|Year : 2023 | Volume
| Issue : 1 | Page : 23-30
|Increased airway resistance among exclusive waterpipe smokers detected using impulse oscillometry
Hassan A Chami1, Nourhan Houjeij2, Maha Makki3, Lina Itani3, Hani Tamim4, Ahmad Al Mulla5, Bartolome Celli6, Salah Zeineldine3
1 School of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America; Department of Medicine and Clinical Research Institute, American University of Beirut, Beirut, Lebanon
2 Department of Nephrology, Saint Louis University, St Louis, Missouri, United States of America
3 Department of Medicine and Clinical Research Institute, American University of Beirut, Beirut, Lebanon
4 Department of Medicine and Clinical Research Institute, American University of Beirut, Beirut, Lebanon; College of Medicine, Alfaisal University, Riyadh, Kingdom of Saudi Arabia
5 Tobacco Control Center, WHO Collaborative Center, Department of Medicine, Hamad Medical Corporation, Doha, Qatar
6 Harvard Medical School, Boston, Massachusetts, United States of America
|Date of Submission||25-Apr-2022|
|Date of Acceptance||05-Nov-2022|
|Date of Web Publication||25-Jan-2023|
Dr. Salah Zeineldine
Department of Internal Medicine, American University of Beirut, Riad El Solh 11-0236, Beirut
Source of Support: None, Conflict of Interest: None
| Abstract|| |
INTRODUCTION: Waterpipe smoking is increasing in popularity, yet the evidence implicating waterpipe smoking in lung disease is limited. We hypothesized that impulse oscillometry (IOS) would detect airway abnormalities in waterpipe smokers (WPS).
METHODS: We studied 210 participants, 40 years or older, from the community, of whom 92 were exclusive WPS and 118 were never-smokers. Waterpipe smoking history was assessed using a validated questionnaire. All participants underwent spirometry, and IOS and absolute and percentage predicted results (for age, sex, height, and weight) were compared between WPS and nonsmokers. The association of IOS parameters with waterpipe smoking duration and extent (waterpipe smoked/day * smoking duration) was evaluated using linear regression.
RESULTS: WPS smoked on average 1.8 ± 1.2 waterpipes/day, over an average duration of 23.3 ± 39.8 years. WPS and nonsmokers were largely asymptomatic and had similar age, body mass index, sex distribution, and spirometric values. Nevertheless, WPS had higher IOS measured resistance at 5Hz compared to nonsmokers, (0.53 ± 0.2 vs. 0.48 ± 0.2 kPa/L/s, P = 0.03) and higher percentage-predicted resistance (124.5 ± 36.3 vs. 115.7% ± 35.6%, P = 0.04). Waterpipe smoking duration was also associated with resistance (β = 0.04 kPa/L/s/year, P = 0.01) and with percentage-predicted resistance (β = 0.05/year, P = 0.02). Waterpipe smoking extent was associated with resistance (β = 0.009 kPa/L/s/waterpipe-year, P = 0.04), while the association with percentage-predicted resistance was near significance (β = 0.009/waterpipe-year, P = 0.07).
CONCLUSIONS: Waterpipe smoking is associated with increased airway resistance assessed by IOS but not by spirometry in largely asymptomatic individuals from the community.
