Abstract
Background
Smoking poses the most common risk factor for chronic obstructive pulmonary disease (COPD) and aggravates disease progression. Tobacco dependence inhibits smoking cessation and may affect smoking patterns that increase tobacco exposure and predispose to lung function decline.
Aims and objectives
We aimed to assess tobacco dependence in current smokers with and without COPD and evaluate its role in disease development.
Method
This cross-sectional study was conducted in Greek rural areas. Current smokers completed the Fagerström Test for Nicotine Dependence and were classified into COPD and non-COPD groups based on spirometry parameters.
Results
Among current smokers, 288 participants comprised the non-COPD and 71 the COPD group. Both presented moderate tobacco dependence, but smokers with COPD started to smoke earlier in the morning. Multiple logistic regression analysis revealed higher COPD prevalence in smokers with higher scores in the Fagerström test (odds ratio OR = 1.12, 95% confidence interval [1.01 – 1.24]) and older age (OR = 1.06 [1.03 – 1.09]), independently of pack-years smoking index. Multiple linear regression analysis in smokers with COPD showed that the forced expiratory volume in the 1st second decreased by 2.3% of the predicted value for each point increase in the Fagerström Test and 0.59% for each year of age, independently of participants’ sex and pack-years smoking index.
Conclusion
The Fagerström score appears to indicate a higher probability for COPD and lung function deterioration when assessed along with age in current smokers. Smoking cessation support programs are fundamental to COPD prevention and management.
Keywords: Tobacco dependence, Fagerström test, chronic obstructive lung disease, smokers, rural population
Introduction
Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide. 1 Importantly, smoking constitutes the most common risk factor for COPD and aggravates disease progression, while smoking cessation improves outcomes.2–4 However, smoking alone does not dictate lung function impairment and COPD development. Lung function trajectories hinge on genetic predisposition, early life conditions and significant exposure to environmental risk factors. 3
Tobacco dependence may affect smoking patterns that increase tobacco exposure and predispose to lung function decline. For example, smokers with stronger nicotine dependence may seek cigarettes with higher nicotine levels, increase tobacco inhalation depth and inhalation duration,5,6 thus increasing nicotine intake per cigarette. 7 Moreover, stronger nicotine dependence is associated with less motivation and higher failure rates at smoking cessation 8 and may, thus, herald persistent tobacco exposure leading to lung function deterioration. Notably, patients with COPD are less likely to quit smoking compared to smokers without COPD, which may imply increased tobacco dependence. 9
The Fagerström test for Nicotine Dependence is a simple questionnaire,10–12 developed in 1978 by Karl-Olov Fagerström and updated to its current form in 1991 by Heatherton et al. It has been widely used as a validated measure of tobacco physical dependence to guide plan of care and nicotine replacement therapy in smoking cessation programs. Its score reveals minimal or mild, moderate and high nicotine dependence. 13
We aimed to assess tobacco dependence among current smokers and explore potential differences between those with and without COPD utilizing the Fagerström Test. We sought to evaluate the role of the Fagerström Test as a prognostic tool for COPD development and progression.
Methods
Study design
We conducted a cross-sectional study in rural areas of northern Greece, after obtaining ethical approval by the Scientific Committee of the 3rd and 4th District Health Directorates. Potential participants were identified upon voluntarily registering to local screening invitations from September 2020 to March 2021.
The study was conducted according to the principles of the Declaration of Helsinki and written informed consent was obtained from all participants. This paper follows the STROBE guidelines for cross-sectional studies. 14
Study population
Current smokers >35 years of age, permanently residing in rural areas, were eligible to participate. Exclusion criteria comprised previously diagnosed COPD under medical treatment and follow-up, other respiratory disorders, including bronchial asthma, any recent acute event posing contraindication to spirometry, and severe neurologic or psychiatric conditions that could render the completion of the Fagerström Test unreliable.
Study assessments and measurements
Demographic data, medical history and smoking status were documented for all participants. We used the Fagerström Test for Nicotine Dependence as a validated measure of tobacco dependence. It comprises six questions, which relate to daily smoking patterns. Each question is rated 0–1 or 0–3, yielding a total score 0–10. A total score <4 points reveals minimal or mild tobacco dependence, 4–6 points reveal moderate dependence and 7–10 points reveal high dependence. 13 Apart from the total score, we also recorded the first question sub-score, namely the time between awakening and first cigarette of the day, as an addiction gradient. Specifically, this question yields a score 0–3; a higher score indicates shorter time to first cigarette.
After completing the Fagerström test, all participants underwent spirometry measurements to capture their forced vital capacity (FVC), forced expiratory volume in the 1st second (FEV1) and FEV1 to FVC ratio. Spirometry was performed by experienced pulmonologists, members of the Hellenic Chest Diseases Society, who were blinded to participants’ Fagerström score. We only included the data from spirometry measurements complying with the ERS/ATS 2019 standards 15 in our analyses.
