Home About us Editorial board Ahead of print Browse Articles Search Submit article Instructions Subscribe Contacts Login 
  • Users Online: 2833
  • Home
  • Print this page
  • Email this page


 
Previous article Browse articles Next article 
ORIGINAL ARTICLE
J Res Med Sci 2022,  27:18

Association of demographic variables and smoking habits with the severity of lung function in adult smokers


1 Acquired Immunodeficiency Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
2 Department of Internal Medicine, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

Date of Submission26-Sep-2021
Date of Decision07-Nov-2021
Date of Acceptance15-Nov-2021
Date of Web Publication18-Feb-2022

Correspondence Address:
Dr. Somayeh Sadeghi
Department of Internal Medicine, School of Medicine, Isfahan University of Medical Sciences, Isfahan
Iran
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jrms.jrms_854_21

Rights and Permissions
  Abstract 


Background: This study aims to evaluate the association between demographic and smoking variables with the severity of lung function loss (Stage I to IV) and spirometry data in smokers. Materials and Methods: Three hundred and fifty smoker men over the age of 20 who had visited in AL-Zahra hospital were involved. Spirometry tests were performed for measuring forced vital capacity (FVC), FEV1, and FEV1%FVC. COPD was categorized into four stages by the (Global Initiative for Chronic Obstructive Lung Disease) criteria of postbronchodilator FEV1/FVC <0.70. FEV1/FVC <70%, in combination with FEV1 ≥80% (Stage I), or 50%≤FEV1 <80% (Stage II), or 30%≤FEV1 <50% (Stage III), or FEV1 ≤30% (Stage IV). Independent t-test, Spearman correlation analysis was used for data analysis. To determine the predicting factors for pulmonary function multiple regressions analysis was performed. Results: 43 (19.5%) of men were defined as Chronic Obstructive Lung Disease (COPD) which 7% of them were Stage I, 23.3% were Stage II, 39.5% were III and 30.2% were stage IV. In 60 (27.1%) of men, the index of Fev1/FVC was <80%. The criteria of PRIS in 74 (33.5%) of the patients and BDR in 59 (26.7%) of participation was positive. There were significant differences in the mean of FEV1 with respect to history of lung disease in relatives (P = 0.035), lung disease hospitalization (P < 0.001) and previous diagnosis of asthma variables (P < 0.001). The mean of FVC was significantly different in patients categorized based on lung disease hospitalization (P < 0.001) and previous diagnosis of asthma (P = 0.018). Furthermore, there was a significant difference in the mean of FEV1/FVC for variables as follows: Time to start smoking after waking up (P = 0.007), lung disease hospitalization (P < 0.001) and previous diagnosis of asthma (P < 0.001). There was a significant association between stages of lung function loss and age of onset of smoking (β-0.355 P = 0.019) and pack per year (β = 0.354 P = 0.02). A linear regression model showed that lung disease hospitalization and age were the influential variables on FEV1 with (B = −21.79 confidence interval [CI]: −28.7, −14.87, P < 0.001and B = −0.418 CI: −0.63, −0.21, P < 0.001), respectively. The only significant influential variable on FVC was lung disease hospitalization (B = −15.89 CI: −21.49, −10.296, P < 0.001). Body mass index, lung disease hospitalization, time to start smoking after waking up in the morning and age had significant relationship on FEV1/FVC with (B = 0.71CI: 0.32, 1.11, P < 0.001, B = −14.29, CI: −19.61,-8.97, P < 0.001, B = 6.54, CI: 2.26, 10.82, P = 0.003 and B = −0.44, CI: −0.59, −0.28, P < 0.001), respectively. Conclusion: The age of onset of smoking and pack-year appears to be associated with the severity of COPD. Hospitalization history due to lung disease, age, the time between waking up in the morning and first cigarette use, BMI, lung disease history in relatives, previous diagnosis of asthma have a negative relationship with lung function.

