Pulmonary Function of U.S. Coal Miners Related to Dust Exposure Estimates1 •2
MICHAEL D. ATTFIELD and THOMAS K. HODOUS Introduction
An obviously important aspect of the evaluation of exposure-responserelationships in coal miners is the accurate estimate of coal mine dust exposure. British Pneumoconiosis Field Research (PFR) studies have benefited in this regard from a systemic longitudinal program of dust measurement underground. These studieshave shown a clear relationship between dust exposure and pneumoconiosis (1-3), chronic bronchitis (4), and various parameters of ventilatory function (5-9).
In contrast, American prevalencestudies from the National Study of Coal Workers' Pneumoconiosis (NSCWP) have not involved simultaneous collection of dust exposure measurements. Instead, years of underground coal mine employment and occupational information have been used as surrogate measures of dust exposures (10-12). For example, the trend toward higher dust levels as one moves from surface to transportation to haulage to face work was used by Kibelstisand coworkers (10), who demonstrated a reduction in FEV, among never-smoking face workers compared with never-smoking surface workers. Later, Morgan and colleagues (11) investigated the association between FEV, and years underground and found small average reductions in FEV, with increasing tenure in all regional groups. Subsequently, using measurements of flows in another group of miners, Hankinson and colleagues (12) demonstrated that airflow decreased with increasing years underground after allowing for age and other confounding factors among both never smokers and current smokers. Despite these findings, the American exposure-response relationships have lacked precision due to the absence of a more refined dust estimate. For this reason British data have been used in the past for standard setting, although the validity of extrapolating British data to American coal miners has not been fully established. Recently, however, Attfield
SUMMARY This study of 7,139U.S. coal miners used linear regression analysis to relate estimates of cumulative dust exposure to several pulmonary function variables measured during medical examinations undertaken bet_en 1969 and 1971. The exposure data Included newly derived cumulative dust exposure estimates for the period up to time of examination based on large data bases of underground airborne duat sempllng measurementa. Negative associations _re found bet_en measures of cumulative exposure and FEV" FYC, and the FEV,/FVC ratio (p < 0.001). In general, the relationships _re similar to those reported for British coal miners. Overall, the resulta demonstrata an adverse effect of coal mine dust exposure on pUlmonary function that occurs even In the absence of radiographically detected pneumoconiosis. AM REV RESPIR DIS 1992; 145:805-809
and Morring (13) have developed jobspecific cumulative dust exposure estimates for U.S. underground coal miners. These werebased on previouslypublished surveys (14) as well as compliance data of the Mine Safety and Health Administration (MSHA). The resulting dust exposure estimates werecorrelated with various indices of prevalence of coal workers pneumoconiosis (CWP), and clear relationships emerged (15). This report takes this new information on dust exposure and applies it to exposureresponse models for FEV 10 FVC, and FEV,/FVC. Methods Medical Data The medical data analyzed here were drawn from the first round of the NSCWP, which took place from 1969to 1971. These data were chosen over data from later rounds of the study because of the excellent participation at that round (91070) and because the miners, in general, had received much higher dust exposures before Round I than they have received since that time. A greater range of exposures facilitates the detection of exposureresponse relationships. The analyses presented here are confined to a subset of 9,078 miners examined at Round 1, consisting of 7,139 white men aged 25 yr or older. Information on ventilatory function, chest symptoms, age, height, and working and smoking history was collected during the medical surveys. In addition, posterior-anterior and lateral chest roentgenograms were taken. The FEV 1 and FVC values used in analysis were derived from the maximum of five forced expiratory maneuvers using a rolling
seal volume spirometer. The percentage of FEV,/FVC ratio (FEV ,/FVCOfo) was obtained using the maximum FEV, and FVC maneuvers. Data for those miners who could not provide at least three acceptable blows were omitted. (For further details on the methods used see Morgan and colleagues [11].) Packyears of smoking was estimated by multiplying the reported packs smoked per day by the reported duration of smoking in years.