Participants were classified into two groups according to spirometry parameters: COPD group (post-bronchodilation FEV1/FVC <0.7) and non-COPD group. Along with spirometry, clinical status was used to confirm COPD diagnosis. 16 Additionally, participants with COPD formed subgroups based on the severity of airflow obstruction, namely FEV1 %predicted value as per GOLD; 16 FEV1 ≥80% predicted: mild obstruction, ≥50% FEV1 <80% predicted: moderate obstruction, ≥30% FEV1 <50% predicted: severe obstruction, FEV1 <30%predicted: very severe obstruction.
Outcomes of interest
We sought potential associations between the Fagerström score and post-bronchodilation FEV1/FVC <0.7, signifying COPD, as a primary outcome. Our secondary analyses explored the decrease in FEV1%predicted value, marking lung function deterioration.
Statistical analyses
We used Shapiro-Wilk test to check the normal distribution of continuous variables. Normally distributed quantitative data were described as means with their standard deviations and were analyzed using the independent t-test. The Pearson r2 test was used to check linear correlation. We used the chi-square test for categorical variables.
We utilized multiple logistic regression analysis to estimate the odds ratio (OR) with 95% confidence interval (CI) for the odds of COPD (post-bronchodilation FEV1/FVC <0.7) in relation to the Fagerström score, age, and pack-years smoking index as independent variables. Multiple linear regression analysis served to evaluate FEV1%predicted values in relation to the Fagerström score, age, sex, and pack-years smoking index as independent variables. The multiple linear regression analysis was performed both in the overall population and in participants with COPD. The models’ independent variables were initially explored in univariate analyses checking statistical significance; the non-statistically significant independent variables were discarded from the multiple logistic and linear regression models.
We conducted the statistical analysis using IBM/SPSS version 25. The significance level was set to α = 0.05 (two-tailed).
Results
Participants’ characteristics
A total of 1149 adults permanently residing in rural areas of northern Greece were identified. After excluding 787 subjects (Figure 1), we included 362 eligible participants. Among them, 288 (80.2%) current smokers comprised the non-COPD and 71 (19.8%) the COPD group (Figure 2(a)), whereas three participants had unreliable spirometry measurements and were, thus, excluded from the analyses.
Figure 1.
Flowchart depicting the selection process for participation in this study.
Figure 2.
Distribution of participants in (a) COPD and non-COPD group; (b) COPD subgroups based on airflow obstruction. COPD: chronic obstructive pulmonary disease.
Table 1 summarizes comparative descriptive data. Smokers with COPD were older and included a higher percentage of males than smokers without COPD. Airflow obstruction was mild in 39.4%, moderate in 49.3% and severe in 11.3% of participants with COPD; none presented very severe airflow obstruction (Figure 2(b)). The Fagerström score was similar in men and women (6.5 ± 2.79 vs 6.0 ± 2.61, p = .09), both in the COPD (6.7 ± 2.96 vs 6.4 ± 2.1, p = .56) and non-COPD group (6.3 ± 2.72 vs 5.9 ± 2.67, p = .23). Interestingly, the 1st question sub-score was higher in men than women without COPD (0.9 ± 0.80 vs 0.7 ± 0.71, p < .01), but not for those with COPD (1.0 ± 0.77 vs 0.9 ± 0.87, p = .52).
Table 1.
Demographic data, lung function parameters, pack-years smoking index and tobacco dependence in participants with and without COPD.
| Non-COPD group (N = 288) | COPD group (N = 71) | ||
|---|---|---|---|
| Sex, male n (%) | 100 (34.7) | 48 (67.6) | p = .01 |
| Mean age (SD), years | 56.7 (11.7) | 64.0 (11.18) | p < .01 |
| Mean FVC (SD), litres | 3.47 (0.93) | 3.28 (1.10) | p = .17 |
| Mean FVC%predicted (SD) | 102.2 (17.81) a | 90.4 (20.31) b | p < .01 |
| Mean FEV1 (SD), litres | 2.81 (0.73) | 2.14 (0.72) | p < .01 |
| Mean FEV1%predicted (SD) | 99.1 (18.68) | 75.3 (20.33) | p < .001 |
| Mean FEV1/FVC (SD) | 0.82 (0.06) | 0.65 (0.06) | p < .01 |
| SI >30 pack-years, N (%) | 128 (44.4%) | 43 (60.6%) | p = .16 |
| SI 21-30 pack-years, N (%) | 92 (31.9%) | 18 (25.4%) | p = .42 |
| SI 11-20 pack-years, N (%) | 47 (16.3%) | 8 (11.3%) | p = .36 |
| SI 1-10 pack-years, N (%) | 21 (7.3%) | 2 (2.8%) | p = .19 |
| Mean fagerström score (SD) | 6.1 (2.69) | 6.6 (2.70) | p = .15 |
| Fagerström first question sub-score | 0.8 (0.75) | 1.0 (0.8) | p = .04 |
COPD: Chronic Obstructive Pulmonary Disease; FVC: Forced Vital Capacity; FEV1: Forced Expiratory Volume in the 1st second; SI: smoking index. Bold values indicate statistical significance.
aN = 237.
bN = 64.