Keywords: Lung disease, nicotine, noncigarette tobacco product, smoking caused disease, waterpipe
|How to cite this article:|
Chami HA, Houjeij N, Makki M, Itani L, Tamim H, Al Mulla A, Celli B, Zeineldine S. Increased airway resistance among exclusive waterpipe smokers detected using impulse oscillometry. Ann Thorac Med 2023;18:23-30
|How to cite this URL:|
Chami HA, Houjeij N, Makki M, Itani L, Tamim H, Al Mulla A, Celli B, Zeineldine S. Increased airway resistance among exclusive waterpipe smokers detected using impulse oscillometry. Ann Thorac Med [serial online] 2023 [cited 2023 Mar 24];18:23-30. Available from: https://www.thoracicmedicine.org/text.asp?2023/18/1/23/368493
Waterpipe is a form of tobacco smoking that has gained worldwide popularity in the last two decades, especially among young adults. The increase in the popularity of waterpipe smoking is partly due to the misperception of reduced harm among the public. While the causal association of cigarette smoking with pulmonary diseases is established, a systematic review of the effects of waterpipe smoking on lung function deemed the quality of evidence linking waterpipe smoking with impaired lung function from moderate to low. Studies that compared spirometric measures of lung function in waterpipe smokers (WPS) and nonsmokers showed inconsistent results and were methodologically limited. Four studies reported reduced spirometric measures of lung function in WPS;,,, however, one of those studies did not account for confounders, and another evaluated the tobacco-burning rather than the charcoal-based waterpipe evaluated in other studies. Several other studies found no significant reduction in spirometric measures of lung function among WPS.,,,,,
Impulse oscillometry (IOS) is a simple, noninvasive technique that assesses the mechanical properties of the lungs during normal breathing., IOS parameters correlate with spirometric measures of lung function in chronic obstructive pulmonary disease (COPD) patients. Furthermore, IOS is more sensitive than spirometry at detecting lung function abnormalities in cigarette smokers, in symptomatic versus asymptomatic individuals with normal spirometry and in COPD patients., Therefore, IOS is an attractive test to assess early respiratory impairment in asymptomatic WPS that may be missed using spirometry.
We hypothesized that IOS would help detect early markers of respiratory impairment in WPS with normal spirometry. To this effect, we conducted a cross-sectional study that compared IOS and spirometric measures of lung function among adults exclusive to WPS and never-smokers from the community.
| Methods|| |
We enrolled 210 participants 40 years or older from the community in Beirut, Lebanon, between September 2013 and March 2017 using previously reported methods. Our sample included 92 exclusive WPS who have been smoking daily for >10 years but never smoked cigarette or other tobacco products, and 118 controls who never smoked. WPS was recruited directly from cafes that offer waterpipe or through advertisements, flyers, social media, and word of mouth; nonsmokers were recruited through the same advertisements. Exclusion criteria included any former or current cigarette, other forms of tobacco smoking, nonsmoking-related pulmonary disease (asthma, bronchiectasis, and fibrosis), and occupational smoke, dust, or chemical exposure. Individuals with diabetes and renal failure were also excluded to allow for unbiased cardiovascular risk evaluation. Nonsmokers with exhaled carbon monoxide (CO) levels >10 ppm were also excluded. All participants signed informed consent. The study was approved by the American University of Beirut Institutional Review Board (IM. HC.03).
Participants were screened for symptoms of respiratory infection before testing and were rescheduled 4 weeks after symptoms resolution if symptoms were present. Participants were surveyed using an investigator-administered questionnaire for sociodemographics characteristics (age, sex, race, income, and education), medical history (respiratory disease/symptoms, family history of lung disease, hypertension, cardiovascular disease, and malignancy), alcohol and caffeine consumption and physical activity. Height and weight were measured, and body mass index (BMI) was calculated.
Waterpipe smoking was assessed using a previously validated investigator-administered questionnaire that accounts for the variability in smoking patterns and intensity. Smoking status was further ascertained using plasma cotinine (a byproduct of nicotine metabolism) in all participants and exhaled CO in nonsmokers. Plasma cotinine levels were measured using a solid-phase competitive ELISA (BIO-QUANT kit) on morning fasting samples. Breath CO was measured by asking the participants to exhale into the micro-smokerlyzer (Bedfont).
IOS parameters including total airway resistance at 5Hz (R5), reactance at 5Hz (X5), impedance (Z), percentage difference in resistance at 5 and 20Hz (R5-R20%), resonance frequency (Fres), reactance area (AX), and coherence at 5Hz were measured using the Masterscreen Carefusion IOS (Hoechberg, Germany). Participants were seated upright with their legs uncrossed, head held in the neutral position, and lips tightly sealed around the IOS mouthpiece, with a nose clip placed and hands supporting cheeks. After machine calibration, and participants' adaptation to tidal breathing through the machine was achieved with no artifact or air leaks, a minimum of three IOS measurements were acquired over 30–90s. Measurements were repeated after the administration of bronchodilators. After three technically acceptable and reproducible measurements were acquired and verified using built-in quality control measures, the measurement with the best coherence was selected. Predicted IOS measures were calculated using previously published equations by Schulz et al. that account for age, sex, height, and weight.