Cumulative Dust Exposures Attfield and Morring (13) describe in detail how the cumulative dust exposure estimates used here were derived. Briefly,respirable dust concentrations from sampling undertaken between 1970 and 1972 by coal mine operators under regulations promulgated by MSHA were back-extrapolated to pre-1970conditions using a ratio derived from measurements made at many of the NSCWP mines during an intensive survey by the Bureau of Mines (BOM) between 1967 and 1968 (14). The resulting concentrations were linked with miner-reported work histories to produce cumulative exposures. In order to obtain the estimated exposures in units of gram-hours per cubic meter (gh/m") a factor of 1,740 (hours per year)/1,OOO (mg per g) was used. These exposure estimates were not adjusted for mine-to-mine variation, as it was felt that the
(Received in original form June 21, 1991 and in revised form September 13, 1991) 1 From the Division of Respiratory Disease Studies, National Institute for Occupational Safety and Health, Morgantown, West Virginia. 2 Correspondence and requests for reprints should be addressed to Michael D. Attfield, Division of Respiratory Disease Studies, NIOSH, 944 Chestnut Ridge Road, Morgantown, WV 26505.
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ATTAELD AND HODOUS
data on inter-mine variations in dust levelwere not sufficiently reliable. In the process of developing dust exposure estimates, Attfield and Morring looked at variations in the basic computational strategy (including an attempt to adjust for mine effects). In order to investigate the sensitivity of the basic approach to these variations, the resulting alternative exposure estimates were correlated with ventilatory function. Comparison ofthe results with those from the basic approach is made in the DISCUSSION.
Regional Effects Possible regional variations in ventilatory function were allowed for by including factorial terms (dummy variables) in the modeling. The regions were: anthracite (eastern Pennsylvania), central Pennsylvania, northern Appalachia (Ohio, northern West Virginia, western Pennsylvania), southern Appalachia (southern West Virginia, eastern Kentucky, western Virginia), Midwest (Illinois, western Kentucky), South (Alabama), and West (Colorado and Utah). Analysis FEV, and FVC were expressed in milliliters for the purpose of analysis. The main modeling consisted of linear regressions of FEV" FVC, and FEV,/FVCOJo against age, height, smoking status, pack-years of cigarette smoking, and estimated cumulative dust exposure, with and without regional effects, using the GLM procedure of the SAS system (SAS Institute, Cary, NC) (16). In order to inquire into any synergistic relationship between dust exposure and smoking, separate models were fit by smoking group, and an interaction term for pack-years and estimated dust exposure was added to the basic model. Subsidiary analyses were undertaken on two subsets of the data. The first selection consisted of those miners who were apparently free of CWP at the time of examination based on consensus determinations (agreementbetweentwo ofthree independent1yobtained readings). The second subset analysis was undertaken on miners from the 17 mines in common to the BOM survey data and NSCWP. Lastly, in order to be sure that the results from the preceding analyses werenot artifacts arising from choiceofpredictor variables,other analyses were undertaken. These included alternative estimates of dust exposure and models using smoking group x age and smoking group x dust exposure interactions instead of pack-years and pack-years x dust exposure. The collinearity between the various time-related variables was also investigated. Results
Basic Statistics Table 1 gives summary statistics for the variables used in the various analyses reported next. Of the total number of
Table 2 summarizes the coefficients and related information for the basic model. This model allowed for age, height, geographic region, smoking staVariable Mean SO tus, pack-yearsof smoking (zero for never No. of observations 7,139 smokers), and estimated cumulative dust Age, yr 10.4 45.8 It accounted for 47% of the exposure. Height, inches 2.6 69.2 total variability in the observed FEV, Years underground 13.2 18.0 PaCk-years, smokers 15.4 23.4 values. One year in age was associated Pack-years, exsmokers 18.7 23.1 with a decrement in FEV, of 31 ml, Estimated cumulative dust whereas the relationship with pack-years exposures, ghlm' 116 77 suggested a loss of about 5 ml for every 0.76 3.48 FEV" L FVC, L 0.85 3.76 pack-year of cigarette smoking. StatistiFEV,IFVC% 9.1 73.1 cally significant regional effects were seen, the principal differences being between the eastern and western mines. The coefficient for estimated cumulative 7,139miners studied, 53 % were smokers dust exposure was -0.69 ml/gh/m" at the time of examination and 270/0 were (p < 0.0001). exsmokers. The question as to whether there is a synergistic effect between smoking and FE~ and Dust Exposure dust exposure was explored by analyzThe basic relationship between FEV, and ing the data for each smoking group estimated cumulative dust exposure is separately and by adding a pack-years/ shown in figures I to 3 by age and smok- dust exposure interaction term to the ing group. Effects of age and smoking overall model. The separate regressions are obvious. More importantly, an associ- indicated that the dust exposure relationation with dust exposure is clearly notice- ship was more severe in never smokers able among the never smokers and for and exsmokers (- 0.73 and -1.0 mIl the exsmokers. An association with dust gh/rrr', respectively) compared with curexposure is also apparent in the current rent smokers (-0.44 ml/gh/m"), Howsmokers, although it appears smaller in ever, the overall model with the interacmagnitude and less consistent. tion term suggestedthat these differences TABLE 1
SUMMARY STATISTICS FOR VARIABLES USED IN MODEL rrrnac
4
Hlgh~
3.5
3
2.5
Fig. 1. FE\/, versus age for three cumulative dust exposure groups (never smokers). Exposures groups (ghlm'): low, < 80; medium, 80 - < 160; high, .. 160.
