|Year : 2017 | Volume
| Issue : 1 | Page : 1-7
Spirometric evaluation of ventilatory function in adult male cigarette smokers in Sokoto metropolis
Muhammad D Isah1, Muhammad A Makusidi1, Aminu Abbas1, Juliana U Okpapi2, Chibueze H Njoku3, Abdullahi A Abba2
1 Department of Medicine, UDUTH, Sokoto, Nigeria
2 Department of Medicine, ABUTH, Zaria, Nigeria
3 Department of Medicine, UCTH, Calabar, Nigeria
|Date of Web Publication||9-May-2017|
Muhammad D Isah
Department of Medicine, Usmanu Danfodiyo University Teaching Hospital, P.M.B. 2370, Sokoto
Source of Support: None, Conflict of Interest: None
Background: Cigarette smoking is a widespread social habit in Nigeria with extensive deleterious multisystemic effect. Ventilatory dysfunction is one of the cigarette smoking-related illnesses that affect the respiratory system. Spirometry is an investigative method that can be used for the early detection of ventilatory dysfunction even before the onset of the symptoms. Subjects and Methods: A questionnaire adapted from the European Community Respiratory Health Survey was administered to collect demographic, clinical, and cigarette smoking data. Ventilatory function test was conducted using Clement Clarke (One Flow) Spirometer, version 1.3. The highest value of each ventilatory function index was chosen for analysis, and individual(s) with ventilatory dysfunction were subjected to post bronchodilator spirometry. Results: For the purpose of this research, 150 participants who were currently cigarette smokers were enrolled, and 50 apparently healthy, age-matched individuals who were never smokers served as controls in the ratio of 3:1. Eighty percent of participants and 68% of controls were aged 40 years or below. The mean age of participants (34.27 ± 8.91 years) and the controls (35.08 ± 10.35 years) was not significantly different (P = 0.592). Similarly, there were no statistically significant differences between the mean anthropometric indices (weight: P = 0.663, height: P = 0.084, and body mass index: P = 0.099) of both participants and controls. The mean values of FEV1 (forced expiratory flow in one second) and FEV1/FVC (FVC=forced vital capacity) were lower in the participants compared to the controls, and this difference was statistically significant (P < 0.001). There was a weak negative correlation between pack-years of cigarette smoking and FEV1 (r = −0.237 and P = 0.004). Obstructive ventilatory defect was found among six study participants (4%) and two controls (4%). Conclusion: Cigarette smoking is associated with decline in ventilatory function test indices (FEV1 and FEV1/FVC) in adult males. Decline in FEV1 is directly related to pack-years of cigarette smoking.
Keywords: Northwest nigeria, spirometry, tobacco smoking
|How to cite this article:|
Isah MD, Makusidi MA, Abbas A, Okpapi JU, Njoku CH, Abba AA. Spirometric evaluation of ventilatory function in adult male cigarette smokers in Sokoto metropolis. Niger Postgrad Med J 2017;24:1-7
|How to cite this URL:|
Isah MD, Makusidi MA, Abbas A, Okpapi JU, Njoku CH, Abba AA. Spirometric evaluation of ventilatory function in adult male cigarette smokers in Sokoto metropolis. Niger Postgrad Med J [serial online] 2017 [cited 2020 Nov 28];24:1-7. Available from: https://www.npmj.org/text.asp?2017/24/1/1/205969
| Introduction|| |
Tobacco smoking, despite being a common social habit, is associated with numerous deleterious effects on the body systems and is not limited to the respiratory system. It is a preventable cause of disease and premature death. The World Health Organization has put the number of tobacco smokers at 1.1 billion persons worldwide, which is about one-third of the world population aged ≥15 years. It is reported that tobacco smoking and its related diseases killed about 100 million people worldwide in the 20th century, and estimates show that by 2030, countries in the developing world are expected to have about seven million tobacco smoking-related deaths annually going by the current trend of cigarette smoking.