Keywords: Demography, respiratory function tests, smoking


How to cite this article:
Toghyani A, Sadeghi S. Association of demographic variables and smoking habits with the severity of lung function in adult smokers. J Res Med Sci 2022;27:18

How to cite this URL:
Toghyani A, Sadeghi S. Association of demographic variables and smoking habits with the severity of lung function in adult smokers. J Res Med Sci [serial online] 2022 [cited 2022 Sep 24];27:18. Available from: https://www.jmsjournal.net/text.asp?2022/27/1/18/337902




  Introduction Top


The main reason for chronic obstructive pulmonary disease is smoking.[1],[2] COPD is a chronic lung disease characterized by persistent airflow restriction. COPD is a progressive disease and is caused by a combination of small airway diseases and parenchymal damage, commonly called emphysema.[3] The prevalence of COPD worldwide is estimated at 210 million.[4]

COPD is a leading cause of morbidity and has even been estimated as the third leading cause of death in 2010.[5] Spirometry is the most common test of lung function in the diagnosis and monitoring of COPD.[6] According to the Global Initiative for Chronic Obstructive Pulmonary Disease, a postbronchodilator FEV1/forced vital capacity (FVC) <0.70 confirms the presence of COPD and is an essential element in the diagnosis of COPD.[3] Postbronchodilator spirometry is not only required when detecting COPD; it is also an essential tool in assessing the severity of COPD because the classification of severity of airflow limitation in COPD is based on postbronchodilator FEV1.[3] Previous studies showed that smoking reduces pulmonary function, including FVC, forced expiratory volume per second (FEV1), and FEV1/FVC.[7] The use of FEV1/FVC is a traditional amount of obstruction in airways to detect airways obstruction during spirometry testing.[8] Smoking burden is regularly measured in pack-years, a product of the average number of packs of cigarettes smoked a day and smoking length in years.[9] Walter et al. detailed that more seasoned smokers with histories of expansive numbers of pack-years had lower FVC levels than nonsmokers, whereas youthful adult smokers had FVC levels similar to or higher than age-equivalent nonsmokers.[10] A study of 100 male smokers, age ranging from 18 to 60 years appeared that those who smoked more than 10 pack-year are related with accelerated decrease in lung function.[11] Smoking duration and participant's age might unfavorably influence lung capacity by declining the FVC and FEV1 test. On the other hand, nonsignificant correlation was found between the number of cigarettes smoked per day and lung function parameters FVC and FEV1.[12] In addition to smoking, history of respiratory diseases in the family, poor financial status, aging, body mass index (lower BMI), age, regular of hookah use, and history of seasonal allergies are other risk factors for COPD.[13],[14]

Few studies also have reported the association between lung function loss and a range of smoking burdens consisting of demographic and nondemographic factors in smoking patients.[15],[16]

In this cross-sectional study, we evaluated the association of demographic variables and smoking habits with the severity of lung function and spirometry data in adult smokers visiting the Al-Zahra Hospital of Isfahan University.


  Methods Top


Design and population

This cross-sectional study was performed in AL Zahra hospital, the main referral hospital of Isfahan University of Medical Sciences from November 2019 to April 2020. This study was approved in Isfahan University of medical sciences with ethics code IR.MUI.MED.REC.1398.710.

There were originally 350 men smokers over the age of 20 who had visited AL Zahra hospital, however, 129 participants were removed according to the exclusion criteria of this study. Therefore, 221 participants were involved in this study. Each participant signed a self-written consent to take part in the study. The exclusion criteria of the study were as followed: (a) presence of acute Respiratory Infection, (b) presence of lung disease counting lung cancer, interstitial lung disease, Tuberculosis, Neuromuscular Disorders, Pneumothorax, (c) unable to perform technically acceptable respiratory function tests.