+--.------,---_._----,-----,..--____,__----r------,-------, 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64
Age (years)
FEV, (liters) 4.5
Low dust 4
Fig. 2. FEY, versus age for three cumulative dust exposure groups (exsmokers). Exposuregroups(ghlm'): low, 0.10). The results certainly did not indicate that the combined effect of smoking and dust exposure is worse than the additive effect of each. In order to eliminate any effects due to CWP on the relationship between FEV 1 and dust exposure, the basic model was fit to the subset of miners who had no radiographic evidence of CWP at the time of examination (n = 4,913). The results revealed a dust exposure coefficient of -0.75 ml/gh/m" (p < 0.001), which is essentially the same as the value previously obtained for all miners. The last analysis of this series used the medical data for miners working at only those mines sampled in the BOM environmental survey (14). Because only 17
of the NSCWP mines were in common with those visited by the BOM industrial hygienists, it might be thought that the derived cumulative dust exposures should be applied only to those mines. The coefficient on dust exposure was found to be just under - 0.65/ml/gh/m3 for this subset, and thus close to that for all miners shown earlier. PVC and FEV11FVCO/O and
Dust Exposure The basic model shown in table 2 was fit also to FVC and FEVI/FVCOJo (table 3). The findings for FVC were very similar to those for FEV h with a dust exposure relationship being detected, albeit to a somewhat lesser extent (-0.49 mIl gh/rn", p < 0.001). The fit of the basic
TABLE 2 REGRESSION COEFFICIENTS AND t STATISTICS FOR FEV, AGAINST AGE, HEIGHT, REGION, SMOKING, AND CUMULATIVE DUST EXPOSURE' Cosfficient Variable Constant, ml Height, inches Age, yr Smoking status relative to never smokers Exsmokers Current smokers Pack-years Regional effects relative to the West Anthracite Central Pennsylvania Northern Appalachia Southern Appalachia South Midwest Estimated cumulative dust exposure, gh/m'
R2 Residual root mean square error Residual df Definition of abbreviation: df ~ degrees of freedom. • Test that coefficients are different from zero.
t p < 0.0001.
ml
-1,702 100 -31 -36 208 -5.0
38.2t -31.4t -10.0t -1.6 -9.9t
t -242 -158 -225 -224 -204 -219 -0.69 0.47 0.55 7.126
-5.5t
model to FEV 1IFVC OJo was not as good, the R 2 value being 0.17. Moreover, the regional effects were not so pronounced as for FEV 1 and FVC, although strong relationships were seen with age, height, pack-years, and cumulative dust exposure (p < 0.0001). No suggestion of an interaction effect between smoking and dust exposure was seen for FVC (p = 0.48) for the FEV 1/FVCOJo ratio (p == 0.57). The basic model was also fit using FVC and FEV 1/FVCOJo to the two subsets of miners defined on the basis of absence of CWP and the BOM/NSCWP overlap. In the first case, relationships with dust exposure were still evident after the omission of all miners with X-ray appearances of CWP, the coefficients being almost unaltered in value. The same was true for the NSCWP subset, although as with FEV 1 the coefficients were slightly smaller in magnitude. Discussion This report represents the first attempt at using data from the NSCWP to correlate pulmonary function with cumulative dust exposure estimates derived from actual mine airborne dust measurements. The various models of exposure show consistent declines in FEVI, FVC, and FEV l/FVC with increasing dust exposure. The environmental data used to derive the cumulative dust exposures employed here have both positive and negative qualities. On the plus side, they are based on many hundreds, and often thousands, of observations. In addition, data were available for nearly all jobs worked by the miners in the study, and the sampling tended to be more intense where dust levels were higher. On the other hand, the dust samples were collected toward the end of the period to which they were applied in this analysis; lack of any published information on temporal changes in dust level for the period 1950 to 1970 makes it impossible to assess whether this back-extrapolation is completely valid. (It is felt that conditions remained fairly constant from about 1960 to 1970, but it is unclear whether dust levels were higher or lower before that time [unpublished communications].) One point favoring the validity of the exposure estimates is their correlation with prevalence of CWP (15). In derivation of the dust exposure estimates used here it was not completely clear which of the many variations in approach was the most valid. The results
ATTFIELD AND HODOUS
608 TABLE 3 REGRESSION COEFFICIENTS AND t STATISTICS FOR FVC AND FEV,/FVC% AGAINST AGE. HEIGHT. REGION. SMOKING. AND CUMULATIVE DUST EXPOSURE' FEV,/FVC%
FVC
Constant. ml Height. inches Age. yr Smoking status relative to never smokers Exsmokers Current smokers Pack-years Regional effects relative to the West Anthracite Central Pennsylvania Northern Appalachia Southern Appalachia South Midwest Estimated cumulative dust exposure. gh/m'