Cigarette smoke contains nicotine, which is the main addictive ingredient in addition to other complex mixtures of chemical additives.,,, These chemicals, which have been implicated in the deleterious multisystemic effect on the human body, include nickel, chromium, hydrogen cyanide, volatile phenols, and benzopyrene.,,, The single most important risk factor for retarded lung development and accelerated decline in the lung function is cigarette smoking., However, other risk factors that may act in concert with cigarette smoking include airway hyper-responsiveness, air pollution, and occupational exposure to organic and inorganic dust.,
There seems to be a linear relationship between amount of tobacco smoked/duration of smoking and its effect on the respiratory system.,,, Furthermore, participants with significant cigarette smoking history also lose an average of 13.2 years of life because of tobacco smoking. However, the morbidity and mortality attributable to tobacco smoking tend to be underestimated, because it is sometimes cited as a contributory or aggravating factor rather than a primary cause of disease and death.
Spirometric evaluation of the lung’s function is a process dating back to the 17th century. Spirometry is a test that measures the airflow and the lung volumes during inspiratory and expiratory maneuvers from full expiration and inspiration, respectively. Spirometry has been attested as one of the investigations of choice for the detection of both subclinical and clinical effects of tobacco smoking on the airway.
Tobacco smokers usually progress slowly from normal spirometry to borderline ventilatory function defect and then to unequivocal ventilatory function defect. These ventilatory function changes are as a result of inflammation, immune response, and scarring in the airway/lungs of the cigarette smokers exposed to its noxious particles and gases. The onset of symptomatic phase of ventilatory function defect in tobacco smokers is variable, but often does not occur until FEV1 has fallen to 50% or less than the predicted normal value or the patient’s best recorded value. Intriguingly, not every cigarette smoker develops ventilatory dysfunction even with significant exposure. However, spirometric evaluation among the cigarette smokers is one way through which ventilatory function defect could be detected early and cigarette smoking cessation advocated.,,,
There are few published studies that sought to evaluate ventilatory function among the cigarette smokers in Nigeria.,, There is lack of data on ventilatory function among the adult cigarette smokers in Sokoto metropolis, and hence, the need for this study. The result from this study was expected to reveal the level of ventilatory dysfunction among the cigarette smokers and further highlight the need for spirometric screening among the cigarette smokers for the early detection of its deleterious effect on the airway. In addition, the study particularly was of importance as it was a pioneer study from northwest Nigeria. Furthermore, this study would benefit the study participants, especially the cigarette smokers, who are vulnerable to ventilatory dysfunction, as they would get to know the functional state of their airway and thereby be encouraged to quit.
| Subjects and Methods|| |
It was a comparative, descriptive cross-sectional study that employed stratified random sampling technique to consecutively enroll consenting participants and controls who fulfilled the inclusion criteria.
Sokoto metropolis is formed by Sokoto North (SN) Local Government Area (LGA), Sokoto South (SS) LGA, and Wamakko (WK) LGA with a population of 232,846, 194,914, and 179,619, respectively. Six cigarette selling points (2 per LGA) in Sokoto metropolis were randomly chosen as sites for recruitment of the study participants.
The sample size for the study was determined by using the Fisher’s formulae on cigarette smoking prevalence among males, standard normal deviate at 95% confidence interval, and level of precision of 9%, 1.96, and 0.05, respectively (n = Z2pq/d2 = (1.96)2 × 0.09 × 0.91/(0.05)2 = 126). Furthermore, the estimated sample size was scaled up (to cover for incomplete and improperly filled questionnaire and incomplete response from the participants and the individuals unable to perform spirometry), and participant–control ratio of 3:1 was chosen to arrive at a sample size of 150 participants and 50 controls. The distribution of the participants and controls was proportionate to the population of the local government area that made up Sokoto metropolis (SN: 58 participants and 19 controls, SS: 48 participants and 16 controls, WK: 44 participants and 15 controls).
