Smoking, Leukocyte Count, and Ventilatory Lung Function in Working Men

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1 Smoking, Leukocyte Count, and Ventilatory Lung Function in Working Men Rafael S. Carel, M.D.;* Melvyn S. Tockman, M.D.;t and Michael Baser, M.Sc.t Results of a cross-sectional study of ventilatory lung function (VLF) in a group of 307 working men showed that the leukocyte count in peripheral blood is more closely associated with the relative position (percentile) of a person in the frequency distribution ofvlf than is smoking intensity Leukocyte count is significantly (and inversely) correlated with VLF in nonsmokers as well as in smokers. A multiple regression analysis indicated that, after accounting for the effect of height and age, white blood cell (WBC) count explains more of the VLF variance than many other health determinants. Moreover, WBC count is the only variable, apart from height and age, that contributes significantly to the regression. Current smokers with elevated leukocyte count in peripheral blood may constitute a defined highrisk group because they demonstrate more negative regression age coefficients when compared with smokers without elevated WBC or with nonsmokers. Mechanisms that may explain these findings are discussed. The relationship between cigarette smoking and impaired pulmonary function has been recognized for many years. Numerous studies':" have singled out cigarette smoking as the leading cause in the development of chronic airway obstruction and chronic obstructive pulmonary disease (COPD). Its deleterious effect on ventilatory lung function (VLF) is proportionate to the cumulative (pack-years) intensity of smoking, and, as a group, long-term smokers have altered pulmonary function tests when compared with lifelong nonsmokers. However, the effect of smoking on lung structure and function is variable, and only a small minority of regular cigarette smokers develop severe chronic airway limitations and progress to disabling COPD Most long-term smokers show only mild or moderate signs of airway obstruction, with only slightly greater than normal decline of their VLF with age. Susceptible smokers, those at risk of developing significant degree of clinical disease, are those with the most rapid rate of loss ofvlf with age Little is known about the cause of the variable susceptibility to develop advanced chronic airflow limitation among smokers. The purpose of this study is to determine from cross-sectional data factors that may assist in distinguishing the more vulnerable smokers from those in whom no greater than predicted decline in VLF is observed. *Department of Occupational Medicine, Soroka Medical Center, Ben-Gurion University Medical School, Beer-Sheva, Israel. tdepartment of Environmental Health Sciences, The Johns Hopkins School of Hygiene and Public Health, Baltimore. Partially supported by a grant from the Committee on Prevention in Occupational Health, the Ministry of Labor, Israel. Manuscript received September 4; revision accepted December 16. Reprint requests: Dr. Carel, MOR Institute, PO Box 938, Bnei Brak, Israel Study Population MATERIAL AND METHODS During , large groups of employed men were examined in a large multiphasic screening center. Most of these examinations were performed as part of periodic evaluations of presumably healthy workers. All examinees were referred to be examined by their employers and not because of specific health complaints. For a forthcoming longitudinal study subjects who undertook three or more periodic health examinations during that period composed the study group. This report, however, considers only the initial, cross-sectional observations. All examinees (N =307) who met this criterion were included in the study Subjects were not excluded because of possible or existing pulmonary or other diseases. Further details describing the automated multiphasic health testing system (AMHTS) and the screened populations have been given elsewhere D Each subject underwent a uniform battery of tests, which included a detailed computerized questionnaire;" physical examination by a physician, ECG, chest roentgenogram, and a comprehensive series of biochemical and physiologic tests (including height, weight, skinfold, blood glucose and cholesterol levels, and CBC). Smoking