Primary outcome
The Fagerström score was similar in smokers with COPD and without COPD, but participants with COPD scored higher in the 1st question sub-score than those without COPD (Table 1, Figure 3). Pearson’s correlation coefficient did not reveal any linear association between the Fagerström score and FEV1/FVC ratio, neither in smokers with COPD (r = −0.05, p = .66), nor in smokers without COPD (r = −0.06, p = .30).
Figure 3.
The Fagerström score and its first question sub-score in current smokers with and without COPD. COPD: chronic obstructive pulmonary disease.
We utilized a multiple logistic regression model to explore the role of Fagerström score along with age in detecting COPD (post-bronchodilation FEV1/FVC <0.7). The preceding univariate analyses checking the model’s independent variables yielded non-statistically significant impact of pack-years smoking index (B = 19.9, p = .34). Our regression analysis revealed that the odds of COPD were higher in smokers with a higher Fagerström score (OR = 1.12, 95%CI 1.01-1.24) and older age (OR = 1.06, 95%CI 1.03-1.09). In other words, we found that the odds of COPD were 1.12 times higher for each point increase in Fagerström score and 1.06 times higher for each year of subjects’ age. This model accounted for 11.2% (Nagelkerke R2) of the FEV1/FVC variable for COPD.
Secondary outcomes
Current smokers with COPD and moderate airflow obstruction scored significantly higher than those with mild airflow obstruction, both in the Fagerström test (7.0 ± 2.81 vs 5.6 ± 2.09, p = .03, Figure 4(a)) and its first question (1.11 ± 0.83 vs 0.71 ± 0.71, p = .04, Figure 4(b)). We did not find any difference in the Fagerström score when comparing smokers with COPD and severe airflow obstruction to those with moderate airflow obstruction, nor between those with severe to those with mild airflow obstruction (Figure 4).
Figure 4.
Comparison among COPD subgroups regarding (a) the Fagerström score; (b) the Fagerström first question sub-score. COPD: chronic obstructive pulmonary disease.
Participants with COPD presented no linear correlation between FEV1%predicted value and the Fagerström score (r = −0.21, p = .08) or 1st question sub-score (r = −0.10, p = .39). Our COPD subgroups analyses according to airflow obstruction did not reveal any linear correlation between FEV1%predicted value and the Fagerström score (mild obstruction: r = −0.90, p = .65; moderate obstruction: r = −0.15, p = .41; severe obstruction: r = −0.12, p = .77). No correlation was found in the non-COPD group, either (Fagerström score: r = −0.15, p = .01; 1st question sub-score: r = −0.11, p = .07).
Multiple linear regression analysis revealed that the FEV1%predicted value decreased by 2.3% of predicted value for each point increase in the Fagerström score and by 0.36% of predicted value for each year increase in age, with 6.46% of predicted value increase in women compared to men (FEV1%pred = 114.53-0.36*Age + 6.46*Sex-2.30*Fagerström score, p < .01 in all co-efficients). Approximately 11.16% (Nagelkerke R2) of FEV1% predicted value may be attributed to age, sex and the Fagerström score variability.
In our subgroup analysis of current smokers with COPD, sex (Β = 4.34, p = .39) and pack-years smoking index (B = 5.34, p = .09) were not significant factors in the univariate analyses and were subsequently detracted from the multiple linear regression analysis. We found that FEV1%predicted value decreased by 2.3% of predicted value for each point increase in the Fagerström score and by 0.59% of predicted value for each year increase in age (FEV1%pred = 127.90–0.585*Age-2.30*Fagerström score, p ≤ .01 in all co-efficients). This model accounted for approximately 13.69% (Nagelkerke R2) of FEV1%predicted value variability. When looking only at current smokers without COPD, we did not observe any significant associations in the linear regression analysis.
Discussion
This cross-sectional study demonstrated higher COPD prevalence and lung function decline in smokers with stronger tobacco dependence. Specifically, a higher score in the Fagerström test, along with older age, appear to indicate higher probability of COPD, independently of pack-years smoking index. Additionally, we found that the lung function (FEV1%predicted) of current smokers with COPD deteriorates as the Fagerström score and age increase, independently of participants’ sex and pack-years smoking index. We noted that current smokers in both the COPD and non-COPD group had moderate tobacco dependence, without any statistical difference, but smokers with COPD started to smoke significantly earlier in the morning. Our findings warrant confirmation in larger studies involving urban areas.
