch, G. Nagel, H. Concin, and J. V. Spadaro, “Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter,” Proceedings of the National Academy of Sciences of the United States of America, vol. 115, pp. 9592– 9597, 2018.
[6] C. A. Pope, R. T. Burnett, G. D. Thurston, M. J. Thun, E. E. Calle, D. Krewski, and J. Godleski, “Cardiovascular mortality and long-term exposure to particulate air pollution: Epidemiological evidence of general pathophysiological pathways of disease,” Circulation: Journal of the American Heart Association, vol. 109, pp. 71–77, 2003.
[7] S¸ermin Gen¸c, Z. F. Zadeo˘gluları, S. H. Fuss, and K. Genc, “The adverse effects of air pollution on the nervous system,” Journal of Toxicology, vol. 2012, 2012.
[8] A. C. Pope, R. T. Burnett, M. J. Thun, E. E. Calle, D. Krewski, K. Ito, and G. D. Thurston, “Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution.,” JAMA, vol. 287 9, pp. 1132–41, 2002.
[9] S. E. Cleland, L. H. Wyatt, L. Wei, N. Paul, M. L. Serre, J. J. West, S. B. Henderson, and A. G. Rappold, “Short-term exposure to wildfire smoke and pm2.5 and cognitive performance in a brain-training game: A longitudinal study of u.s. adults,” Environmental Health Perspectives,nvol. 130, no. 6, p. 067005, 2022.
[10] Y. Bai, Y. Zhang, J. Zhang, Q. Mu, W. Zhang, M. Butlin, Y. Guo, and X. Wang, “Particulate matter and human health: Toxicological assessment and importance of size and composition of particles for oxidative damage and carcinogenic mechanisms,” Journal of Environmental Science and Health, Part C, vol. 33, pp. 489–520, 2015.
[11] N. L. Strominger, R. J. Demarest, and L. B. Laemle, Noback’s human nervous system, seventh edition structure and function. Humana Press, 2012.
[12] S. Weichenthal, M. Hatzopoulou, and M. S. Goldberg, “Exposure to traffic-related air pollution during physical activity and acute changes in blood pressure, autonomic and micro-vascular function in women: a cross-over study,” Particle and fibre toxicology, vol. 11, no. 1, pp. 1–16, 2014.
[13] X. Xia, H. Qiu, T. Kwok, F. W. Ko, C. L. Man, and K.-F. Ho, “Time course of blood oxygen saturation responding to short-term fine particulate matter among elderly healthy subjects and patients with chronic obstructive pulmonary disease,” Science of The Total Environment, vol. 723, p. 138022, 2020.
[14] S. Talebi, D. J. Lary, L. O. Wijeratne, B. Fernando, T. Lary, M. Lary, J. Sadler, A. Sridhar, J. Waczak, A. Aker, and et al., “Decoding physical and cognitive impacts of particulate matter concentrations at ultra-fine scales,” Sensors, vol. 22, no. 11, p. 4240, 2022.
[15] V. Jurcak, D. Tsuzuki, and I. Dan, “10/20, 10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems,” NeuroImage, vol. 34, p. 1600–1611, Feb 2007.
[16] P. L. Nunez and R. Srinivasan, Electric fields of the brain: the neurophysics of EEG. Oxford University Press, USA, 2006.
[17] P. Welch, “The use of fast fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms,” IEEE Transactions on audio and electroacoustics, vol. 15, no. 2, pp. 70–73, 1967.
[18] T. Chen and C. Guestrin, “Xgboost,” Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016.
[19] S. M. Lundberg and S.-I. Lee, “A unified approach to interpreting model predictions,” in Advances in Neural Information Processing Systems 30 (I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, eds.), pp. 4765–4774, Curran Associates, Inc., 2017.
[20] B. C. Ross, “Mutual information between discrete and continuous data sets,” PLoS ONE, vol. 9, no. 2, 2014.
[21] R. A. Fisher, The Design of Experiments. Edinburgh, Scotland: Oliver and Boyd, 1935. This book discusses the principles of experimental design and the distinction between correlation and causation.
[22] D. J. MacKay, Information Theory, Inference and Learning Algorithms. Cambridge, UK: Cambridge University Press, 2003. The book discusses the application of Occam’s Razor in the context of information theory and statistical modeling.