habits were recorded as reported by the examinee (categorized into four levels of current smoking, two levels of past smoking, and a group of never-smokers). Complaints of chronic cough were obtained from the computerized questionnaire. The WBC analyses were performed by a Coulter S analyzer. Almost three fourths of the enrolled subjects were of European extraction, 20 percent were of Mediterranean ancestry and 6 percent were second-generation Israeli born. Those of the last category were often of "mixed" ethnic origin. This relative distribution of subjects according to ethnic groups is similar to that found in a much larger sample of screened Israeli workers. 20 Five percent of the study group had only elementary school education, 40 percent were high school graduates, and 50 percent had college or higher education. This level of education is reflected in the types of occupations reported by these persons (skilled workers and professionals). About 50 percent of the participants were engaged in office-type jobs, and most others were industrial workers, drivers, or seafarers. Only a few subjects reported specific occupational exposure to pulmonary noxious materials. CHEST I 93 I 6 I JUNE

2 Table l-diatribution ofparticipanta By Smoking Habits, With Mean Values ofseveral Factors in the Smoking Categories FEV1±SO Smoking Mean Age, Mean Height, Mean WBC, Category No. yr cm 1()3 cells/mm" FEV., L (BTPS) FEV1% Never SM ± ± ± ±.66 l00± 14 (31)t PastSM ± ± ± ± ± 15 (light); (19) Past SM ± ± ± ± ± 14 (heavy) (16) Current SM (light) ± ± ± ±.55 99± 14 (7) Current SM < 1 P/O ± ± ± ±.72 97± 12 (8) Current SM-1 P/O ± ± ± ±.78 98± 15 (9) Current S~f>1 P/O ± ± ± ±.55 94± 13 (10) Mean Value 45.0± ± ± ±.66 loo± 14 Significance p=.oo4 NS p<.ooi NS p<.04 *FEV1% = mean observed/predicted value (in percentages) using the regression equation for nonsmokers in this study tnumbers in parentheses are percentage of the total group (307 persons). :l:light smokers: those smoking less than 10 cigarettes/day Heavy smokers: those smoking 1 P/O (pack/day) or more. Pulmonary Function Spirometric measurements were done with a 6-L water-filled Warren E. Collins Vitalometer. Measures of forced vital capacity (FVC) and forced expiratory volume in one second (FEV 1 ) were based on three satisfactory maximal forced expiratory maneuvers performed with the subject in the standing position (without a nose clip). The largest FVC and FEV 1 values of all acceptable trials were selected as "representative" test results, in accordance with the American Thoracic Society (ATS) criteria. Test efforts were maintained in most trials for at least six seconds of exhalation. All volumes were corrected to BTPS. Because some of the tall subjects exhaled to FVC volume of 6 L (maximal capacity of the spirometer used), it was thought that this measurement was not accurate in all cases. Therefore, in this report almost all data analyses presented are either of FEV1or as percent of predicted FEV1 (FEV 1%). Prediction formulas used here were based on data of nonsmokers in this study group. All computations were done on a COC 6400 computer using SPSS software package. RESULTS The distribution of subjects by their smoking habits is given in Table I. Ofthe 307 men in the study group, 105 (34 percent) are current smokers, 108 (35 percent) are past smokers, and 94 (31 percent) are lifelong nonsmokers (NSM). The level of cigarette smoking in adult males found in this study is similar to those in previous reports from Israel. 22 Current smokers are about five years younger than past smokers (one-way ANOVA, p<.oo4). The mean age of the study group is 45.0 ± 9.4 years (range, 20 to 70 years). There is no statistically significant difference in the mean height among the various smoking categories (mean height, ± 6.6 em), There is a statistically significant (p<.ooi) increase in WBC count concomitant with the level of smoking. Mean FEV} values (FEV}) were lower, but not significantly so, in smokers than in current nonsmokers. When corrected for age and height (by expressing FEV} values as percent predicted), mean FEV 1 % values (FEV}%) differ significantly among the various smoking categories (p<.04). A dose-response relationship between daily consumption of cigarettes (smoking intensity) and (lower) mean FEV} values is seen. Past