All participants filled out a checklist requesting information on demographic data, smoking habits, and a history of diseases and respiratory symptoms. And then, they were tested for their lungs function. The demographic data included age, level of education (Illiterate, High school, Diploma, Associate Degree, Bachelor's, Master's degree), and BMI. The following variables of smoking habits were also recorded in the checklist including the age of the onset of smoking, duration of smoking (years), number of cigarette packs consumed daily, pack-year (was defined as the number of years of daily smoking multiplied by the number of cigarettes smoked daily divided by 20,[9] amount of time between getting up in the morning and the first cigarette. Other requesting information were questions with yes/no answers including the use of hookah, addiction, a history of chronic lung disease in first-degree relatives, seasonal allergies, previous lung disease hospitalizations, and previous diagnosis of asthma

Pulmonary function assessment

Spirometry was performed before and 15 min after 400 micrograms of salbutamol managed by a trained technician in accordance with the American Thoracic Society (ATS) and European Respiratory Society standards.[17] While the participants were sitting they were asked to make a forced exhalation followed by a forced inhalation. FVC, forced expiratory volume in1s (FEV1), and FEV1 percent in relation to the maximal FVC (FEV1%FVC) were registered. FVC was characterized as the biggest of either forced expiratory or forced inspiratory vital capacity from technically acceptable curves. The reported FEV1 is considered to be a good biological marker of the risk of obstructive pulmonary disease. If the Spirometric quality was not satisfactory, the maneuver would be repeated until the best quality was obtained. The highest value of FVC and the highest value of FEV1 were selected from the measurements for which the repeatability criteria were met. A pulmonologist reviewed the quality of all the tests. Bronchodilator responsiveness (BDR) was calculated change of >12% of the baseline forced expiratory volume in 1 s (FEV1) if this also exceeds 200 mL according to ATS guidelines.[18] COPD was defined by the Global Initiative for Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria of postbronchodilator FEV1/FVC <0.70. FEV1/FVC <70%, in combination with FEV1 ≥80% (Stage I), or 50%≤FEV1 <80% (Stage II), or 30%≤FEV1 <50% (Stage III), or FEV1 ≤30% (Stage IV).[19] Participants with normal ratio but postbronchodilator FEV1 <80% predicted were categorized to have the GOLD unclassifiable disease or Preserved Ratio Impaired.[20] Postbronchodilator FEV1/FVC <80% were predicted to be considered unclassifiable airway obstruction.[21] For evaluation of bronchodilator response (BDR), we used ATS guidelines (post FEV1– preFEV1/preFEV1 × 100 more than 12%).

Statistical analysis

Data are presented as mean (standard deviation) or frequency (percent). For comparing the mean of pulmonary functions in categories of variables, independent t-test is used. Spearman correlation analysis was performed to get the association between the severity of long loss and study variables. Further analysis using multiple regressions was conducted to confirm the predictors of the pulmonary functions. The level of significance is taken as P < 0.05. Statistical analysis was conducted using the SPSS software version 16 (SPSS Inc., Chicago, Illinois, USA).


  Results Top


Two hundred and twenty-one men participated in the study. -Forty-three men (19.5%) had COPD so most of them were in stage III [Table 1]. In 27.1% of men, the index of FEV1/FVC was <80%. The criteria of PRIS in 74 (41.6%) were positive. BDR was positive in 59 (26.7%) of participation 53 (24.0) of participants were used short-acting beta-agonist inhalers, 16 (7.2) used long-acting muscarinic antagonist, 27 (12.2) used short-acting muscarinic antagonist, 2 (0.9) used inhaled corticosteroids and 16 (7.2) used long-acting beta-agonist and inhaled corticosteroids.
Table 1: The information of studied patients