The participants (all males) for the study were aged 18–60 years. Current cigarette smokers that patronized the selected cigarette selling points and were without chest deformity, illness(es), or previous cardiothoracic surgery that would hinder the performance of spirometry were selected as the participants. The control for the study was age group matched, apparently healthy, never cigarette smokers who were in the company of the participants or lived in the vicinity of the cigarette selling points. The participants were identified while smoking a cigarette; on the other hand, controls were those age group matched participants with no cigarette smoking history.
A questionnaire adapted from the European Community Respiratory Health Survey questionnaire and had been pretested was administered by the researcher (face-to-face interview with the participants/control) to retrieve and document relevant data on the participants’ demography, cigarette smoking history, pack-years smoked, smoking index (smoking index criteria, i.e., product of number of cigarette/day and duration in years), and clinical evaluation (reporting of the symptoms).
Weight (using Hana Mechanical Weighing Scale, model BR9012) and standing height (using Seca Freestanding Mobile Stadiometer) were measured to the nearest 0.1 kg and 0.1 m, respectively. Spirometry was performed according to the American Thoracic Society guideline using Clement Clarke (One Flow) Spirometer, version 1.3 with the participants being asked to abstain from smoking at least one hour before the procedure. The participants were then asked to sit comfortably in a chair, and the complete process of spirometry was explained and demonstrated to the participants and all doubts if any were clarified. The participants were instructed to lift their chin, extend their neck slightly, and then breathe in fully. The study participants also had their nostrils closed by a nose clip, after which the lips were sealed around the sterile mouthpiece of the spirometer. The participant then forcefully blew air out as fast and as completely as possible through the mouth. The best of three readings of the various lung volumes and flow data (FVC, FEV1, and FEV1/FVC) taken five minutes apart was recorded, and a post-bronchodilator spirometry was performed on the participants with ventilatory function defect (obstructive and/or restrictive defect) to quantify the degree of reversibility. Spirometry was performed by the researcher in the mornings between 7:00 am and 11:00 am throughout the data collection period.
Approval from the Health Research and Ethics Committee of Usmanu Danfodiyo University Teaching Hospital, Sokoto was obtained on 23rd August, 2013 (ref. no.: UDUTH/HREC/2013/NO 36) before the commencement of the study, and informed consent was sought from the study participants. The data for this study were collected from 1st September, 2013 to 28th February, 2014.
Data from the questionnaire were recorded and analyzed using Statistical Package for Social Sciences, version 19 (IBM SPSS version 19, SPSS Inc., Chicago, IL 60606-6307, USA) software. The mean and standard deviation were calculated for age, weight, height, body mass index (BMI), FEV1, FVC, and FEV1/FVC. Frequencies and percentages were presented for the smoking index. Independent sample t-test was used to compare significance for numerical variables at P < 0.05. Pearson product moment correlation coefficient was used to examine the relationship between pack-years of cigarette smoking and FEV1. Multiple linear regressions were performed to determine the predictors of decline in FEV1 from among independent variables, which included age, pack-years, and smoking index.
| Results|| |
One hundred and twenty (80.0%) participants and 34 (68.0%) controls were aged 40 years or below. One hundred and twenty-seven (84%) study participants and 38 (76%) controls were employed. Commercial motorcyclists (40% of participants and 20% of controls) and civil servants (29.4% of participants and 30% of controls) constituted the two largest occupational groups. Only two (1.3%) cigarette smokers had symptoms (chronic cough, dyspnea, chest pain, and wheezing) referable to the respiratory system. The clinical and sociodemographic characteristics of participants and control were not significantly different [Table 1].
|Table 1: Clinical and sociodemographic characteristics of the study participants and the controls|
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Cigarette smokers and nonsmokers did not differ in mean age, height, weight, and BMI [Table 2]. Similarly, there was no statistical significant difference in age between the participants and controls with mean age of 34.3 (8.91) years versus 35.1 (10.35) years, respectively. Comparison of the mean values of ventilatory function test indices showed all except FVC to be reduced in the cigarette smokers. According to [Table 2], FEV1/FVC was statistically significant between the participants and controls (P < 0.001).
|Table 2: Clinical parameters, spirometric indices, and ventilatory function of the study participants and the controls|
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The mean age of cigarette smoking habit commencement was 16.9 (4.17) years. The mean pack-years and cigarette smoking index were 8.71 and 163.98, respectively. Number of cigarettes smoked daily increased from the initial value of 3.69 to the current value of 13.29. Other smoking characteristics among the study participants were as displayed in [Table 3].
