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Health effects of concurrent ambient and tobacco smoke-derived particle exposures at low concentrations in children with asthma


Exposure to particulate matter less than 2.5 microns from either ambient pollution (AMB-PM2.5) or secondhand smoke (SHS-PM2.5) have been associated with asthma worsening, but there is little information on effects and relative potency with concurrent exposures. We studied health effects of concurrent exposures to AMB-PM2.5 and SHS-PM2.5 over a 6-year period in schoolchildren with asthma. Regression calibration with instrumental variables (RCIV) was utilized to estimate effects of personal exposure to low-level SHS and AMB-PM2.5 on daily albuterol usage and urinary leukotriene E4 (uLTE4; a biomarker of asthma-related inflammation) using urine cotinine and concentrations from fixed and personal pollution monitors. Each IQR increase in SHS-PM2.5 exposure was associated with a 6.7% increase (95% CI: 1.0–12.8%) in uLTE4 on the same day and 9.4% increase (95% CI: −2.6 to 22.7%) in albuterol use the next day, when children were co-exposed to mean levels of AMB-PM2.5. The dose-response relationship between health outcomes and one pollutant was higher at lower levels of the other pollutant. For example, at lower levels of predicted SHS-PM2.5 exposure, increases in health outcomes per IQR increase in AMB-PM2.5 ranged between 2 and 5%, but were negligible at higher SHS-PM2.5 levels. Comparing at equivalent co-exposure levels, SHS-PM2.5 was 1.6 times more potent than AMB-PM2.5 for uLTE4 (95% CI: 1.1–2.3); estimates for albuterol usage were similar but less significant. Effects at mean co-exposure levels were closer [SHS to AMB-PM2.5 potency ratio = 1.2 (95% CI: 0.9–1.5) for uLTE4 and 1.2 (95% CI: 0.7–1.9) for albuterol usage]. In summary, concurrent exposure to relatively low levels of SHS and AMB-PM2.5 were associated with health outcomes in asthmatic schoolchildren. Dose responses varied with changes in the relative amounts of each pollutant; SHS-PM2.5 was observed to be more potent than AMB-PM2.5 when co-exposure levels were equivalent.

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Fig. 1: Relative potency of pollutants.

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  1. Zheng XY, Ding H, Jiang LN, Chen SW, Zheng JP, Qiu M, et al. Association between air pollutants and asthma emergency room visits and hospital admissions in time series studies: a systematic review and meta-analysis. PLoS ONE. 2015;10:e0138146.

    Article  Google Scholar 

  2. Schwartz J, Bind M-A, Koutrakis P. Estimating causal effects of local air pollution on daily deaths: effect of low levels. Environ Health Perspect. 2017;125:23–29.

    Article  CAS  Google Scholar 

  3. Adams K, Greenbaum DS, Shaikh R, van Erp AM, Russell AG. Particulate matter components, sources, and health: Systematic approaches to testing effects. J Air Waste Manag Assoc. 2015;65:544–58.

    Article  CAS  Google Scholar 

  4. Jin W, Su S, Wang B, Zhu X, Chen Y, Shen G, et al. Properties and cellular effects of particulate matter from direct emissions and ambient sources. J Environ Sci Health. 2016;51:1075–83.

    Article  CAS  Google Scholar 

  5. Centers for Disease Control and Prevention. Vital signs: disparities in nonsmokers’ exposure to secondhand smoke—United States, 1999–2012. Morbidity Mortal Wkly Rep. 2015;64:103–8. Accessed 16 Jan 2019.

    Google Scholar 

  6. Benowitz NL, Jain S, Dempsey DA, Nardone N, Helen GS, Jacob P 3rd. Urine cotinine screening detects nearly ubiquitous tobacco smoke exposure in urban adolescents. Nicotine Tob Res. 2017;19:1048–54.

    CAS  PubMed  Google Scholar 

  7. Chilmonczyk BA, Salmun LM, Megathlin KN, Neveaux LM, Palomaki GE, Knight GJ, et al. Association between exposure to environmental tobacco smoke and exacerbations of asthma in children. N. Engl J Med. 1993;328:1665–9.

    Article  CAS  Google Scholar 

  8. Ciaccio CE, Gurley-Calvez T, Shireman TI. Indoor tobacco legislation is associated with fewer emergency department visits for asthma exacerbation in children. Ann Allergy Asthma Immunol. 2016;117:641–5.

    Article  Google Scholar 

  9. Pope CA 3rd, Burnett RT, Krewski D, Jerrett M, Shi Y, Calle EE, et al. Cardiovascular mortality and exposure to airborne fine particulate matter and cigarette smoke: shape of the exposure-response relationship. Circulation. 2009;120:941–8.

    Article  CAS  Google Scholar 

  10. Burnett RT, Pope CA 3rd, Ezzati M, Olives C, Lim SS, Mehta S, et al. An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure. Environ Health Perspect. 2014;122:397–403.

