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The impact of smoking on estimated biological age and body fat composition: A cross-sectional study.
- Source :
- Tobacco Induced Diseases; Dec2023, Vol. 21, p1-6, 6p
- Publication Year :
- 2023
-
Abstract
- INTRODUCTION Smoking tobacco results in the death of more than 8 million people every year. Our study aims to explore a new approach for smoking cessation by analyzing body composition differences between smokers and non-smokers, focusing on potential variations in biological and chronological ages. METHODS A cross-sectional study was conducted in 2019 at the Special Hospital for Medical Rehabilitation in Croatia. It included 164 subjects, 81 smokers and 83 non-smokers, aged 40-65 years. This study was part of a two-year investigation on locomotor parameter changes as early COPD predictors. Measurements encompassed body parameters, spirometry tests, and body composition. Spirometry was done using the Flowscreen Pro device, and the FEV1/FVC ratio determined lung function. The GAIA 359 PLUS device assessed body composition and estimated biological age. Exclusion criteria applied to specific medical conditions and recent surgeries. RESULTS Smokers had a slightly higher percentage of fat tissue than non-smokers (median=27%, IQR: 24-31) compared to non-smokers (median=25%, IQR: 22-28, p<0.001). The difference in the Gaia estimated age and the actual age of the subjects was significantly higher in the group of smokers (median=2, IQR: 0-3) compared to non-smokers (median=0 IQR: -2-2, p=0.003), but they did not differ in muscle tissue, weight or the proportion of trunk adipose tissue. CONCLUSIONS Our study revealed that smokers exhibit higher fat tissue percentages and a higher estimated biological age relative to non-smokers. These findings underscore the established health hazards of smoking and the imperative for smoking cessation in mitigating these adverse effects. [ABSTRACT FROM AUTHOR]
- Subjects :
- SMOKING prevention
BODY composition
BIOMARKERS
SMOKING cessation
BODY weight
NON-smokers
AGE distribution
CROSS-sectional method
COMPARATIVE studies
OBSTRUCTIVE lung diseases
FORCED expiratory volume
PULMONARY function tests
DESCRIPTIVE statistics
SMOKING
PREDICTION models
SPIROMETRY
ADIPOSE tissues
Subjects
Details
- Language :
- English
- ISSN :
- 20707266
- Volume :
- 21
- Database :
- Complementary Index
- Journal :
- Tobacco Induced Diseases
- Publication Type :
- Academic Journal
- Accession number :
- 175397524
- Full Text :
- https://doi.org/10.18332/tid/174663