There was a negative correlation between pack-years and FEV1 (r = −0.237 and P = 0.004) as depicted in [Figure 1]. Multiple linear regression analysis showed that age was the statistically significant independent predictor of FEV1 decline (P = 0.019) [Table 4].
| Discussion|| |
This study revealed that the male cigarette smokers in Sokoto metropolis were predominantly (80%) aged 40 years or younger. This might be because of early indulgence in cigarette smoking habit and more patronage of cigarette selling points by adolescents/young adults rather than the middle-aged/the elderly, who probably got their cigarettes by sending others on errand to buy on their behalf., Our finding was similar to that of Hammad et al., who also had a significant proportion of their study participants below 40 years of age. Similarly, even nonpopulation-based studies that deployed probability sampling technique revealed age pattern comparable to that in our study.
Civil servants (among nonsmokers) and commercial motorcyclist (among smokers) were the dominant occupations of the study participants. This observation might be connected with the urban setting of data collection and the timing of data collection (morning), as this time of the day was when most civil servants were on the way to their working places and commercial motorcyclists made brisk business because of the high turnout of commuters. Even though, the index study did not aim to evaluate effect of occupation on ventilatory function, previous studies have found cigarette smoking to be prevalent among Civil servants and Commercial motorcyclist, with these groups of workers civil servant and commercial motorcyclist) not having a significant risk for development of ventilatory dysfunction owing to their jobs.,,, Hammad et al. recruited participants who were all employed and were predominantly laborers, shopkeepers, and farmers. However, there was no mention of how their occupation could have impacted their ventilatory function, even though physical activity is known to impact ventilatory function. In another study by Al Omari et al., 65 (12.7%) of the recruited participants had an occupation that was risky for development of chronic obstructive pulmonary disease but failed to give details of their jobs.
There was no significant difference in the mean age and mean anthropometric indices indicating a proper matching in this study. The mean age of cigarette smokers and nonsmokers in this study was similar with those in the study by Harkirat et al., which aimed at determining the relationship between cigarette smoking and pulmonary function. The participants in some related studies were much older than those in our study.,,, These variations may not be unconnected to the differing sampling technique adopted in each study.
In this study, a decline in all ventilatory function test indices was noted among the cigarette smokers when compared with the noncigarette smokers except for FVC. However, only the difference between FEV1/FVC among the participants and the control was statistically significant. This finding is comparable with that by Jaya et al. in India. Toshio and Toshihiko and Nancy et al. also found no significant difference in the values of FVC between the cigarette smokers and the nonsmokers. Furthermore, Toshio and Toshihiko found that cigarette smoking did not make significant contribution to FVC decline especially in those who were asymptomatic, and this was in agreement with our finding. In contrast, studies by Babatunde et al., Sunita and Abhijit, Rubeena et al., and Ritesh et al. found all spirometric indices to be significantly higher in the noncigarette smokers when compared to the cigarette smokers. These findings reaffirm the effect of cigarette smoking on the airway and ventilatory function.
In the context of the Global Initiative for Chronic Obstructive Lung Disease criteria for categorization of spirometric indices result, majority (96%) of our study participants could be considered as not having ventilatory dysfunction. This percentage of participants with normal ventilatory function was higher when compared with findings from studies of Babatunde et al., Sunita and Abhijit, and Rubeena et al. Obstructive ventilatory dysfunction was the predominant ventilatory dysfunction pattern found in this study, which agreed with the findings of Sunita and Abhijit and Rubeena et al. The pattern of ventilatory function test indices in our study might largely be attributable to the fact that most of the participants were young with low mean pack-years and cigarette smoking index.