[23] Y.-N. Sun, W. Qin, J.-H. Hu, H.-W. Xu, and P. Z. Sun, “A causal model-inspired automatic feature-selection method for developing datadriven soft sensors in complex industrial processes,” Engineering, vol. 22, pp. 82–93, 2023.
[24] J. D. Ramsey, K. Zhang, M. Glymour, R. S. Romero, B. Huang, I. EbertUphoff, S. Samarasinghe, E. A. Barnes, and C. Glymour, “Tetrad—a toolbox for causal discovery,” in 8th international workshop on climate informatics, 2018.
[25] Y. Zheng, B. Huang, W. Chen, J. Ramsey, M. Gong, R. Cai, S. Shimizu, P. Spirtes, and K. Zhang, “Causal-learn: Causal discovery in python, arXiv preprint arXiv:2307.16405, 2023.
[26] P. Davies and I. Maconochie, “The relationship between body temperature, heart rate and respiratory rate in children,” Emergency Medicine Journal, vol. 26, no. 9, pp. 641–643, 2009.
[27] W. D. McArdle, F. I. Katch, and V. L. Katch, Exercise Physiology: Nutrition, Energy, and Human Performance. Wolters Kluwer Health, 8 ed., 2015.
[28] L. Sherwood, Human Physiology: From Cells to Systems. Cengage Learning, 9 ed., 2015.
[29] J. T. Cacioppo and L. G. Tassinary, Principles of psychophysiology: Physical, social, and inferential elements. Cambridge University Press, 1990.
[30] W. T. Roth, “Cardiovascular behavioral medicine,” Handbook of Psychophysiology, vol. 2, p. 4, 1984.
[31] A. C. Guyton and J. E. Hall, Textbook of Medical Physiology. Elsevier Saunders, 11 ed., 2006.
[32] S. K. Powers and E. T. Howley, Exercise Physiology: Theory and Application to Fitness and Performance. McGraw-Hill, 8 ed., 2012.
[33] G. J. Tortora and B. Derrickson, Principles of Anatomy and Physiology. John Wiley Sons, 12 ed., 2009.
[34] D. E. Mohrman and L. J. Heller, Cardiovascular Physiology. McGrawHill Education, 8 ed., 2018.
[35] R. D. Brook, B. Franklin, W. Cascio, Y. Hong, G. Howard, M. Lipsett,
R. Luepker, M. Mittleman, J. Samet, S. C. Smith, et al., “Cardiovascular effects of air pollution,” Circulation, vol. 109, no. 21, pp. 2655–2671, 2004.
[36] C. A. Pope III, D. W. Dockery, R. E. Kanner, G. M. Villegas, and J. Schwartz, “Heart rate variability, air pollution, and cardiovascular disease risk,” Air Quality, Atmosphere Health, vol. 113, no. 4, pp. 324– 332, 2006.
[37] J. Lelieveld, A. Haines, and A. Pozzer, “Air pollution and oxidative stress in cardiovascular diseases,” Frontiers in Public Health, vol. 7, p. 307, 2019.
[38] M. Boas, U. Feldt-Rasmussen, and K. M. Main, “Environmental endocrine disruptors: an evolutionary perspective,” The Journal of Clinical Endocrinology Metabolism, vol. 91, no. 6, pp. 2074–2080, 2006.
[39] C. A. Pope III and D. W. Dockery, “Air pollution and heart rate variability,” Circulation, vol. 109, no. 21, pp. e211–e211, 2004.
[40] A. Bhatnagar, “Environmental cardiology: studying mechanistic links between pollution and heart disease,” Circulation research, vol. 99, no. 7, pp. 692–705, 2006.
[41] W. J. Paulus and C. Tschope, “Endothelial dysfunction: a pathophysiologic factor in heart failure,” Circulation, vol. 116, no. 19, pp. 2034–2046, 2007.
[42] R. D. Brook, S. Rajagopalan, C. A. Pope III, J. R. Brook, A. Bhatnagar, A. V. Diez-Roux, F. Holguin, Y. Hong, R. V. Luepker, M. A. Mittleman, et al., “Particulate matter air pollution and cardiovascular disease: An update to the scientific statement from the american heart association,” Circulation, vol. 121, no. 21, pp. 2331–2378, 2010.
[43] J. B. West, Pulmonary Pathophysiology: The Essentials. Lippincott Williams Wilkins, 8 ed., 2012.