RESUMEN
Exposure to cigarette smoke among smokers is highly variable. This variability has been attributed to differences in smoking behavior as measured by smoking topography, as well as other behavioral and subjective aspects of smoking. The objective of this study was to determine the factors affecting smoke exposure as estimated by biomarkers of exposure to nicotine and carbon monoxide (CO). In a multi-center cross-sectional study of 3585 adult smokers and 1077 adult nonsmokers, exposure to nicotine and CO was estimated by 24h urinary excretion of nicotine and five of its metabolites and by blood carboxyhemoglobin, respectively. Number of cigarettes smoked per day (CPD) was determined from cigarette butts returned. Puffing parameters were determined through a CreSS® micro device and a 182-item adult smoker questionnaire (ASQ) was administered. The relationship between exposure and demographic factors, smoking machine measured tar yield and CPD was examined in a statistical model (Model A). Topography parameters were added to this model (Model B) which was further expanded (Model C) by adding selected questions from the ASQ identified by a data reduction process. In all the models, CPD was the most important and highest ranking factor determining daily exposure. Other statistically significant factors were number of years smoked, questions related to morning smoking, topography and tar yield categories. In conclusion, the models investigated in this analysis, explain about 30-40% of variability in exposure to nicotine and CO.
Asunto(s)
Antimetabolitos , Monóxido de Carbono , Nicotiana/metabolismo , Nicotina , Agonistas Nicotínicos , Humo/efectos adversos , Fumar/efectos adversos , Adulto , Antimetabolitos/sangre , Antimetabolitos/orina , Biomarcadores/sangre , Biomarcadores/orina , Monóxido de Carbono/sangre , Monóxido de Carbono/orina , Carboxihemoglobina/análisis , Estudios Transversales , Equipos y Suministros , Femenino , Humanos , Masculino , Persona de Mediana Edad , Nicotina/sangre , Nicotina/orina , Agonistas Nicotínicos/sangre , Agonistas Nicotínicos/orina , Fumar/metabolismo , Encuestas y Cuestionarios , Breas/análisis , Adulto JovenRESUMEN
BACKGROUND: This article describes the data mining analysis of a clinical exposure study of 3585 adult smokers and 1077 nonsmokers. The analysis focused on developing models for four biomarkers of potential harm (BOPH): white blood cell count (WBC), 24 h urine 8-epi-prostaglandin F2alpha (EPI8), 24 h urine 11-dehydro-thromboxane B2 (DEH11), and high-density lipoprotein cholesterol (HDL). METHODS: Random Forest was used for initial variable selection and Multivariate Adaptive Regression Spline was used for developing the final statistical models RESULTS: The analysis resulted in the generation of models that predict each of the BOPH as function of selected variables from the smokers and nonsmokers. The statistically significant variables in the models were: platelet count, hemoglobin, C-reactive protein, triglycerides, race and biomarkers of exposure to cigarette smoke for WBC (R-squared = 0.29); creatinine clearance, liver enzymes, weight, vitamin use and biomarkers of exposure for EPI8 (R-squared = 0.41); creatinine clearance, urine creatinine excretion, liver enzymes, use of Non-steroidal antiinflammatory drugs, vitamins and biomarkers of exposure for DEH11 (R-squared = 0.29); and triglycerides, weight, age, sex, alcohol consumption and biomarkers of exposure for HDL (R-squared = 0.39). CONCLUSIONS: Levels of WBC, EPI8, DEH11 and HDL were statistically associated with biomarkers of exposure to cigarette smoking and demographics and life style factors. All of the predictors together explain 29%-41% of the variability in the BOPH.
Asunto(s)
HDL-Colesterol/sangre , Dinoprost/análogos & derivados , Fumar/sangre , Fumar/orina , Tromboxano B2/análogos & derivados , Adulto , Algoritmos , Biomarcadores/sangre , Biomarcadores/orina , Minería de Datos , Dinoprost/orina , Femenino , Humanos , Recuento de Leucocitos , Masculino , Análisis de Regresión , Tromboxano B2/orina , Estados UnidosRESUMEN
INTRODUCTION: There are about 4,800 different chemical constituents in cigarette smoke. Therefore, the total systemic exposure evaluation of the population of smokers to cigarette smoke is challenging. Measurement of biomarkers as surrogates of cigarette smoke constituents is a realistic approach to assess exposure. OBJECTIVE: To estimate cigarette smoke exposure of the U.S. smoker population. METHODS: Stratified, cross-sectional, multicenter design (39 sites in 31 states); 3,585 adult cigarette smokers and 1,077 nonsmokers. Biomarkers were determined from 24-hr urine collections or blood samples. Population estimates were generated by weighting sample data with weights from a large U.S. probability sample (Behavioral Risk Factor Surveillance System). RESULTS: The adult smoker population estimates for tobacco-specific biomarkers were nicotine equivalents 13.3 mg/24 hr (SE 0.14), serum cotinine 184 ng/ml (1.8), and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol 439 ng/24 hr (5.5). The population estimates for smokers and nonsmokers for nontobacco-specific biomarkers were 1-hydroxypyrene 317 (6.8) and 110 (7.1) ng/24 hr, 4-aminobiphenyl Hb adducts 43.1 (1.04) and 11.4 (1.5) pg/g Hb, carboxyhemoglobin 5.26(0.04) in percent of hemoglobin saturation and 1.45(0.02), 3-hydroxypropylmercapturic acid 2,030 (24) and 458 (17) microg/24 hr, monohydroxy-butenyl-mercapturic acid 3.61 (0.1) and 0.30 (0.02) microg/24 hr, and dihydroxy-butyl-mercapturic acid 556 (4.9) and 391 (5.5) microg/24 hr. On average, young adult smokers had lower exposure than older smokers; female smokers had lower exposure than males, and Black smokers had lower exposure than Whites. DISCUSSION: This study estimated the population exposure to cigarette smoke constituents in adult U.S. smokers and identified significant differences between subpopulations. The data may serve as a reference for monitoring the impact of changes in cigarette consumption and the introduction of potentially reduced exposure cigarettes.
Asunto(s)
Biomarcadores/análisis , Exposición a Riesgos Ambientales , Nicotiana , Fumar/sangre , Fumar/orina , Adulto , Biomarcadores/sangre , Biomarcadores/orina , Cromatografía de Gases , Cromatografía Liquida , Estudios Transversales , Demografía , Femenino , Humanos , Inmunoensayo , Masculino , Espectrometría de Masas en Tándem , Estados UnidosRESUMEN
Cigarette burn time (CBT), conventionally defined as the time a cigarette burns during smoking, can be affected by cigarette design and smoking behavior. A previous study showed a strong negative correlation between CBT and nicotine yield under machine smoking conditions. This study for the first time examined the relationship of CBT and exposure to nicotine and carbon monoxide in adult smokers in a controlled clinical study. 24h nicotine equivalents excretion (NE), carboxyhemoglobin (COHb) and CBT were measured in two groups of 20 adults smoking Marlboro Lights and 20 adults smoking Marlboro Ultra on two consecutive days. Approximately 20% of the total variability in CBT was attributed to cigarette brand, 34% to smokers and 1% to study day. The exposure index, defined as the number of cigarettes smoked per day divided by average daily CBT for each smoker, accounted for a large proportion of the total variability in NE (R(2)=0.79-0.91) and COHb (R(2)=0.85-0.90). We conclude that CBT has an important influence on levels of NE and COHb in adult smokers. CBT, along with the number of cigarettes smoked per day, can be used to estimate adult smokers' exposure to nicotine and carbon monoxide.