Click here to view


The mean of FEV1, FVC, and FEV1/FVC after use of bronchodilator with respect to different categorization is shown in [Table 2]. The mean of FEV1 for men without a history of lung disease in relatives (P = 0.035), without lung disease hospitalization (P < 0.001), without previous diagnosis of asthma (P < 0.001) was significantly more than others. Also the mean of FVC between categories of variables lung disease hospitalization (P < 0.001), without previous diagnosis of asthma (P = 0.018) was statistically different. Finally the mean of FEV1/FVC for men who started smoking after waking up in the morning after 30 min (P = 0.007), without lung disease hospitalization (P < 0.001), without previous diagnosis of asthma (P < 0.001), was more and according to independent t-test these differences were statistically significant.
Table 2: Comparison of the mean of spirometery data in patients with respect to different categories of variables

Click here to view


The relationship between stages of lung function loss and other variables in the study, is shown in [Table 3]. According this table there was a significant association between stages of lung function loss and age of onset of smoking (β = −0.355 P = 0.019) and pack per year (β = 0.354 P = 0.02). When the age of onset smoking decreases, the stages of lung function loss increases. Also when the pack per year increases the stages of lung function loss increase.
Table 3: Correlation between stages of chronic obstructive lung disease and studied variables

Click here to view


We used linear regression model for evaluating the effect of study variables on FEV1, FVC, and FEV1/FVC. FEV1, FVC, and FEV1/FVC were dependent variables. At first, we entered all variables in each model. Then, we used Hosmer et al. (2013) method to the selection of significant variables. The information of the final three models are in [Table 4]. In first model, lung disease hospitalization and age were the influential variables on fev1 with (B = −21.79 CI: −28.7, −14.87 P < 0.001 and B = −0.418 CI: −0.63, −0.21 P < 0.001), respectively. With regards to B coefficients when age increases the FEV1 decreases and there was an inverse relationship between the lung disease hospitalization and FEV1.
Table 4: linear regression models for determining factors predicted the forced expiratory volume1, forced vital capacity, and Forced expiratory volume1/forced vital capacity

Click here to view


The only significant influential variable on FVC were lung disease hospitalization and there was an inverse relationship between this variable and FVC (B = −15.89 CI: −21.49, −10.296 P < 0.001).

In model 3, BMI, lung disease hospitalization, Time to start smoking after waking up in the morning and Age had a significant relationship on FEV1/FVC. B coefficients for BMI, hospitalization history, and time to start smoking after waking up in the morning age was (B = 0.71 CI: 0.32, 1.11, P < 0.001, B = −14.29, CI: −19.61, −8.97, P < 0.001, B = 6.54, CI: 2.26, 10.82 P = 0.003, and B = −0.44, CI: −0.59, −0.28 P < 0.001) respectively. When BMI increase and age decreases and the mean of FEV1/FVC increases. Furthermore, there were a negative association between FEV1/FVC and lung disease hospitalization.

Entered variables

Education, time to start smoking after waking up in the morning, Hookah, History of lung disease in relatives, Allergies, lung disease hospitalization, Asthma, Saba: Short-acting beta-agonist, Lama: Long-acting muscarinic antagonist, Sama: Short-acting muscarinic antagonist, Icslaba: Inhaled corticosteroids and long-acting beta-agonist, Ics inhaled corticosteroids, Addiction, Age, BMI, Age of onset of smoking, Pack year


