Effect of chronic smoking on regional cerebral blood flow in asymptomatic individuals. 1993

Y Isaka, and K Ashida, and M Imaizumi, and H Abe
Department of Nuclear Medicine, Osaka National Hospital, Japan.

Correlations between cigarette smoking and cerebral blood flow (CBF) were determined. The purpose of the present study was to determine whether the level of cigarette use is a significant predictor of regional CBF (rCBF) when age, gender, mean arterial blood pressure, total cholesterol, fasting blood glucose, hematocrit, and presence of ST-T change and left ventricular hypertrophy on electrocardiogram (ECG) are controlled. We studied a continuous sample of 40 asymptomatic individuals including 20 smokers and 20 nonsmokers. Subjects (mean age 66.2 yr) had an average smoking index of 456 +/- 485.1 (mean +/- standard deviation) [(Number of cigarette/d) x (years of smoking history)]. Regional CBF was measured using the intravenous 133Xe injection method. Simple linear regression and multivariate regression analyses were performed, which modeled regional cerebral blood flow as a function of smoking index and other cerebrovascular disease risk factors. The male-to-female ratio was higher in the group of smokers (18/2) than in the group of nonsmokers (2/18) (P < 0.01). The mean hematocrit of smokers was significantly higher than that of nonsmokers (P < 0.01). There were no significant differences in other variables tested between the two groups. Simple linear regression analysis demonstrated a significant negative correlation of smoking index with CBF in whole brain (r = -0.33; P < 0.05), the right hemisphere (r = -0.34; P < 0.05), right parietal cortex (r = -0.36; P < 0.05), right occipital cortex (r = -0.34; P < 0.05) and left parietal cortex (r = -0.33; P < 0.05).(ABSTRACT TRUNCATED AT 250 WORDS)

UI MeSH Term Description Entries
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D002318 Cardiovascular Diseases Pathological conditions involving the CARDIOVASCULAR SYSTEM including the HEART; the BLOOD VESSELS; or the PERICARDIUM. Adverse Cardiac Event,Cardiac Events,Major Adverse Cardiac Events,Adverse Cardiac Events,Cardiac Event,Cardiac Event, Adverse,Cardiac Events, Adverse,Cardiovascular Disease,Disease, Cardiovascular,Event, Cardiac
D002560 Cerebrovascular Circulation The circulation of blood through the BLOOD VESSELS of the BRAIN. Brain Blood Flow,Regional Cerebral Blood Flow,Cerebral Blood Flow,Cerebral Circulation,Cerebral Perfusion Pressure,Circulation, Cerebrovascular,Blood Flow, Brain,Blood Flow, Cerebral,Brain Blood Flows,Cerebral Blood Flows,Cerebral Circulations,Cerebral Perfusion Pressures,Circulation, Cerebral,Flow, Brain Blood,Flow, Cerebral Blood,Perfusion Pressure, Cerebral,Pressure, Cerebral Perfusion
D005260 Female Females
D006400 Hematocrit The volume of packed RED BLOOD CELLS in a blood specimen. The volume is measured by centrifugation in a tube with graduated markings, or with automated blood cell counters. It is an indicator of erythrocyte status in disease. For example, ANEMIA shows a low value; POLYCYTHEMIA, a high value. Erythrocyte Volume, Packed,Packed Red-Cell Volume,Erythrocyte Volumes, Packed,Hematocrits,Packed Erythrocyte Volume,Packed Erythrocyte Volumes,Packed Red Cell Volume,Packed Red-Cell Volumes,Red-Cell Volume, Packed,Red-Cell Volumes, Packed,Volume, Packed Erythrocyte,Volume, Packed Red-Cell,Volumes, Packed Erythrocyte,Volumes, Packed Red-Cell
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000367 Age Factors Age as a constituent element or influence contributing to the production of a result. It may be applicable to the cause or the effect of a circumstance. It is used with human or animal concepts but should be differentiated from AGING, a physiological process, and TIME FACTORS which refers only to the passage of time. Age Reporting,Age Factor,Factor, Age,Factors, Age
D000368 Aged A person 65 years of age or older. For a person older than 79 years, AGED, 80 AND OVER is available. Elderly

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