Spirometry was performed using the KoKo Px Nspire Health system, following the American Thoracic Society and European Respiratory Society guidelines after IOS to avoid affecting the bronchomotor tone., The same technician performed both spirometry and IOS in both WPS and nonsmokers. Participants performed at least three maneuvers of maximal forced inspiratory and expiratory efforts before and after bronchodilator administration. Percentage-predicted values for sex, age, height, and weight, were obtained from built-in equations.
Sociodemographic and health characteristics, smoking habits, and spirometry parameters of WPS and nonsmokers were summarized and compared using Chi-square test and two-sample t-test to determine bivariate differences for categorical and continuous variables, respectively.
The independent (exposure) variable in the main analysis was waterpipe smoking status, categorized as WPS versus nonsmoker. Secondary independent variables assessed the extent of waterpipe smoking exposure and included: Smoking duration in years and the product of smoking duration and intensity (number of waterpipes smoked daily) expressed in waterpipe-years.
The primary dependent (outcome) variable in the main analyses was prebronchodilator R5. Secondary independent variables evaluated in secondary analyses included Z, X5, Fres, R5-R20%, and AX measured pre and postbronchodilators. Percentage-predicted measures were evaluated to account for variability in the participants' age, sex, weight, and height.
The association of waterpipe smoking and IOS parameters was evaluated by comparing the various IOS and spirometry parameters expressed as mean ± standard deviation between WPS and nonsmokers using t-test. Because of their skewed distribution, percentage-predicted IOS parameters were log-transformed to ensure normal distribution. The association of log-transformed IOS parameters with waterpipe smoking and its extent was further evaluated using linear regression. Analyses were repeated, excluding participants whose coherence 5Hz <0.6. P < 0.05 was considered statistically significant. Statistical analyses were performed using SPSS (IBM Corp, Armonk NY, USA).
| Results|| |
Demographic, health, and smoking characteristics of WPS and nonsmokers are presented in [Table 1] All participants were Caucasian of Arab ethnicity. WPS and nonsmokers had similar ages, and no significant difference in sex distribution or BMI. Two WPS (2.2%) reported dyspnea, and no other participant reported chronic cough or other respiratory symptoms or diseases. Similar proportions of WPS and nonsmokers reported exercising regularly and no meaningful difference in self-reported hypertension, cardiovascular disease, or family history of lung diseases. As expected, WPS had significantly higher morning plasma cotinine levels compared to nonsmokers. All participants who reported being nonsmokers had plasma cotinine levels <10 ng/ml and exhaled CO <10 ppm. Ninety-six percent of WPS smoked daily, on average 1.8 ± 1.2 waterpipes/day, over an average duration of 23.3 ± 39.8 years, 53% smoked flavored tobacco, 43% smoked unflavored tobacco, and 4.3% smoked both.
|Table 1: Demographic, health and smoking characteristics of waterpipe smokers and nonsmokers|
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No significant difference in spirometric parameters between WPS and nonsmokers was detected [Table 2]. Forced expiratory flow (FEF 25%–75%) was numerically lower in nonsmokers, although the difference did not reach statistical significance. An obstructive pattern on spirometry (postbronchodilator forced expiratory volume in 1 s [FEV1]/forced vital capacity [FVC]<0.7) was present in 3 WPS and 2 nonsmokers, (3.3% vs 1.7% P = 0.6), reduced FEV1 <80% was present in 3 WPS and 4 nonsmokers, (3.3% vs. 3.4% P = 1), and FVC <80% in 1 WPS and 3 nonsmokers (1.1% vs. 2.5% P = 0.6).