smokers have higher mean VLF values than both never-smokers and current smokers. Toestimate the association of various health parameters with VLF measurements, we determined the crude frequency of these factors in the various quartiles of the FEV} frequency distribution. When there is no association between the concerned variable and the distribution of FEV., one can expect to observe about 25 percentof the subjects with that characteristic in each quartile of the VLF frequency distribution. If there is an association, an unequal proportion of subjects with that characteristic would be found in either end (extreme) of the distribution. To control for a possible effect of age or height, the frequency distribution of VLF as percent predicted (VLF%) is evaluated. Initially each factor is assessed individually The results are shown for data related to FEVh but very similarfindings also have been obtainedfor FVC% data. As expected, age and height are unrelated to FEV1% distribution (Table 2). Weight, Quetelet index (QI), blood pressure, and cholesterol values are not significantly different among the top and bottom quartiles. The mean WBC level (in the whole study group) is significantly higher (t = 4.73, p<.oo3) in persons in 1138 Ventilatory Lung Function in Working Men (Carel, Tockman, Baser)

3 Table 2-Distribution ofsubjects or Mean Values a/certain Variables in the Various Quartiles ofthe FEV.% Range Quartiles of FEV. % of predicted Factors and Their Categories Lowest 25-49% 50-74% Highest Total Age, yr 44.7± ± ± ± ±9.4 Height, ern 171.4± ± ± ± ±6.6 Weight, kg 77.1 ± ± ± ± ± 11.4 QI, kg/rn! 26±3 26±3 26±3 26±3 26±3 SBe mm Hg 126.6± ± ± ± ± 13.6 OB~ mm Hg 78.0± ± ± ± ± 10.9 Cholesterol, mg/dl 220.9± ± ± ± ±38.8 WBC Alit 7.82± ± ± ± ± 1.68 NSMt 7.38± ± ± ± ± 1.38 SM~1 Plot 9.14± ± ± ± ±2.05 Smoking history Never 21 (22) 29 (31) 22 (22) 22 (22) 94 (100) Past SM (light) 15 (25) 9 (15) 17 (29) 18 (31) 59 (100) Past SM (heavy) 7 (15) 9 18) 18 (36) 15 (31) 49 (100) Current SM (light) 5 (23) 8 (36) 4 (18) 5 (23) 22 (100) Current SM< 1 PID 8 (33) 11 (43) 3 (12) 3 (12) 25 (100) Current SM-l P/D 10 (37) 6 (21) 6 (21) 6 (21) 28 (100) Current SM>1 P/D 13 (43) 10 (33) 5 (16) 2 (8) 30 (100) Chronic cought Yes 10 (48) 5 (24) 5 (24) 1 (4) 21 (100) No 69 (24) 77 (27) 70 (24) 70 (24) 286 (100) Old TBt Yes 5 (83) 1 (17) 6 (100) No 74 (24) 82 (27) 75 (25) 70 (24) 301 (100) *Numbers in parentheses are percentages of the same row tstatistically significant difference between lowest and upper quartiles. The middle quartile values are shown in the table but not included in the statistical analyses. the lowest quartile as compared with members of the top quartiles offev 1 % distribution. This difference is most pronounced in current smokers of at least 1 pack! day (P/D) (t=4.96, p<.ool). Never-smokers demonstrate the same tendency but to a lesser extent (t = 3.76, p<.(02). In each quartile heavy smokers have significantly higher mean WBC values than nonsmokers (mean WBC difference, about 1,700 cells/cu mm in each category). Light current smokers are evenly distributed across FEV1% quartiles. When comparing the frequency distribution of subjects in the top and bottom quartiles between nonsmokers and current heavy smokers, a statistically significant difference is found (X 2 = 14.2, p=.(02). Of the many factors tested in a similar way only subjects complaining of chronic cough and those with mild x-ray film findings of old pulmonary tuberculosis (TB) are in significantly larger numbers in the lowest FEV 1% quartile compared with the top quartile. No difference in the proportion of subjects in the various FEV1% quartiles is found for ethnicity education, occupation; among subjects with diagnoses of obesity hypertension, or asthma; ECG findings of left ventricular hypertrophy ST-T changes; or chest x-ray film findings of increased bronchial markings (all of these variables are not shown in Table 2). Since the study group is composed of essentially healthy men, little may be gained from studying the relationship between VLF and disease states in this group. In comparing individuals at the lowest and highest deciles of the VLF% distribution, statistically significant differences are also found for mean cholesterol Table 3-Simpk Correlation Coefficients (r) Between VU and Certain Health Determination WBCt Height Age Weight A B C Cholesterol OBP SBP Smoking FEV :1: -.23 (-.11) :1: (-.06) FVC :1: -.20 (-.08) :1: -.12:1: (-.08) Height (-) (.11).15:1: (-.05) (-) (-) (-) Age (-.05) (-.08) (-) (-.04) (-.08) Weight (-.07) (.09) (-.05) *AII(r) values with no special markings are significant at p<.oollevel. t A= the whole group (307 men); B= nonsmokers only (153 men); C = heavy smokers only (58 men). :l:p<.05.; p>.05.; IIp<.01. CHEST / 93 / 6 / JUNE,