    Article  Google Scholar 

  11. Strand M, Vedal S, Rodes C, Dutton SJ, Gelfand EW, Rabinovitch N. Estimating effects of ambient PM2.5 exposure on health using PM2.5 component measurements and regression calibration. J Exp Sci Environ Epi. 2006;16:30–8.

    Article  CAS  Google Scholar 

  12. Strand M, Hopke PK, Zhao W, Vedal S, Gelfand E, Rabinovitch N. A study of health effect estimates using competing methods to model personal exposures to ambient PM2.5. J Expo Sci Environ Epidemiol. 2007;17:549–58.

    Article  CAS  Google Scholar 

  13. Hoffman BC, Rabinovitch N. Urinary leukotriene E4 as a biomarker of exposure, susceptibility, and risk in asthma: an update. Immunol Allergy Clin North Am. 2018;38:599–610.

    Article  Google Scholar 

  14. Strand M, Sillau S, Grunwald GK, Rabinovitch N. Regression calibration for models with two predictor variables measured with error and their interaction, using instrumental variables and longitudinal data. Stat Med. 2014;33:470–87.

    Article  Google Scholar 

  15. Strand M, Sillau S, Grunwald GK, Rabinovitch N. Regression calibration with instrumental variables for longitudinal models with interaction terms, and application to air pollution studies. Environmetrics. 2015;26:393–405.

    Article  CAS  Google Scholar 

  16. Urbano FL. Review of the NAEPP 2007 expert panel report (EPR-3) on asthma diagnosis and treatment guidelines. J Manag Care Pharm. 2008;14:41–9.

    Article  Google Scholar 

  17. Rabinovitch N, Strand M, Gelfand EW. Particulate levels are associated with early asthma worsening in children with persistent disease. Am J Respir Crit Care Med. 2006;173:1098–105.

    Article  CAS  Google Scholar 

  18. Rabinovitch N, Silveira L, Gelfand EW, Strand M. The response of children with asthma to ambient particulate is modified by tobacco smoke exposure. Am J Resp Crit Care Med. 2011;184:1350–7.

    Article  CAS  Google Scholar 

  19. Carroll RJ, Ruppert D, Stephanski LA. Measurement Error in Nonlinear Models: A Modern Perspective. 2nd edition. Boca Raton: Chapman and Hall/CRC; 2006.

    Book  Google Scholar 

  20. Delfino RJ, Quintana PJ, Floro J, Gastañaga VM, Samimi BS, Kleinman MT, et al. Association of FEV1 in asthmatic children with personal and microenvironmental exposure to airborne particulate matter. Environ Health Perspect. 2004;112:932–41.

    Article  CAS  Google Scholar 

  21. Rabinovitch N, Adams CD, Strand M, Koehler K, Volckens J. Within-microenvironment exposure to particulate matter and health effects in children with asthma: a pilot study utilizing real-time personal monitoring with GPS interface. Environ Health. 2016;15:96.

    Article  Google Scholar 

  22. Matt GE, Quintana PJ, Destaillats H, et al. Thirdhand tobacco smoke: emerging evidence and arguments for a multidisciplinary research agenda. Environ Health Perspect. 2011;119:1218–26.

    Article  CAS  Google Scholar 

  23. Williams R, Suggs J, Creason J, Rodes C, Lawless P, Kwok R, et al. The 1998 Baltimore particulate matter epidemiology-exposure study: part 2. Personal exposure assessment associated with an elderly study population. J Expo Anal Environ Epidemiol. 2000;10:533–43.

    Article  CAS  Google Scholar 

  24. Martins-Green M, Adhami N, Frankos M, Valdez M, Goodwin B, Lyubovitsky J, et al. Cigarette smoke toxins deposited on surfaces: implications for human health. PLoS One. 2014;9:e86391.

    Article  Google Scholar 

  25. Goettel M, Niessner R, Scherer M, Scherer G, Pluym N. Analysis of urinary eicosanoids by LC-MS/MS reveals alterations in the metabolic profile after smoking cessation. Chem Res Toxicol. 2018;31:176–82.

    Article  CAS  Google Scholar 

  26. Turner MC, Cohen A, Jerrett M, Gapstur SM, Diver WR, Pope CA 3rd, et al. Interactions between cigarette smoking and fine particulate matter in the Risk of Lung Cancer Mortality in Cancer Prevention Study II. Am J Epidemiol. 2014;180:1145–9.

    Article  Google Scholar 

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We would like to thank Arden Pope for his review and helpful comments on this paper.

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Correspondence to Matthew Strand.

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Strand, M., Rabinovitch, N. Health effects of concurrent ambient and tobacco smoke-derived particle exposures at low concentrations in children with asthma. J Expo Sci Environ Epidemiol 30, 785–794 (2020).

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