Conversely, several IOS parameters were significantly different between WPS and nonsmokers [Table 3] and [Figure 1]. Absolute and percent-predicted R5 were higher in WPS compared to nonsmokers. R5 decreased postbronchodilator administration in both WPS and nonsmokers with no subsequent difference in postbronchodilator R5 between WPS and nonsmokers; however, very few participants had a significant bronchodilator response defined as a decrease in R5 by >40%. Similarly, Z was significantly higher in WPS compared to nonsmokers, although the numerically higher percentage-predicted Z in WPS was of borderline significance. Postbronchodilator X5 was more negative in WPS versus nonsmokers, although the difference in percentage-predicted X5 between WPS and nonsmokers was not statistically significant. Percentage-predicted Fres was significantly higher in WPS compared to nonsmoker, while the numerically higher absolute Fres in WPS vs. nonsmokers was of borderline significance. Other secondary IOS parameters, including R5%–20% and AX, were not significantly different between WPS and nonsmokers [Supplement Table S1].
[Additional file 1]
|Figure 1: (a) Mean pre-bronchodilator airway resistance at 5Hz (R5), kPa/L/s in waterpipe smokers and non-smokers. (b) Mean % predicted pre-bronchodilator airway resistance at 5Hz (R5) in waterpipe smokers and non-smokers. (c) Mean pre-bronchodilator FEV1/FVC in waterpipe smokers and non-smokers|
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Waterpipe smoking duration was significantly associated with absolute and with percentage-predicted R5 [Table 4]. Waterpipe smoking extent in waterpipe years was also associated with absolute R5, although the association with percentage-predicted R5 was nearly significant. Waterpipe smoking duration and extent in waterpipe-years were also associated with Z, Fres, and AX but not with their percentage-predicted measures. Waterpipe smoking duration was also significantly associated with R5-R20% and with percentage-predicted X5. Waterpipe smoking duration was associated with postbronchodilator R5, Z, and Fres but not with their percentage-predicted values [Supplement Table S2]. Results were similar in sensitivity analyses excluding 24 participants whose coherence at 5Hz was <0.6 (results not shown).
[Additional file 2]
|Table 4: Association of impulse oscillometry measures with waterpipe smoking extent|
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| Discussion|| |
Middle-aged adult exclusive WPS from the community who never smoked other tobacco products had higher absolute and percentage-predicted prebronchodilator airway resistance at 5 Hz (R5) measured with IOS compared to never-smokers. The duration and extent of waterpipe smoking (waterpipe-years) were also related to the degree of airway resistance. Such difference in lung function was not detected using spirometry in this largely asymptomatic sample.
IOS parameters measured at lower frequencies (5 Hz) are sensitive to airway obstruction. Therefore, increased R5 in WPS compared to nonsmokers, suggests the presence of airflow limitation associated with waterpipe smoking. The magnitude of the difference in R5 between WPS and nonsmokers in our sample of 0.05 kPa/L/s is larger than the previously reported difference of 0.02 kPa/L/s between cigarette smokers and nonsmokers with normal spirometry, and similar to the difference in R5 between asymptomatic and symptomatic individuals without airway obstruction on spirometry.,
Although R5 decreased postbronchodilator in WPS and nonsmokers with no difference in postbronchodilator R5 between WPS and nonsmokers, the increased airway resistance in WPS cannot be considered reversible since very few participants had a significant bronchodilator response.
R5%–R20% possibly reflects small airway dysfunction and was not significantly different in WPS and nonsmokers, suggesting that the difference in total airway resistance (R5) between WPS and nonsmokers is attributed to increased large airway resistance. Alternatively, the lack of difference in R5%–R20% between WPS and nonsmokers could be attributed to greater variability in measuring R5%–R20% or other environmental exposures in nonsmokers.
Lower (more negative) X5, which indicates increased dynamic elastance, has been attributed to a decrease in lung elastic recoil in smokers., Therefore, lower postbronchodilator X5 in WPS compared to nonsmokers suggests the presence of decreased lung elastic recoil in WPS, which has been associated with hyperinflation and airflow obstruction. However, percentage-predicted X5 were numerically but not statistically different among WPS and nonsmokers; therefore, the difference in X5 could be due to differences in other characteristics of our participants.