%
ml
Variable
-4.584 155 -26
R2 Residual root mean square error Residual df
28 -87 -2.3
51.1:1: -22.8:1:
106.8 -0.261 -0.253
-6.7:1: -17.1:1:
1.1 -3.6t -4.1:1:
-1.18 -3.17 -0.069
-3.6t -10.2:1: -9.7:1:
:j:
-451 -232 -366 -309 -282 -342 -0.49 0.44 0.64 7.126
t
1.73 0.31 0.87 -0.03 0.09 0.58 -0.008 0.18 8.2 7.126
• Test that coefficients are different from zero.
t p < 0.001. :I: p < 0.0001.
presented are based on the strategy felt to be most reliable. Other exposure estimates, developed using variations on the basic strategy (13), were correlated with ventilatory function in an attempt to assess the sensitivity of the results to variations in method. They gave rise to coefficients for dust exposure ranging between -0.51 to -0.62 ml/gh/m", Although these are a little smaller than the figure of -0.69 in table 1, they were still very unlikely to be due to chance (P < 0.0001). Regional effects were included in the regression models in order to allow for systematic differences between geographic areas ofthe country. Results from British miners have indicated that such factors exist and should be taken into account (6). It is not known why systematic effects occur, but they could have been due to many factors, including climate, life-style, ethnicity, season of year, and technical reasons. However, one problem with allowing for regional effects is that geographic region is confounded with geologic variations in coal type. Hence, allowance for region may remove some of the effect rightly due to coal dust exposure. To determine the possible extent of this effect, the basic model was run omitting regional effects. When this was done, the dust exposure coefficient on FEV 1 rose from - 0.69 to - 0.80 ml/gh/m", Dust concentrations for certain jobs at the coal mine face were apparently 6 mg/m" or greater on average before the 1969 Federal Coal Mine Safety and
Health Act (14), implying a yearly exposure of about 10 gh/m", These exposures, taken in conjunction with the various estimates for dust exposures on FEV 1 noted previously, suggest a decrement of 5 to 9 ml/yr, Under the current 2 mg/m" federal dust limit, the predicted dust effect should obviously be about one-third of that (i,e., 2 to 3 mllyr). In this respect, an exposure of 2 mg/m! over a 4O-yr working life at the coal face would be associated with roughly a l00-mlloss in FEV l • If it is thought that a 5- to 9-ml decrement of FEV 1 per year is clinically insignificant, it must be remembered that the average decrement for smokers was only 5 ml per pack-year. This, in itself, is also a minor loss in lung function. However, it is well known that smoking can cause severe effects in some smokers. Hence, this small average loss among smokers conceals some severe long-term effects in a minority. Could it then be that the average decrement of 5 to 9 ml associated with dust exposure also hides some severe dust exposure effects? Further study is continuing on this topic. The existence of such an effect is suggested in the findings of Hurley and Soutar (7), who detected a subgroup of miners with severe dust-related losses in FEV l . Pack-years was used in the regression analyses in this report because its use has been stated to be more appropriate than employment of categorical terms for smoking adjustment (17). However, since some prefer the latter approach, an anal-
ysis was undertaken replacing pack-years with dummy variables for the three smoking groups, and variables representing their interaction with age. The results gave rise to a dust exposure coefficient of -0.65 ml/gh/m" (p < 0.001), very similar to that obtained in the model using pack-years. Addition of an interaction term representing systematic differences in dust exposure between the smoking groups to this model did not suggest that the exposure effect varied over the smoking groups (p > 0.10). Because the interaction terms for smoking and dust exposure in the latter model and in that based on pack-years werenot significantly different from zero, synergism between smoking and dust exposure was not evident in these data. Indeed, if anything, there was a suggestion that smokers might suffer less of an effect of dust exposure than did their neversmoking colleagues. It would be unwise to conclude from this that smoking might have a protective effect against dust exposure, however, because the observed effect could wellhave been due to selection caused by the departure from the industry of miners affected by their exposure to both tobacco smoke and dust. In any study such as this, with several time-related variables, multicollinearity is a potential problem. Although collinearity does not lead to biased estimates of coefficients, their variability may be increased, with the result that estimates of the coefficients may be far from their true values in any particular analysis. However, the effects of multicollinearity can be