  Discussion Top


In this cross-sectional study of a population of male adult smokers, we found that age of onset of smoking and pack-year was closely associated with the severity of lung function loss The present study demonstrates that the mean of onset of smoking was 16.54 (6.01) in Stage IV, 23.12 (8.06) in Stage III, 23.30 (6.41) in Stage II, and 18[2] in Stage I of COPD smokers. This means that the age of onset of smoking is connected to poorer pulmonary function. Furthermore, the smokers on Stage IV of COPD had the mean pack-years of 65.19 (33.64), Stage III with the mean of 42.48 (18.96), Stage II with the mean of 41.05 (26.28), and Stage I with the mean of 35.[7] It was found that more smoking measured as pack-year was associated with poorer pulmonary function. The impact of cigarette smoking on lung function is dose dependent, so it is expected that the sooner smoking begins the worse the lung function becomes. A finding that seems to be of secondary importance is that people who started smoking earlier are more likely to continue smoking and are heavier smokers.[22] Kurmi et al. examined the relationship between smoking and airway obstruction in men and women found that airway obstruction was strongly associated with smoking and the onset of smoking at an early age. In both sexes, the OR was more extreme in those who started to smoke at a younger age (P < 0.0001 in men and 0.0063 in women).[23] A previous study by Ballah, et al. that compared the lung function between smokers and nonsmokers indicated that there is a statistical relationship between pack-year of smoking and FEV1 levels. They also found out that the onset of smoking at a younger age is associated with a lower value of FEV1.[24] A study was also conducted involving 10,187 participants that showed a significant correlation between airflow obstruction (FEV1/FVC) and pack-year (regression coefficient β = −0.023 ± SE0.003; P = 0.003).

The present study demonstrates that The mean of FEV1, FVC andFEV1/FVC for smokers without previous diagnosis of asthma and without any history of pulmonary disease hospitalization was significantly higher compared to smokers with these variables according to independent t-test. Accordingly, the linear regression model to evaluate the effect of study variables on FEV1, FVC, and FEV1/FVC showed that the history of hospitalization for pulmonary diseases in the present study is inversely related to FEV1, FVC, and FEV1/FVC. Hunter, et al. examined the risk factors for subsequent admission to COPD and found that prior admission to COPD or respiratory disease was a risk factor that agrees with the present study.[25] Prognosis in patients with COPD indicated that Increasing age, low BMI, decreased FEV1, and prior respiratory or cardiovascular admission hospitalization were predictors of poor outcome.[26] Polese et al. Evaluated the lung function, and pulmonary diffusion for carbon monoxide (DLCO) in patients between 15 and 30 days after discharge admission for severe COVID-19 showed a restrictive pattern with a reduction in FVC in 54% of individuals.[27]

Lange, et al. compared lung function in people with asthma and people without asthma who identify themselves as asthmatics, there were substantially greater declines in FEV1 levels over time than those who did not. Subjects with asthma and smokers had a more noteworthy decrease in FEV1 than those without asthma and nonsmokers, respectively.[28] In the current study, the average fev1 level for smokers without a history of lung disease in relatives was significantly higher than smokers with a history of lung disease in relatives. In addition, the mean of FEV1/FVC for smokers who started smoking within 30 min after waking up was significantly higher in comparison with those who started smoking at least 30 min after waking up. Accordingly, linear regression model demonstrated started smoking ≤ 30 min after waking more decreased FEV1/FVC. A recent study indicated that compared to current smokers with a late start of smoking cigarettes, those who smoked their first cigarette at an early age had a higher risk of chronic obstructive pulmonary disease.[29] According to the linear regression model, age was inversely related to FEV1 and FVC as well as BMI as directly related to FEV1/FVC. Rewashed, Rawashdeh et al. calculated the connection between the smoking duration, the number of cigarettes smoked per day, age, and pulmonary function parameters that suggested smoking duration and participant age could reduce the volume associated with the FVC, FEV1.[12] An increase in FEV1/FVC among participants with a high BMI in our study may be due to elasticity loss because of gaining weight has a greater effect on FVC than FEV1.[30] Our results are in contrast to a study that showed that FEV1/FVC was lower in the obese group than in the other groups.[31]


  Conclusion Top


In a population of male adult smokers, age of onset of smoking and pack-year appears to have a strong relationship with the stages of lung function loss. History of pulmonary disease hospitalization, age, amount of time between getting up in the morning and the first cigarette, BMI, history of lung disease in relatives, previous diagnosis of asthma have a negative impact on lung function.

