BACKGROUND AND OBJECTIVE: The lung age of smokers is greater than their real age. We have had the clinical impression that the lung age of non-smokers might be older than their real age and that obese subjects with decreased VC and FEV1 would also have an increased lung age. This cross-sectional study investigated the relationships between lung age and smoking status, and lung age and BMI. METHODS: Subjects comprised 3247 men who consulted our institute for health screening; 819 subjects were non-smokers. In smokers and non-smokers, lung age estimated by the predictive equation based on height and FEV1 was compared with chronological age. To investigate the relationship between lung age and BMI in non-smokers, subjects were categorized into four groups based on quartiles of BMI and the lung age of the four groups compared. Multiple linear regression was used to determine the relative contribution of BMI and smoking status to lung age. RESULTS: The predictive equation used to estimate lung age significantly overestimated the chronological age of study subjects. In non-smokers, higher BMI was significantly associated with higher lung age. BMI, duration of smoking and number of cigarettes per day were significantly associated with increased lung age. CONCLUSIONS: Lung age could be used to motivate lifestyle change in obese individuals.
BACKGROUND AND OBJECTIVE: The lung age of smokers is greater than their real age. We have had the clinical impression that the lung age of non-smokers might be older than their real age and that obese subjects with decreased VC and FEV1 would also have an increased lung age. This cross-sectional study investigated the relationships between lung age and smoking status, and lung age and BMI. METHODS: Subjects comprised 3247 men who consulted our institute for health screening; 819 subjects were non-smokers. In smokers and non-smokers, lung age estimated by the predictive equation based on height and FEV1 was compared with chronological age. To investigate the relationship between lung age and BMI in non-smokers, subjects were categorized into four groups based on quartiles of BMI and the lung age of the four groups compared. Multiple linear regression was used to determine the relative contribution of BMI and smoking status to lung age. RESULTS: The predictive equation used to estimate lung age significantly overestimated the chronological age of study subjects. In non-smokers, higher BMI was significantly associated with higher lung age. BMI, duration of smoking and number of cigarettes per day were significantly associated with increased lung age. CONCLUSIONS: Lung age could be used to motivate lifestyle change in obese individuals.