The prevalence of undiagnosed ventilatory dysfunction among the study participants from this study was 4% in both the study participants and the control. The symptomatic study participants (1.3%) were among those with abnormal ventilator function. Wisnivesky et al. reported a lower prevalence (2.3%) of undiagnosed ventilatory dysfunction. However, a higher prevalence of 12.6 and 5.7% was recorded by Barthwal and Singh and Nabeel et al., respectively. Toshio and Toshihiko attributed the 6.3% ventilatory dysfunction found among Japanese workers in their study to be low, and reasoned that it was probably because of selection bias. The result of ventilatory function pattern in the current study might be explained by the large number of young study participants having low mean pack-years and probably being in their early phase of airway changes.
A linear relationship was found between FEV1 and pack-years in earlier studies.,, This study corroborated this fact with a weak negative correlation (r = −0.237) between pack-years and FEV1, which probably could be explained by the low mean pack-years and concomitant early airway changes. In the same vein, negative correlation was observed by Paula et al., Sumangala et al., and David and Meir.
The most important independent variable that determines ventilatory function test indices for normal healthy individuals are age and height. Multiple linear regression from this study suggested that only age was the significant predictor of decline in FEV1 among the current cigarette smokers (P = 0.019). Our finding might not be unrelated with relatively low mean pack-years of cigarette smoking among the study participants. Paula et al. in their study also found age among other factors to be a better explanatory factor for lowered FEV1 than pack-years.
| Conclusion|| |
Cigarette smoking is associated with decline in ventilatory function. There is a direct relationship between decline in ventilatory function and duration and quantity of cigarettes smoked (pack-years and smoking index). Spirometry is a valuable technique for the detection of ventilatory dysfunction among the cigarette smokers. Cigarette smokers should undergo spirometry for early diagnosis of ventilatory dysfunction, and irrespective of spirometric result, they should be encouraged to quit.
This work is a part of a dissertation for the fellowship of the National Postgraduate Medical College of Nigeria. I thank Professor S.A. Isezuo, Dr. H.M. Liman, and Dr. A.S. Maiyaki for their help and suggestions.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Yebpella GG, Oladipo MO, Magomya AM, Abechi SE, Udiba UU, Kamba EA. Multi-element analysis of selected brands of cigarettes in Nigerian market. Arch Appl Sci Res 2013;5:61-7.
Iwegbue CM, Nwajei GE, Eguavon O. Metal distribution in some brands of cigarette ash in Nigeria. J Environ Sci Eng 2009;51:93-6.
Yebpella GG, Shallangwa GA, Hammuel O, Magonya A, Oladipo MO, Nok AN et al.
Heavy metal control of different brand of cigarettes commonly smoked in Nigeria and its toxicological implications. Pac J Sci Technol 2011;12:356-62.
Awotedu AA, Higenbottam TW, Onadeko BO. Tar, nicotine and carbon monoxide yield of some Nigerian cigarettes. J Epidemiol Community Health 1983;37:218-20.
Global Initiative for Chronic Obstructive Lung Disease. Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease; 2006. Available from: http://www.goldcopd.org/guidelineitam.asp
. [Last accessed on 2012 Aug 20].
Gilliland F, Berhane K, McConnell R, Gauderman W, Vora H, Rappaport E et al.
Maternal smoking during pregnancy, environmental tobacco smoke exposure and childhood lung function. Thorax 2000;55:271-6.
Anong T, Premtip T. Effects of smoking on chest expansion, lung function, and respiratory muscle strength of youths. J Phys Ther Sci 2014;26:167-70.
Mussavir HB, Syed Badshah HZ, Syed Mohammad AZ, Imran K. Use of spirometry in detecting airway obstruction in asymptomatic smokers. Pak Armed Forces Med J 2010;3:1-6.