Several studies have evaluated the effects of waterpipe smoking on lung function, yet to our knowledge, this is the first study that compared lung function in WPS and nonsmokers using both IOS and spirometry. Prior studies that used spirometry to compare the lung function of WPS and nonsmokers from the community found conflicting results.,,,,,,,,, Studies that reported that FEV1,,,, FEV1/FVC,,, FEF25%–75%, or FVC, were reduced in WPS compared to nonsmokers,,, have several limitations., Contrary to our study, one study did not use percentage-predicted spirometric values or adjust for imbalances in predictors of lung function between WPS and nonsmokers. While another study evaluated the noncharcoal-based Chinese waterpipe, which burns tobacco directly, this waterpipe differs from the widely used charcoal-based traditional waterpipe that we and other studies have evaluated., Furthermore, unlike our study, none of those studies used a validated method to assess waterpipe smoking exposure or an objective method to ascertain nonsmoking status., Similar to our findings, other studies that used spirometry did not find a significant reduction in percentage predicted FEV1,,,,,, FEV1/FVC,,,,,, or FEF25%–75%, in WPS versus nonsmokers. A meta-analysis of six studies deemed the quality of evidence to be moderate to low.,,,,,
The mechanisms that might explain how waterpipe smoking impairs lung function have not been well elucidated. The increased prebronchodilator R5 in WPS could be mediated by waterpipe smoke-induced airway mucosal inflammation and mucus hypersecretion similar to changes previously described with cigarette smoking., Indeed, the small airway epithelium of light WPS has a higher percentage of secretory cells compared to nonsmokers. Mice exposed to waterpipe smoke for a week have shown increased markers of inflammation and oxidative injury, including interleukin (IL)–6, tumor necrosis factor-α (TNF-α), anti-oxidative enzyme catalases, and glutathione peroxidase in bronchoalveolar fluid and lung tissue to levels similar to that produced by cigarette smoke. Furthermore, bronchoalveolar lavage fluid of WPS with COPD show increased metalloproteinase 2 and 9 gene expression similar to that of cigarette smokers with COPD. Although light WPS had very few upregulated oxidative stress-related genes in the small airway epithelium transcriptome compared to cigarette smokers, and the cellular composition of lower respiratory epithelial fluid of light WPS was not significantly different from nonsmokers. Other factors previously associated with cigarette smoking-induced airway disease, such as increased in airway IL–8 and TNF-α levels cytokines that promote neutrophil chemotaxis and activate adhesion molecules, could also be contributing.
This study is limited by the observational cross-sectional design that does not allow making firm conclusions regarding causality. Nevertheless, the linear association between the duration and extent of waterpipe smoking and the degree of airway resistance suggests the presence of a biological gradient and thus supports a causal association between waterpipe smoking and increased airway resistance. Balancing this limitation are several strengths, including the well-described community-based sample of largely asymptomatic individuals selected independent of the risk of respiratory conditions or symptoms and the exclusion of nonsmoking related respiratory disease, which reduced the risk of selection bias. Furthermore, objective ascertainment of nonsmoking status using exhaled CO and plasma cotinine and using a validated instrument to assess waterpipe smoking exposure reduced bias from misclassification. While the exclusion of individuals with concurrent or prior history of cigarette or other tobacco smoking and adjustment for other potential confounders using percentage-predicted lung function measures further strengthen this study.
| Conclusions|| |
In a community-based sample of largely asymptomatic adults with normal spirometry, exclusive waterpipe smoking was associated with increased airway resistance assessed by IOS even after accounting for confounders. This finding provides further evidence that waterpipe smoking is a risk factor for lung disease even in apparently healthy individuals and justifies measures to raise awareness of its adverse health effects. Prospective longitudinal studies evaluating lung function in WPS in comparison to nonsmokers are needed to strengthen the evidence implicating waterpipe smoking in lung disease.
We are grateful to the participants who agreed to enroll in this study and undergo study procedures. We would also like to acknowledge the contribution of Eleine El-Khoury and Blanche Ghandour to data management and analysis and the contribution of Nadine Ammar to data collection.
Financial support and sponsorship
This work was supported by a grant from the Qatar National Research Fund, National Priorities Research Program (project number: 5-975-3-216). The funder had no role in the design, management, data collection, analyses, or interpretation of the data or in the writing of the manuscript or the decision to submit for publication.