4 levels (225.6±38.1 mg/dl vs 214.0±38.8 mg/dl: p<.04) and for diastolic blood pressure (82.4 ± 12.1 mm Hg vs 77.6± 10.9 mm Hg; p<.ooi). Table 3 presents the simple linear correlation coefficients between VLF and various health parameters. As is well known, FVC and FEV 1 are highly correlated (r =.91). Both VLFs are most strongly correlated with height and (negatively) with age. Other variables have substantially lower correlation coefficients with VLF. Weight is positively correlated (r=.25) and WBC, cholesterol level and blood pressure are negatively correlated. Leukocyte count (in the whole group) is significantly correlated (r= -.14, p<.05) with VLF. Since the correlation between WBC and smoking (seven categories) is strong (r =.36, p<.ooi), it is important to determine whether the association between WBC and VLF exists independently of cigarette smoking. For nonsmokers (group B in Table 3), the correlation coefficient between VLF and WBC is -.23 for FEV 1 and -.20 for FVC. Further, after adjusting for the effect of smoking, WBC level is still significantly correlated with VLF% (r = -.18 for FEV1% and r= -.19 for FVC%, with p<.ooi for both). As expected, the correlation between smoking intensity and VLF reached a significant level (r= -.14 for FVC and r = -.12 for FEVI; p<.05 for both) after adjusting for age. The correlation of cholesterol with VLF is strong (r = -.20) and partly explained by the correlation between cholesterol and age (r =.24, p<.ooi). After adjusting for the effect of age, the correlation between cholesterol and VLF becomes much weaker. The same argument holds for the relationship between blood pressure and VLF. All other correlations ofvlf with various health variables are small (r<.oi) and not statistically significant (not shown in the table). To evaluate further the relative and combined effect of various health determinants on the VLF level, analysis of variance (ANOVA) ofvlf (as the dependent variable) by these relevant variables is performed. Table 4 presents the ANO\~ of FEV 1 and FEV 1% by several covariates (continuous variables) and certain main effects (discrete variables). Variables included in the ANOVA are those showing statistical relationship with VLF distribution in earlier analyses. Smoking level was divided into seven categories (see Table I). After accounting for the effect of height and age, which have, as expected, much larger F values than any other variable, the WBC level has a highly significant effect (p<.ooi). Cholesterol level (p<.04) and complaints of chronic cough (p<.02) are significant to a lesser extent. Smoking, ethnicity occupation, diagnoses of asthma, and old TB do not contribute significantly to the variance of VLF. Also, no interaction is found among the various determinants listed in the ANOVA. When the effects of age and height are eliminated (by performing ANOVA of FEV l% instead of FEVI)' WBC still has an effect on the variance of VLF% (p<.ooi), with some other determinants (diastolic blood pressure, chronic cough) having statistically significant but small effects. The results of multiple linear regression (MLR) analyses ofvlf (as the dependent variable) on several predictors (independent variables) are given in Table 5. The stepwise regression technique provides a method to determine the relative contribution of the concerned variables as they enter the regression (after accounting for the effects of all variables already in the regression). For both FVC and FEV l, height is the first (most contributory) variable to enter the regression equation. When height and age are included in the regression, the coefficient of determination (R2 =percentage of VLF variance explained by this mode) is.54 for FVC and.67 for FEV 1 (nonsmokers). In this type of regression, a uniform effect of age on VLF is assumed for the whole age span studied (a 1140 Ventilatory Lung Function in Working Men (Carel, Tockman. Baser)