Stang P, Lydick E, Silberman C, Kempel A, Keating ET. The prevalence of COPD: Using smoking rates to estimate disease frequency in the general population. Chest 2000;117:354S-9S.
Xu X, Dockery DW, Ware JH, Speizer FE, Ferris BG Jr. Effects of cigarette smoking on rate of loss of pulmonary function in adults: A longitudinal assessment. Am Rev Respir Dis 1992;146:1345-8.
Naresh R, Makwana V, Shahi R, Yadav S. A study on prevalence of smoking & tobacco chewing among adolescents in rural areas of Jamnagar district, Gujarat state. J Med Res 2007;1:47-9.
Akanbi MO, Akanbi FO, Malu A, Okoli CO. Ventilatory function and cigarette smoking in cement handlers in North Central Nigeria: A cross-sectional study. J Med Trop 2012;14:19-25.
John H. On the capacity of the lungs, and on the respiratory function, with a view of establishing a precise and easy method of detecting disease by the spirometer. Med Chir Trans 1846;29:137-252.
Charlotte SU, Anders L, Ronald D, Jens D, Gert H, Patrick HC et al.
On behalf of the TOP study group. Early detection of COPD in general practice. Int J Chron Obstruct Pulmon Dis 2011;6:123-7.
Hammad AQ, Jamil AS, Tahira KS, Fahmida AS, Fahira R, Anjum H. Spirometric screening of chronic obstructive pulmonary disease in smokers presenting to tertiary health care. J Med 2009;10:40-4.
Paula R, Timo H, Vuokko K. The use of microspirometry in detecting lowered FEV1
values in current or former cigarette smokers. Prim Care Respir J 2008;17:232-7.
Kerstjens HA, Rijcken B, Schouten JP, Postma DS. Decline of FEV1
by age and smoking status: Facts, figures and fallacies. Thorax 1997;52:820-7.
Rexhepi AM, Brestovci B. Influence of smoking and physical activity on pulmonary function. Internet J Pulm Med 2010;11:1-2.
Georgios S, Per J, Siguard M, Olle Z. Early detection of COPD in primary care: Screening by invitation of smokers aged 40 to 55 years. Br J Gen Pract 2004;54:201-6.
Zieliñski J, Bednarek M; Know the Age of Your Lung Study Group. Early detection of COPD in a high risk population using spirometric screening. Chest 2001;119:731-6.
Grzetic-Romcevic T, Devcic B, Sonc S. Spirometric testing on World COPD day. Int J Chron Obstruct Pulmon Dis 2011;6:141-6.
Barış SA, Yıldız F, Başyiğit I, Boyacı H, Ilgazlı A. Prevalence of smoking and chronic obstructive pulmonary diseases amongst teachers working in Kcaeli, Turkey. Multidiscip Respir Med 2011;6:92-6.
Muhammad BA, Emmanuel OB. The effect of cigarette smoking on pulmonary function and respiratory symptoms on Nigerian firefighters. Meeting abstract. Chest 2008;134:17003.
Babatunde OA, Ayodele AA, Adekemi EA. Effects of tobacco smoking on pulmonary function indices among undergraduate students. Niger J Med Rehabil 2015;18:1-14.
American Thoracic Society. Lung function testing: Selection of reference values and interpretative strategies. Am Rev Respir Dis 1991;144:1202-18.
Raji MO, Abubakar IS, Oche MO, Kaoje AU. Prevalence and determinants of cigarette smoking among in school adolescent in Sokoto metropolis, North West Nigeria. Int J Trop Med 2013;8:81-6.
Awosan KJ, Ibrahim MT, Sabir AA, Ejimoden P. Awareness and prevalence of risk factors of coronary heart disease among teachers and bankers in Sokoto, Nigeria. J Med Med Sci 2013;4:335-42.