offset by increasing the sample size, as variance is inversely proportional to numbers of observations. Because of the large sample size in this study, the problems associated with collinearity are somewhat mitigated. A study of collinearity in the data revealed that as the dust exposure coefficient declined toward zero, the age coefficient rose to smokingadjusted values of - 32 to - 37 ml/yr, values much greater than those commonly encountered ill prediction equations for FEV l (-23 to -29 mllyr) (18-22). These large age-related declines seem less plausible than the alternative view that a real dust exposure effect exists. Morgan (23) has argued that the effects of smoking and dust exposure are different, smoking leading to severedamage in a minority whereas dust exposure causes small losses in the majority. In an analysis relating to this topic, Attfield and Hodous (results presented at the 1989 American Thoracic Society conference) examined the distribution of FEV 1 values
PULMONARY FUNCTION OF U.S. COAL MINERS
in smokers and never smokers but failed nificance of their dust exposure coeffito find support for this hypothesis. Over- cient was less than for the models involvall, it appeared that dust and smoking ing FEV 1 and FVC. In summary, this study has found clear acted similarly on ventilatory function in causing a general shift of the FEV 1 dis- exposure-response relationships between various pulmonary function parameters tribution to lower values. The estimates of FEV 1 decline on dust and estimated cumulative dust exposure exposure given in this report are very simi- in a large national cohort of U.S. underlar to figures reported for British miners. ground coal miners. The results indicate Rogan and coworkers (5) detected a that miners working in dusty conditions reduction in FEV 1 with cumulative dust (6 mg/m") could experience average efexposure of - 0.6 ml/gh/m". Soutar and fects not unlike those seen for smokers. Hurley (6) obtained an estimate of the The results weregenerally consistent with dust exposure effect of -0.76 ml/gh/m" findings from a study of British underground coal miners. among a group of current and exminers. As in this study, they found that the effect Acknowledgment of dust was not greater in current smokers. Furthermore, they also showed that The writers thank the many who have assistthe relationship between dust exposure ed in the collection and processing of data, and FEV 1 was similar in miners who did those who have given other information or advice, and those who have reviewed the and did not have pneumoconiosis. Soutar and Hurley (6) found that not manuscript and supplied many useful comonly was FEV 1 related to cumulative dust ments and suggestions. exposure, but that a similar trend was also References found for FVC. This observation had 1. Jacobsen M, Rae S, Walton WH, Rogan JM. been reported earlier by Morgan and coThe relation between pneumoconiosis and dust exworkers for U.S. miners (11) using years posure in British coal mines. In: Walton WH, ed. of underground work. Because the cur- Inhaled particles. III. Old Woking, Surrey,UK: Unrent report is based on essentially the win Bros., 1971; 903-19. same set of data, it is not surprising that 2. McLintock JS, Rae S, Jacobsen M. The attack the same phenomenon appears in the rate of progressive massive fibrosis in British In: Walton WH, ed, Inhaled particles. present results. Morgan and coworkers, coalminers. III. Old Woking, Surrey, UK: Unwin Bros., 1971; however, did not use dust exposure esti- 933-52. mates, and hence the present results have 3. Jacobsen M, Burns J, Attfield MD. Smoking not been reported previously. The cur- and coal workers' simple pneumoconiosis. In: Walrent results confirm the trend of FVC ton WH, ed. Inhaled particles. IV. Oxford: Pergamon Press, 1977; 759-71. with dust exposures seen in the British 4. Rae S, Walker DD, Attfield MD. Chronic bronminers. chitis and dust exposure in British coal miners. In: Morgan and colleagues reported that Walton WH, ed. Inhaled particles. III. Old Wokyears underground had no effect on ing, Surrey, UK: Unwin Bros., 1971; 883-96. 5. Rogan JM, Attfield MD, Jacobsen M, Rae S, FEV 1/FVCOJo. The findings of this study Walker DD, Walton WHoRole of dust in the workdo not support that statement, as a rela- ing environment in the development of chronic tionship with FEV l/FVCOJo and estimat- bronchitis in Britishcoal miners.Br J Ind Med 1973; ed dust exposure was detected (- 0.0080J01 30:217-26. gh/m", p < 0.0001), although the size of 6. Soutar CA, Hurley JF. Relation between dust exposureand lung function in minersand ex-miners. the effect was clearly not large. Soutar Br J Ind Med 1986; 43:307-20. and Hurley (6) also found a small coeffi- 7. Hurley JF, Soutar CA. Can exposure to cient for the ratio (-0.OO50J0/gh/m 3 ) ; in coalmine dust cause a severe impairment of lung contrast to this study, the statistical sig- function. Br J Ind Med 1986; 43:150-7.
