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Smoking history: relationships with inflammatory markers, metabolic markers, body composition, muscle strength, and cardiopulmonary capacity in current smokers
OBJECTIVE: To determine the relationships that smoking history has with inflammatory markers, metabolic markers, body composition, muscle strength, and cardiopulmonary capacity in current smokers. METHODS: This was a cross-sectional study involving 65 smokers (age range: 18-60 years). On three non-c...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Sociedade Brasileira de Pneumologia e Tisiologia
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7572273/ https://www.ncbi.nlm.nih.gov/pubmed/32556029 http://dx.doi.org/10.36416/1806-3756/e20180353 |
Sumario: | OBJECTIVE: To determine the relationships that smoking history has with inflammatory markers, metabolic markers, body composition, muscle strength, and cardiopulmonary capacity in current smokers. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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. |
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