5 Table 5-Stepwise Multiple Linear Regression Analysis ofvlf on Height (~., in Meters) and Age (~2' in Years) in Various Subgroups ofstudy Populations FVC,L FEV b L Group No. Con st. J31 J32 R R2 Const. s, ~2 R HZ The Whole Group NSM All WBC categories, 1()3 cells/mrn" WBC<6.5 NSM All SM WBC>6.5<8.0 NSM All SM WBC>8.0 NSM All M constant rate of loss of VLF throughout the whole range of age). The partial regression coefficient ofvlf on age (~2) is an estimate of the annual rate of decline of VLF after controlling for the effect of height on VLF based on cross-sectional data. For the whole group the value of ~2 is - 26 mllyear for FVC and - 23 mllyear for FEVI' The third independent variable to enter the (unforced) stepwise MLR for both FVC and FEV I is WBC. The regression equations with three predictors (for the whole study group) are: FVC (1.,)= height (m) age (yr)-.080 WBC (1Q3 cells/mm") FEV I (I.A) = height (m) age (yr) WBC (1Q3 cells/mm'') By adding to the MLR analysis, the R2 value rises from.54 to.57 for FVC, and from.46 to.48 for FEVi Thus, a regression equation with these three variables explains only additional 2 percent of the total variance of VLF compared with an equation with only two terms (height and age). Additional terms add only negligibly to the R2 value. In this study no higher order terms such as (age)" or (height)" were used as "predictors." Previous works have shown that little additional variance is explained by introducing such nonlinear terms into the regression equation. When performing similar MLR analyses in different WBC level categories (less than 6,500 cells/rum", 6,500 to 8,000 cells/rum", and over 8,000 cells/mm"), the age coefficient (~2) is less negative in the groups with lower WBC levels (in smokers and nonsmokers alike). For example, the age coefficient of FVC in the lowest WBC level (WBC<6,500) is - 27 mllyear, while in the middle group (WBC 6,500 to 8,000), it is -30 ml/year, and in the highest group (WBC>8,OOO) it is -40 ml/year. The corresponding values for FEV I are - 21 ml/year, - 26 ml/year, and - 43 mllyear, respectively In each WBC category the age coefficient is less negative in nonsmokers than in smokers. These findings demonstrate that WBC level is inversely related to VLF level and that this relationship is slightly more prominent in smokers than in nonsmokers. DISCUSSION Although cigarette smoking is the leading cause of chronic airways obstruction, only a small proportion of regular smokers develop significant clinical disease. Our data identify an association of WBC elevation with greater decline ofvlf per year of cross-sectional age. This observation suggests that the more susceptible smokers (those with accelerated rate of VLF decline) may be characterized by their level of leukocytes in the peripheral blood. These results confirm those of other tnvestigators'":" that WBC level is associated with smoking intensity (see Table 1). However, we also demonstrate that WBC is inversely related to VLF, independently of smoking (Tables 2 to 4). Moreover, the simple correlation between WBC level and VLF (Table 3) is statistically significant, while that of smoking is not. This correlation is more evident in nonsmokers than in smokers. The correlation between VLF and WBC falls only minimally after adjusting the leukocyte count for smoking intensity The mean WBC level is Significantly higher in the lowest quartile (or decile) of the VLF% distribution compared with the top quartile (see Table 2). This phenomenon is noted to a lesser extent for smoking level, attesting to the small average effect of smoking on cross-sectional VLF level. Of a broad variety of health characteristics (biochemical and physiologic variables, health complaints, diagnoses, and x-ray film findings) that were analyzed for possible association CHEST / 93 / 6 / JUNE,