609 8. LoveRG, Miller BG. Longitudinal study of lung function in coal miners. Thorax 1982; 37:193-7. 9. Marine WM, Gurr D, Jacobsen M. Clinically important respiratory effects of dust exposure and smoking in British coal miners. Am Rev Respir Dis 1988; 137:106-12. 10. Kibelstis JS, Morgan EJ, Reger R, Lapp NL, Seaton A, Morgan WKC. Prevalence of bronchitis and airways obstruction in American bituminous coal miners. Am Rev Respir Dis 1973; 108:886-93. 11. Morgan WKC, Handelsman L, Kibelstis J, Lapp NL, Reger R. Ventilatory capacity and lung volumes of US coal miners. Arch Environ Health 1974; 28:182-9. 12. Hankinson JL, Reger RB, Fairman RP, Lapp NL, Morgan WKC. Factors influencing expiratory flow rates in coal miners. In: Walton WH, ed. Inhaled particles. IV. Oxford: Pergamon Press, . 1977; 735-55. 13. Attfield MD, Morring K. The derivation of dust exposures for U.S. coal miners working before 1970. Am Ind Hyg Assoc J (In Press). 14. Jacobson M. Respirable dust in bituminous coal mines in the U.S. In: Walton WH, ed. Inhaled particles. III. Old Woking,Surrey, UK: UnwinBros., 1971; 745-55. 15. Attfield MD, Morring K. Some investigations into the relationship between coalworkers' pneumoconiosis and dust exposure in U.S.coal miners. Am Ind Hyg Assoc J (In Press). 16. SAS Institute Inc. SAS$ User's Guide: Statistics, version 5 edition. Cary, NC: SASInstitute Inc., 1985; 433-506. 17. Morgan WKC. Letter to the editor. Thorax 1983; 38:878. 18. Crapo RO, Morris AH, Gardner RM. Reference spirometric values using techniques and equipment that meet ATS recommendations. Am Rev Respir Dis 1981; 123:659-64. 19. Knudsen RJ, Slatin RC, Lebowitz MD, Burrows B.The maximal expiratory flow-volume curve. Normal standards, variability, and effects of age. Am Rev Respir Dis 1976; 115:587-600. 20. Knudsen RL, LebowitzMD, Holberg CJ, Burrows B. Changes in the normal maximal expiratory flow-volume curve with growth and aging. Am Rev Respir Dis 1983; 127:725-34. 21. Miller A, Thornton JC, Warshaw R, Bernstein J, Selikoff IJ, Teirstein AS. Mean and instantaneous expiratory flows, FVC and FEV,: prediction equations from a probability sample of Michigan, a large industrial state. BullEur Physiopathol Respir 1986; 22:589-97. 22. Morris JF, Koski A, Johnson LC. Spirometric standards for healthy nonsmoking adults. Am Rev Respir Dis 1971; 103:57-67. 23. Morgan WKC. On dust, disability, and death (editorial). Am Rev Respir Dis 1986; 134:639-41.
MICHAEL D. ATTFIELD and THOMAS K. HODOUS Introduction
An obviously important aspect of the evaluation of exposure-responserelationships in coal miners is the accurate estimate of coal mine dust exposure. British Pneumoconiosis Field Research (PFR) studies have benefited in this regard from a systemic longitudinal program of dust measurement underground. These studieshave shown a clear relationship between dust exposure and pneumoconiosis (1-3), chronic bronchitis (4), and various parameters of ventilatory function (5-9).