Acknowledgments

This study has been funded by Isfahan University of Medical Sciences. The authors thank the participants of this study for their contributions.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Ruiz CA, Pinedo AR, Guerrero AC, Ulibarri MM, Cristobal Fernández M, Lopez Gonzalez G. Characteristics of COPD smokers and effectiveness and safety of smoking cessation medications. Nicotine Tob Res 2012;14:1035-9.  Back to cited text no. 1
    
2.
Sundblad BM, Larsson K, Nathell L. High rate of smoking abstinence in COPD patients: Smoking cessation by hospitalization. Nicotine Tob Res 2008;10:883-90.  Back to cited text no. 2
    
3.
Kronborg T, Hangaard S, Cichosz SL, Hejlesen O. Increased accuracy after adjustment of spirometry threshold for diagnosing COPD based on pre-bronchodilator FEV1/FVC. Respir Care 2019;64:85-90.  Back to cited text no. 3
    
4.
Bousquet J, Khaltaev N. Global Surveillance, Prevention and Control of Chronic Respiratory Diseases: A Comprehensive Approach. Geneva, Switzerland: World Health Organization 2007. p. 1-146.  Back to cited text no. 4
    
5.
Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V, et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: A systematic analysis for the global burden of disease study 2010. Lancet 2012;380:2095-128.  Back to cited text no. 5
    
6.
Celli BR, Decramer M, Wedzicha JA, Wilson KC, Agustí A, Criner GJ, i. An official American Thoracic Society/European Respiratory Society statement: Research questions in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2015;191:e4-27.  Back to cited text no. 6
    
7.
Kuperman AS, Riker JB. The variable effect of smoking on pulmonary function. Chest 1973;63:655-60.  Back to cited text no. 7
    
8.
Enright PL, Connett JE, Bailey WC. The FEV1/FEV6 predicts lung function decline in adult smokers. Respir Med 2002;96:444-9.  Back to cited text no. 8
    
9.
Bhatt SP, Kim YI, Harrington KF, Hokanson JE, Lutz SM, Cho MH, et al. Smoking duration alone provides stronger risk estimates of chronic obstructive pulmonary disease than pack-years. Thorax 2018;73:414-21.  Back to cited text no. 9
    
10.
Walter S, Nancy NR, Collier CR. Changes in the forced expiratory spirogram in young male smokers. Am Rev Respir Dis 1979;119:717-24.  Back to cited text no. 10
    
11.
Chowdhury NJ, Nessa A, Begum M, Nabi MA, Matin NI. Relationship between pack year and lung function parameters in asymptomatic smokers. Mymensingh Med J 2021;30:509-13.  Back to cited text no. 11
    
12.
Rawashdeh A, Alnawaiseh N. Effects of cigarette smoking and age on pulmonary function tests in≥40 years old adults in Jordan. Biomed Pharmacol J 2018;11:789-93.  Back to cited text no. 12
    
13.
Fang X, Wang X, Bai C. COPD in China: The burden and importance of proper management. Chest 2011;139:920-9.  Back to cited text no. 13
    
14.
Bahtouee M, Maleki N, Nekouee F. The prevalence of chronic obstructive pulmonary disease in hookah smokers. Chron Respir Dis 2018;15:165-72.  Back to cited text no. 14
    
15.
Johannessen A, Eagan TM, Omenaas ER, Bakke PS, Gulsvik A. Socioeconomic risk factors for lung function decline in a general population. Eur Respir J 2010;36:480-7.  Back to cited text no. 15
    
16.
Tantisuwat A, Thaveeratitham P. Effects of smoking on chest expansion, lung function, and respiratory muscle strength of youths. J Phys Ther Sci 2014;26:167-70.  Back to cited text no. 16
    
17.
Jian W, Zheng J, Hu Y, Li Y, GAO Y, An J. What is the difference between FEV1 change in percentage predicted value and change over baseline in the assessment of bronchodilator responsiveness in patients with COPD? J Thorac Dis 2013;5:393-9.  Back to cited text no. 17
    