Hani AN, Shalabia AA, Dua’a FM. Pulmonary function test: The value among smokers and nonsmokers. Health Sci J 2012;6:703-13.
Abisola MO, Olufunmilayo F, Patrick N, Peter N. Prevalence and factors associated with hypertension and obesity among civil servants in Kaduna, Kaduna State, June 2012. Pan Afr Med J 2014;18:13.
Olukunmi LO, Oyesegun OO, Olufunmilola LD. Incidence of lifestyle associated health risk among executives in Southwestern Nigeria. J Nat Sci Res 2013;3:59.
Abiodun OA, Olu-Abiodun OO, Oluwale FA. The pattern of cigarette smoking among commercial motorcyclist in semi-urban town in Nigeria. Appl J Hyg 2012;1:8-14.
Gathuru IM, Bunker CH, Ukoli FA, Egbagbe EE. Differences in rates of obstructive lung disease between Africans and African Americas. Ethn Dis 2002;12:S3-107-13.
Al Omari M, Khassawneh BY, Khader Y, Dauod AS, Bergus G. Prevalence of chronic obstructive pulmonary disease among adult male cigarettes smokers: A community based study in Jordan. Int J Chron Obstruct Pulmon Dis 2014;9:753-8.
Harkirat K, Richa GT, Sukhjinder KD, Saahiba K. Relationship between smoking and pulmonary function. NJIRM 2011;2:1-6.
Younus M, Choudhry MK, Syed ZA, Mushtaq W. Role of spirometry in the early diagnosis of chronic obstructive pulmonary disease in smokers. Available from: http://www.pjcm.net/pdf-v16-n2-p3
. [Last accessed on2014 Aug 30].
Toshio N, Toshihiko S. A longitudinal study on the effect of cigarette smoking on rate of decline in spirometric measurements in male Japanese workers. J Epidemiol 1995;5:59-65.
Sunita N, Abhijit A. A study of pulmonary function test among smokers and non smokers in a rural area of Gujarat. J Clin Diagn Res 2011;5:1151-3.
Rubeena B, Mahagaonkar AM, Kulkami NB, Nadeem A, Nighute S. Study of pulmonary function tests among smokers and non-smokers in a rural area. Pravara Med Rev 2009;4:11-6.
Jaya MG, Kalyani S, Raveendran C. Evaluation of the effect of smoking on pulmonary function in young healthy adults. IJBR 2014;5:359-63.
Nancy NR, Rai UC. Study of forced expiratory spirogram in South Indian beedi smokers and cigarette smokers. Indian J Chest Dis Allied Sci 1983;25:25-30.
Ritesh MK, Prandya AG, Hemant BM. Comparative study of spirometric parameters between active tobacco smokers and tobacco non-smokers. IOSR J Pharm 2012;2:222-4.
Wisnivesky J, Skloot G, Rundle A, Revenson TA, Neugut A. Spirometry screening for airway obstruction in asymptomatic smokers. Aust Fam Physician 2014;43:463-7.
Barthwal MS, Singh S. Early detection of chronic obstructive pulmonary disease in asymptomatic smokers using spirometry. J Assoc Physicians India 2014;62:238-42.
Nabeel M, Suleman HA, Bushra M, Muhammad I. The efficacy of spirometry as a screening tool in detection of air flow obstruction. Open Respir Med J 2010;4:71-5.
Sumangala MP, Mahesh JP, Manjunath A, Nilima ND. Reduction of spirometric lung function test in habitually smoking healthy young adults: Its correlation with pack years. JKIMSU 2012;1:89-94.
David S, Meir R. Prevalence of chronic obstructive pulmonary disease among smokers aged 45 and up in Israel. Isr Med Assoc J 2007;9:800-2.
Oloyede IP, Ekrikpo UE, Ekanem EE. Normative values and anthropometric determinants of lung function indices in rural Nigerian children: A pilot survey. Niger J Paediatr 2013;40:406-11.
[Table 1], [Table 2], [Table 3], [Table 4]
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