In contrast, American prevalencestudies from the National Study of Coal Workers' Pneumoconiosis (NSCWP) have not involved simultaneous collection of dust exposure measurements. Instead, years of underground coal mine employment and occupational information have been used as surrogate measures of dust exposures (10-12). For example, the trend toward higher dust levels as one moves from surface to transportation to haulage to face work was used by Kibelstisand coworkers (10), who demonstrated a reduction in FEV, among never-smoking face workers compared with never-smoking surface workers. Later, Morgan and colleagues (11) investigated the association between FEV, and years underground and found small average reductions in FEV, with increasing tenure in all regional groups. Subsequently, using measurements of flows in another group of miners, Hankinson and colleagues (12) demonstrated that airflow decreased with increasing years underground after allowing for age and other confounding factors among both never smokers and current smokers. Despite these findings, the American exposure-response relationships have lacked precision due to the absence of a more refined dust estimate. For this reason British data have been used in the past for standard setting, although the validity of extrapolating British data to American coal miners has not been fully established. Recently, however, Attfield
SUMMARY This study of 7,139U.S. coal miners used linear regression analysis to relate estimates of cumulative dust exposure to several pulmonary function variables measured during medical examinations undertaken bet_en 1969 and 1971. The exposure data Included newly derived cumulative dust exposure estimates for the period up to time of examination based on large data bases of underground airborne duat sempllng measurementa. Negative associations _re found bet_en measures of cumulative exposure and FEV" FYC, and the FEV,/FVC ratio (p < 0.001). In general, the relationships _re similar to those reported for British coal miners. Overall, the resulta demonstrata an adverse effect of coal mine dust exposure on pUlmonary function that occurs even In the absence of radiographically detected pneumoconiosis. AM REV RESPIR DIS 1992; 145:805-809
and Morring (13) have developed jobspecific cumulative dust exposure estimates for U.S. underground coal miners. These werebased on previouslypublished surveys (14) as well as compliance data of the Mine Safety and Health Administration (MSHA). The resulting dust exposure estimates werecorrelated with various indices of prevalence of coal workers pneumoconiosis (CWP), and clear relationships emerged (15). This report takes this new information on dust exposure and applies it to exposureresponse models for FEV 10 FVC, and FEV,/FVC. Methods Medical Data The medical data analyzed here were drawn from the first round of the NSCWP, which took place from 1969to 1971. These data were chosen over data from later rounds of the study because of the excellent participation at that round (91070) and because the miners, in general, had received much higher dust exposures before Round I than they have received since that time. A greater range of exposures facilitates the detection of exposureresponse relationships. The analyses presented here are confined to a subset of 9,078 miners examined at Round 1, consisting of 7,139 white men aged 25 yr or older. Information on ventilatory function, chest symptoms, age, height, and working and smoking history was collected during the medical surveys. In addition, posterior-anterior and lateral chest roentgenograms were taken. The FEV 1 and FVC values used in analysis were derived from the maximum of five forced expiratory maneuvers using a rolling
seal volume spirometer. The percentage of FEV,/FVC ratio (FEV ,/FVCOfo) was obtained using the maximum FEV, and FVC maneuvers. Data for those miners who could not provide at least three acceptable blows were omitted. (For further details on the methods used see Morgan and colleagues [11].) Packyears of smoking was estimated by multiplying the reported packs smoked per day by the reported duration of smoking in years.
Cumulative Dust Exposures Attfield and Morring (13) describe in detail how the cumulative dust exposure estimates used here were derived. Briefly,respirable dust concentrations from sampling undertaken between 1970 and 1972 by coal mine operators under regulations promulgated by MSHA were back-extrapolated to pre-1970conditions using a ratio derived from measurements made at many of the NSCWP mines during an intensive survey by the Bureau of Mines (BOM) between 1967 and 1968 (14). The resulting concentrations were linked with miner-reported work histories to produce cumulative exposures. In order to obtain the estimated exposures in units of gram-hours per cubic meter (gh/m") a factor of 1,740 (hours per year)/1,OOO (mg per g) was used. These exposure estimates were not adjusted for mine-to-mine variation, as it was felt that the
(Received in original form June 21, 1991 and in revised form September 13, 1991) 1 From the Division of Respiratory Disease Studies, National Institute for Occupational Safety and Health, Morgantown, West Virginia. 2 Correspondence and requests for reprints should be addressed to Michael D. Attfield, Division of Respiratory Disease Studies, NIOSH, 944 Chestnut Ridge Road, Morgantown, WV 26505.