18.
Sterk PJ. Let's not forget: the GOLD criteria for COPD are based on post-bronchodilator FEV1. Eur Respir J 2004;23:497-8.  Back to cited text no. 18
    
19.
Wan ES, Castaldi PJ, Cho MH, Hokanson JE, Regan EA, Make BJ, et al. Epidemiology, genetics, and subtyping of preserved ratio impaired spirometry (PRISm) in COPDGene. Respir Res 2014;15:89.  Back to cited text no. 19
    
20.
American Thoracic Society. Lung function testing: Selection of reference values and interpretative strategies. Am Rev Respir Dis 1991;144:1202-18.  Back to cited text no. 20
    
21.
Dugral E, Balkanci D. Effects of smoking and physical exercise on respiratory function test results in students of university: A cross-sectional study. Medicine 2019;98:e16596.  Back to cited text no. 21
    
22.
Apostol GG, Jacobs DR Jr., Tsai AW, Crow RS, Williams OD, Townsend MC, et al. Early life factors contribute to the decrease in lung function between ages 18 and 40: The coronary artery risk development in young adults study. Am J Respir Crit Care Med 2002;166:166-72.  Back to cited text no. 22
    
23.
Kurmi OP, Li L, Wang J, Millwood IY, Chen J, Collins R, et al. COPD and its association with smoking in the Mainland China: A cross-sectional analysis of 0.5 million men and women from ten diverse areas. Int J Chron Obstruct Pulmon Dis 2015;10:655-65.  Back to cited text no. 23
    
24.
Mb A, Fmcp D, Denue B, Fmcp B, Mubi, Eo B, et al. Correlation of pack year of smoking and lung function variables in firefighters. 2015;3:32-7.  Back to cited text no. 24
    
25.
Hunter LC, Lee RJ, Butcher I, Weir CJ, Fischbacher CM, McAllister D, et al. Patient characteristics associated with risk of first hospital admission and readmission for acute exacerbation of chronic obstructive pulmonary disease (COPD) following primary care COPD diagnosis: A cohort study using linked electronic patient records. BMJ Open 2016;6:e009121.  Back to cited text no. 25
    
26.
Schembri S, Anderson W, Morant S, Winter J, Thompson P, Pettitt D, et al. A predictive model of hospitalisation and death from chronic obstructive pulmonary disease. Respir Med 2009;103:1461-7.  Back to cited text no. 26
    
27.
Polese J, Sant'Ana L, Moulaz IR, Lara IC, Bernardi JM, Lima MD, et al. Pulmonary function evaluation after hospital discharge of patients with severe COVID-19. Clinics 2021;76:e2848.  Back to cited text no. 27
    
28.
Lange P, Scharling H, Ulrik CS, Vestbo J. Inhaled corticosteroids and decline of lung function in community residents with asthma. Thorax 2006;61:100-4.  Back to cited text no. 28
    
29.
Kim G, Song H, Park K, Noh H, Lee E, Lee H, Kim H, Paek Y. Association of time to first morning cigarette and chronic obstructive pulmonary disease measured by spirometry in current smokers. Korean J Fam Med 2018;39:67-73.  Back to cited text no. 29
    
30.
Thyagarajan B, Jacobs DR, Apostol GG, Smith LJ, Jensen RL, Crapo RO, et al. Longitudinal association of body mass index with lung function: The CARDIA study. Respir Res 2008;9:31.  Back to cited text no. 30
    
31.
Do JG, Park CH, Lee YT, Yoon KJ. Association between underweight and pulmonary function in 282,135 healthy adults: A cross-sectional study in Korean population. Sci Rep 2019;9:14308.  Back to cited text no. 31
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

Top
Previous article  Next article
 
  Search
 
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

 
  In this article
Abstract
Introduction
Methods
Results
Discussion
Conclusion
References
Article Tables

 Article Access Statistics
    Viewed622    
    Printed18    
    Emailed0    
    PDF Downloaded131    
    Comments [Add]    

Recommend this journal