BACKGROUND: Exhaled carbon monoxide (COex) level is positively associated with tobacco smoking and exposure to smoke from biomass/coal burning. Relatively little is known about its determinants in China despite the population having a high prevalence of smoking and use of biomass/coal. METHODS: The China Kadoorie Biobank includes 512,000 participants aged 30-79 years recruited from 10 diverse regions. We used linear regression and logistic regression methods to assess the associations of COex level with smoking, exposures to indoor household air pollution and prevalent chronic respiratory conditions among never smokers, both overall and by seasons, regions and smoking status. RESULTS: The overall COex level (ppm) was much higher in current smokers than in never smokers (men: 11.5 vs 3.7; women: 9.3 vs 3.2). Among current smokers, it was higher among those who smoked more and inhaled more deeply. Among never smokers, mean COex was positively associated with levels of exposures to passive smoking and to biomass/coal burning, especially in rural areas and during winter. The odds ratios (OR) and 95% confidence interval (CI) of air flow obstruction (FEV1/FVC ratio<0.7) for never smokers with COex at 7-14 and ≥14 ppm, compared with those having COex<7, were 1.38 (1.31-1.45) and 1.65 (1.52-1.80), respectively (Ptrend<0.001). Prevalence of other self-reported chronic respiratory conditions was also higher among people with elevated COex (P<0.05). CONCLUSION: In adult Chinese, COex can be used as a biomarker for assessing current smoking and overall exposure to indoor household air pollution in combination with questionnaires.

Original publication

DOI

10.1093/ije/dyt158

Type

Journal article

Journal

Int J Epidemiol

Publication Date

10/2013

Volume

42

Pages

1464 - 1475

Keywords

China, Exhaled carbon monoxide, epidemiology, household air pollution, smoking, Adult, Aged, Air Pollution, Indoor, Biomass, Breath Tests, Carbon Monoxide, China, Coal, Cough, Environmental Exposure, Exhalation, Female, Heating, Humans, Linear Models, Logistic Models, Male, Middle Aged, Odds Ratio, Pulmonary Disease, Chronic Obstructive, Respiration Disorders, Rural Population, Seasons, Smoke, Smoking, Tobacco Products, Tobacco Smoke Pollution, Tuberculosis, Pulmonary