Conflicts of interest
There are no conflicts of interest.
| References|| |
Maziak W, Taleb ZB, Bahelah R, Islam F, Jaber R, Auf R, et al.
The global epidemiology of waterpipe smoking. Tob Control 2015;24 Suppl 1:i3-12.
Office of the Surgeon General, Office on Smoking and Health. Reports of the Surgeon General. The Health Consequences of Smoking: A Report of the Surgeon General. Atlanta (GA): Centers for Disease Control and Prevention (US); 2004.
Raad D, Gaddam S, Schunemann HJ, Irani J, Abou Jaoude P, Honeine R, et al.
Effects of water-pipe smoking on lung function: A systematic review and meta-analysis. Chest 2011;139:764-74.
El-Zaatari ZM, Chami HA, Zaatari GS. Health effects associated with waterpipe smoking. Tob Control 2015;24 Suppl 1:i31-43.
She J, Yang P, Wang Y, Qin X, Fan J, Wang Y, et al.
Chinese water-pipe smoking and the risk of COPD. Chest 2014;146:924-31.
Boskabady MH, Farhang L, Mahmodinia M, Boskabady M, Heydari GR. Comparison of pulmonary function and respiratory symptoms in water pipe and cigarette smokers. Respirology 2012;17:950-6.
Al-Fayez SF, Salleh M, Ardawi M, Zahran FM. Effects of sheesha and cigarette smoking on pulmonary function of Saudi males and females. Trop Geogr Med 1988;40:115-23.
Meo SA, AlShehri KA, AlHarbi BB, Barayyan OR, Bawazir AS, Alanazi OA, et al.
Effect of shisha (waterpipe) smoking on lung functions and fractional exhaled nitric oxide (FeNO) among Saudi young adult shisha smokers. Int J Environ Res Public Health 2014;11:9638-48.
Aydin A, Kiter G, Durak H, Ucan ES, Kaya GC, Ceylan E. Water-pipe smoking effects on pulmonary permeability using technetium-99m DTPA inhalation scintigraphy. Ann Nucl Med 2004;18:285-9.
Kiter G, Uçan ES, Ceylan E, Kilinç O. Water-pipe smoking and pulmonary functions. Respir Med 2000;94:891-4.
Layoun N, Saleh N, Barbour B, Awada S, Rachidi S, Al-Hajje A, et al.
Waterpipe effects on pulmonary function and cardiovascular indices: A comparison to cigarette smoking in real life situation. Inhal Toxicol 2014;26:620-7.
Al Mutairi SS, Shihab-Eldeen AA, Mojiminiyi OA, Anwar AA. Comparative analysis of the effects of hubble-bubble (Sheesha) and cigarette smoking on respiratory and metabolic parameters in hubble-bubble and cigarette smokers. Respirology 2006;11:449-55.
Köseoğlu N, Aydin A, Uçan ES, Ceylan E, Eminoğlu O, Durak H, et al.
The effects of water-pipe, cigarette and passive smoking on mucociliary clearance. Tuberk Toraks 2006;54:222-8.
Mohammad Y, Shaaban R, Al-Zahab BA, Khaltaev N, Bousquet J, Dubaybo B. Impact of active and passive smoking as risk factors for asthma and COPD in women presenting to primary care in Syria: First report by the WHO-GARD survey group. Int J Chron Obstruct Pulmon Dis 2013;8:473-82.
Bickel S, Popler J, Lesnick B, Eid N. Impulse oscillometry: Interpretation and practical applications. Chest 2014;146:841-7.
Komarow HD, Myles IA, Uzzaman A, Metcalfe DD. Impulse oscillometry in the evaluation of diseases of the airways in children. Ann Allergy Asthma Immunol 2011;106:191-9.
Anderson WJ, Lipworth BJ. Relationships between impulse oscillometry, spirometry and dyspnoea in COPD. J R Coll Physicians Edinb 2012;42:111-5.
Shinke H, Yamamoto M, Hazeki N, Kotani Y, Kobayashi K, Nishimura Y. Visualized changes in respiratory resistance and reactance along a time axis in smokers: A cross-sectional study. Respir Investig 2013;51:166-74.
