Smoking history: relationships with inflammatory markers, metabolic markers, body composition, muscle strength, and cardiopulmonary capacity in current smokers

• Published in: Jornal brasileiro de pneumologia Vol. 46; no. 5; p. e20180353
• Main Authors: Gouveia, Tamara Dos Santos, Trevisan, Iara Buriola, Santos, Caroline Pereira, Silva, Bruna Spolador de Alencar, Ramos, Ercy Mara Cipulo, Proença, Mahara, Ramos, Dionei
• Format: Journal Article
• Language: English
• Published: Brazil Sociedade Brasileira de Pneumologia e Tisiologia 01-01-2020
• Subjects: Adult; Biomarkers - analysis; Biomarkers - metabolism; Body composition; Body Composition - drug effects; Body Composition - physiology; Body Mass Index; Cardiorespiratory Fitness; Cross-Sectional Studies; Female; Humans; Inflammation - metabolism; Male; Middle Aged; Monocytes; Monocytes - metabolism; Muscle Strength - drug effects; Muscle Strength - physiology; Original; RESPIRATORY SYSTEM; Smokers; Smoking; Smoking - adverse effects; Smoking - blood; Smoking - metabolism; Tobacco; Triglycerides; Triglycerides - blood; Waist Circumference; Composição corporal; Waist circumference; Tobacco; Monocytes; Triglicerídeos; Tabaco; Circunferência abdominal; Monócitos; Triglycerides; Body composition; Fumar; Smoking
• ISSN: 1806-3756; 1806-3713; 1806-3756
• DOI: 10.36416/1806-3756/e20180353

To determine the relationships that smoking history has with inflammatory markers, metabolic markers, body composition, muscle strength, and cardiopulmonary capacity in current smokers.
This was a cross-sectional study involving 65 smokers (age range: 18-60 years). On three non-consecutive days, each participant was evaluated in terms of smoking history, pre-existing comorbidities, lung function (by spirometry), peripheral muscle strength (by dynamometry), body composition (by bioelectrical impedance analysis), levels of metabolic/inflammatory markers, and maximum cardiopulmonary capacity (by treadmill exercise test). We evaluated the relationships that smoking history has with inflammatory markers, metabolic markers, body composition, muscle strength, and cardiopulmonary capacity, using logarithmic transformation of the data and calculating Pearson's correlation coefficient and for partial correlations adjusted for age, gender, body mass index (BMI), and comorbidities. To identify the influence of smoking history on pre-existing comorbidities, we used a logistic regression model adjusted for age, BMI, and duration of smoking.
Smoking history correlated significantly, albeit weakly, with triglyceride level (r = 0.317; p = 0.005), monocyte count (r = 0.308; p = 0.013), and waist circumference (r = 0.299; p = 0.017). However, those correlations did not retain their significance in the adjusted analysis. In the logistic regression model, smoking more than 20 cigarettes/day correlated significantly with the presence of metabolic diseases (OR = 0.31; 95% CI: 1.009-1.701; p = 0.043).
In this sample of smokers, smoking history correlated positively with the triglyceride level, the monocyte count, and waist circumference. The prevalence of metabolic disease was highest in those who smoked more than 20 cigarettes/day.