6 with VLF level, WBC is the most closely associated determinant of VLF level after accounting for the association with height and age (see Table 4). Regression analysis shows thatthepartialregression coefficients of VLF on age are similar in smokers and nonsmokers (see Table 5). This indicates that, on average, smokers examined in this study (presumably healthy employed men) do not demonstrate an accelerated rate of decline of their lung function compared with nonsmokers. It is possible that the selection of working men has resulted in a population with better lung function across smoking categories. Such a selection, however, would not be expected to alter the association of WBC level with VLF. When comparing the partial (age) regression coefficients among several WBC categories, it is evident that groups of persons with relatively higher leukocyte counts have more negative annual rates of decline of their VLF than groups with lower mean WBC levels. These analyses suggest a role for leukocyte count as a predictor in evaluating VLF impairment. The association between elevated WBC levels and reduced VLF is found in both smokers and nonsmokers (see Tables 2 and 3). In this context, WBC level can be viewed as an independent risk factor (based on crosssectional data) for ascertaining compromised lung function, similar to its role as a predictor in the multiple causation of the development of myocardial infarction. 29 It should be noted that the correlation coefficients between VLF and WBC, though statistically significant, are much lower than those between VLF and height and age (see Table 3). When regressing VLF on various determinants, WBC enters the regression as the third variable but adds only about 2 to 3 percent to the explained variance (see Table 5). Smoking and other variables do not contribute significantly to the regression. The ability of peripheral WBCs to explain more of the VLF variance than smoking intensity may lead to certain hypotheses in regard to the relation of smoking, WBC, and reduced VLF. Cigarette smoking has been shown to be associated with accumulation of neutrophils in the lung. 30,31 However, the mechanism by which smoking causes this accumulation is not yet clear. It could be postulated that the WBC level in peripheral blood is proportionate to the WBC level in the lung. Thus, the WBC level in peripheral blood may be a more direct index of the potential degree of damage to lung tissue than smoking per see Several mechanisms could explain the role of leukocyte level as a risk factor in the development ofvlf impairment. First, elevated WBC could reflect the presence of chronic bronchitis. In this event, WBC elevation would be an indirect expression of the increased airways resistance and corresponding ob structive impairment associated with chronic bronchitis. Further evidence for the presence of inflammatory process in these individuals could be obtained from the relatively high percentage of persons with complaints of chronic cough (see Table 2) in the lowest quartile ofvlf distribution or from the ANOVA results (see Table 4). A second explanation might be based on the direct effect of leukocytes on the lung parenchyma. Recent experimental studies in animals and humans have shown that an excess in polymorphonuclear leukocytes in the lung tissue may play a dominant role in the pathogenesis of emphysema. The neutrophils present in the lung in greater numbers (following stimulation of alveolar macrophages by the inhaled smoke) release proteases (elastase), which induce degradation of lung elastin and destruction of pulmonary tissues. It could be postulated that smokers with a relatively higher level of peripheral leukocyte count may also have a greater tendency for neutrophils to migrate to the lung. Excess neutrophils in the lung result in enhanced release of elastolytic enzymes by these cells. Higher concentration of (unopposed) elastases disturb the protease-antiprotease balance regularly maintained in the lung. This process gradually leads to the development of chronic airway obstruction and pulmonary emphysema. The presence of a relatively high level of peripheral leukocyte count may constitute a particular risk factor for accelerated development of chronic airway obstruction. Longitudinal studies are required to confirm elevated WBCs as such a risk factor. If smokers with elevated leukocyte count in peripheral blood do demonstrate accelerated VLF decline, special smoking cessation efforts should be aimed at this high-risk group. This intervention may also reduce the risk of lung cancer and all-cause mortality REFERENCES 1 US Public Health Service. Smoking and health: a report of the Surgeon General. 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