Smoking poses the most common risk factor for COPD and aggravates disease progression, including lung function and exacerbation rate.17,18 Smoking status has been utilized previously in prediction models for COPD and related symptoms19,20 and is considered pivotal together with age. 21 The pack-years smoking index is commonly used to quantify smoking habit severity and allow for an estimation of the risk for respiratory diseases. However, tobacco use may vary over time rendering recall potentially unreliable. 22 Furthermore, some studies underlined a discrepancy between pack-years’ two components; a stronger impact of smoking duration was noted over cigarettes per day on the incidence and progression of respiratory diseases, including lung cancer and COPD.23,24 Moreover, pack-years smoking index does not reflect behavioral parameters, such as selection of cigarettes with higher nicotine levels, tobacco inhalation depth and duration.
Tobacco dependence may affect such smoking patterns that potentially increase intake of nicotine and other harmful substances,5,6 thus precipitating lung function decline. It also exerts an inhibitory effect in smoking cessation 8 and may, thus, herald persistent tobacco exposure leading to lung function decline. To evaluate its role in COPD, previous studies have used the Fagerström Test for Nicotine Dependence. Jiménez-Ruiz et al. found that the majority of smokers with COPD had moderate to severe nicotine dependence, whereas smokers without COPD had weak to moderate dependence. 25 Another study showed that strong nicotine dependence did not differ between smokers with and without COPD. 26
In contrast to these studies, we recruited an exclusively rural population, to minimize the impact of air pollutants as a confounding factor on COPD development and progression, which could have weakened any correlation with nicotine dependence and exposure. We also performed an analysis of the 1st question sub-score as an addiction gradient, indicating a different smoking pattern, namely the time between awakening and first cigarette of the day. Apart from comparing tobacco dependence between the COPD and the non-COPD group, we also performed multiple regression analyses to explore the role of the Fagerström score in identifying subjects at higher risk for COPD and lung function decline.
Confidence in the findings of our study may be limited due to the small sample size. Although we screened a fair number of participants (N = 1149), the population of interest comprised current smokers with no other respiratory diseases or previous COPD diagnosis under treatment and follow-up, thus restricting eligibility for participation. Our study was conducted in exclusively rural areas, thus limiting our findings’ generalizability, as lung function may differ in urban areas due to concurrent exposure to air pollutants or differences in smoking habits. Another limitation is the potential under-representation of patients with very severe airflow obstruction or worse clinical state, who may have not voluntarily registered for participation. We were not able to assess COPD development in former smokers, as the Fagerström test is only applicable to current smokers; thus, our study excluded a subgroup of individuals who may develop COPD.
Larger studies involving urban areas are warranted to confirm our findings and delineate the role of tobacco dependence in early disease state. Its evaluation in subjects with small-airways impairment who may later develop spirometrically confirmed COPD 27 merits assessment and documentation in future studies.
Conclusion
Higher scores in the Fagerström test for Nicotine Dependence appear to indicate a higher probability of COPD and lung function decline, when assessed along with age in current smokers residing in rural areas. Our findings imply that patients with COPD may need a more tailored or intense smoking cessation intervention. Future powered trials are warranted to confirm our findings and provide valuable insights in early disease state.
Acknowledgment
This study was conducted under the auspices of Hellenic Chest Diseases Society (HCDS). We cordially thank the HCDS Board Members at the time this study was conducted, namely I. Titopoulos, T. Karapetsas, S. Tryfon, K. Porpodis, M. Saroglou and C. Efthymiou.
Footnotes
Author contributions: Efthymia Papadopoulou: Methodology, Formal analysis, Investigation, Writing - Original Draft, Writing - Review & Editing, Visualization. Anna-Bettina Haidich: Methodology, Validation, Formal analysis, Data Curation, Writing - Review & Editing, Supervision. Alexander Mathioudakis: Methodology, Writing - Review & Editing. Drosos Tsavlis: Investigation, Data Curation, Writing - Review & Editing. Konstantina Papadopoulou: Data Curation, Writing - Original Draft, Visualization. Rena Oikonomidou: Investigation, Writing - Review & Editing, Visualization. Panagiotis Bogiatzidis: Conceptualization, Validation, Writing - Review & Editing. Stavros Tryfon: Conceptualization, Methodology, Formal analysis, Investigation, Writing - Original Draft, Writing - Review & Editing, Visualization, Supervision, Project administration.
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: HCDS provided financial support for the publication.
ORCID iDs
Efthymia Papadopoulou https://orcid.org/0000-0002-2415-0842
Stavros Tryfon https://orcid.org/0000-0001-5102-0480
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.