Frantz S, Nihlén U, Dencker M, Engström G, Löfdahl CG, Wollmer P. Impulse oscillometry may be of value in detecting early manifestations of COPD. Respir Med 2012;106:1116-23.
Chami HA, Isma'eel H, Tamim H, Adawi M, Al Kuwari M, Al Mullah A. The association of water-pipe smoking and coronary artery calcium in a community-based sample. Chest 2019;155:1217-25.
Abou Arbid S, Al Mulla A, Ghandour B, Ammar N, Adawi M, Daher R, et al.
Validation of an Arabic version of an instrument to measure waterpipe smoking behavior. Public Health 2017;145:124-31.
Schulz H, Flexeder C, Behr J, Heier M, Holle R, Huber RM, et al.
Reference values of impulse oscillometric lung function indices in adults of advanced age. PLoS One 2013;8:e63366.
Miller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, Coates A, et al.
Standardisation of spirometry. Eur Respir J 2005;26:319-38.
Tomalak W, Czajkowska-Malinowska M, Radliński J. Application of impulse oscillometry in respiratory system evaluation in elderly patients. Pneumonol Alergol Pol 2014;82:330-5.
Tan TX, Vo T, Khoa T, Hanh HD, Thu TT, Lan LT. Investigating Chronic Obstructive Pulmonary Disease (COPD) in Vietnamese Patients Using Impulse Oscillometry (IOS). Vol. 46. IFMBE Proceedings; 2015. p. 285-8.
Knudson RJ, Lebowitz MD, Holberg CJ, Burrows B. Changes in the normal maximal expiratory flow-volume curve with growth and aging. Am Rev Respir Dis 1983;127:725-34.
Zaidan MF, Meah S, Duarte A. The use and interpretation of impedance oscillometry in pulmonary disorders. Curr Pulmonol Rep 2018;7:196-202.
Oostveen E, MacLeod D, Lorino H, Farré R, Hantos Z, Desager K, et al.
The forced oscillation technique in clinical practice: Methodology, recommendations and future developments. Eur Respir J 2003;22:1026-41.
Borrill ZL, Roy K, Vessey RS, Woodcock AA, Singh D. Non-invasive biomarkers and pulmonary function in smokers. Int J Chron Obstruct Pulmon Dis 2008;3:171-83.
Friedman SM, Maslow CB, Reibman J, Pillai PS, Goldring RM, Farfel MR, et al.
Case-control study of lung function in World Trade Center Health Registry area residents and workers. Am J Respir Crit Care Med 2011;184:582-9.
Kolsum U, Borrill Z, Roy K, Starkey C, Vestbo J, Houghton C, et al.
Impulse oscillometry in COPD: Identification of measurements related to airway obstruction, airway conductance and lung volumes. Respir Med 2009;103:136-43.
Woolcock AJ, Vincent NJ, Macklem PT. Frequency dependence of compliance as a test for obstruction in the small airways. J Clin Invest 1969;48:1097-106.
Saetta M, Turato G, Maestrelli P, Mapp CE, Fabbri LM. Cellular and structural bases of chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2001;163:1304-9.
Strulovici-Barel Y, Shaykhiev R, Salit J, Deeb RS, Krause A, Kaner RJ, et al.
Pulmonary abnormalities in young, light-use waterpipe (Hookah) smokers. Am J Respir Crit Care Med 2016;194:587-95.
Khabour OF, Alzoubi KH, Bani-Ahmad M, Dodin A, Eissenberg T, Shihadeh A. Acute exposure to waterpipe tobacco smoke induces changes in the oxidative and inflammatory markers in mouse lung. Inhal Toxicol 2012;24:667-75.
Kaddah S, Rashed L, Obaia E. A preliminary study: Matrix metalloproteinase expression as an indicator of the hazards of shisha (narghila) smoking. Arch Med Sci 2009;5:570-6.
Keatings VM, Collins PD, Scott DM, Barnes PJ. Differences in interleukin-8 and tumor necrosis factor-alpha in induced sputum from patients with chronic obstructive pulmonary disease or asthma. Am J Respir Crit Care Med 1996;153:530-4.
[Table 1], [Table 2], [Table 3], [Table 4]