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ATTAELD AND HODOUS
data on inter-mine variations in dust levelwere not sufficiently reliable. In the process of developing dust exposure estimates, Attfield and Morring looked at variations in the basic computational strategy (including an attempt to adjust for mine effects). In order to investigate the sensitivity of the basic approach to these variations, the resulting alternative exposure estimates were correlated with ventilatory function. Comparison ofthe results with those from the basic approach is made in the DISCUSSION.
Regional Effects Possible regional variations in ventilatory function were allowed for by including factorial terms (dummy variables) in the modeling. The regions were: anthracite (eastern Pennsylvania), central Pennsylvania, northern Appalachia (Ohio, northern West Virginia, western Pennsylvania), southern Appalachia (southern West Virginia, eastern Kentucky, western Virginia), Midwest (Illinois, western Kentucky), South (Alabama), and West (Colorado and Utah). Analysis FEV, and FVC were expressed in milliliters for the purpose of analysis. The main modeling consisted of linear regressions of FEV" FVC, and FEV,/FVCOJo against age, height, smoking status, pack-years of cigarette smoking, and estimated cumulative dust exposure, with and without regional effects, using the GLM procedure of the SAS system (SAS Institute, Cary, NC) (16). In order to inquire into any synergistic relationship between dust exposure and smoking, separate models were fit by smoking group, and an interaction term for pack-years and estimated dust exposure was added to the basic model. Subsidiary analyses were undertaken on two subsets of the data. The first selection consisted of those miners who were apparently free of CWP at the time of examination based on consensus determinations (agreementbetweentwo ofthree independent1yobtained readings). The second subset analysis was undertaken on miners from the 17 mines in common to the BOM survey data and NSCWP. Lastly, in order to be sure that the results from the preceding analyses werenot artifacts arising from choiceofpredictor variables,other analyses were undertaken. These included alternative estimates of dust exposure and models using smoking group x age and smoking group x dust exposure interactions instead of pack-years and pack-years x dust exposure. The collinearity between the various time-related variables was also investigated. Results
Basic Statistics Table 1 gives summary statistics for the variables used in the various analyses reported next. Of the total number of
Table 2 summarizes the coefficients and related information for the basic model. This model allowed for age, height, geographic region, smoking staVariable Mean SO tus, pack-yearsof smoking (zero for never No. of observations 7,139 smokers), and estimated cumulative dust Age, yr 10.4 45.8 It accounted for 47% of the exposure. Height, inches 2.6 69.2 total variability in the observed FEV, Years underground 13.2 18.0 PaCk-years, smokers 15.4 23.4 values. One year in age was associated Pack-years, exsmokers 18.7 23.1 with a decrement in FEV, of 31 ml, Estimated cumulative dust whereas the relationship with pack-years exposures, ghlm' 116 77 suggested a loss of about 5 ml for every 0.76 3.48 FEV" L FVC, L 0.85 3.76 pack-year of cigarette smoking. StatistiFEV,IFVC% 9.1 73.1 cally significant regional effects were seen, the principal differences being between the eastern and western mines. The coefficient for estimated cumulative 7,139miners studied, 53 % were smokers dust exposure was -0.69 ml/gh/m" at the time of examination and 270/0 were (p < 0.0001). exsmokers. The question as to whether there is a synergistic effect between smoking and FE~ and Dust Exposure dust exposure was explored by analyzThe basic relationship between FEV, and ing the data for each smoking group estimated cumulative dust exposure is separately and by adding a pack-years/ shown in figures I to 3 by age and smok- dust exposure interaction term to the ing group. Effects of age and smoking overall model. The separate regressions are obvious. More importantly, an associ- indicated that the dust exposure relationation with dust exposure is clearly notice- ship was more severe in never smokers able among the never smokers and for and exsmokers (- 0.73 and -1.0 mIl the exsmokers. An association with dust gh/rrr', respectively) compared with curexposure is also apparent in the current rent smokers (-0.44 ml/gh/m"), Howsmokers, although it appears smaller in ever, the overall model with the interacmagnitude and less consistent. tion term suggestedthat these differences TABLE 1
SUMMARY STATISTICS FOR VARIABLES USED IN MODEL rrrnac
4
Hlgh~
3.5
3
2.5
Fig. 1. FE\/, versus age for three cumulative dust exposure groups (never smokers). Exposures groups (ghlm'): low, < 80; medium, 80 - < 160; high, .. 160.
+--.------,---_._----,-----,..--____,__----r------,-------, 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64
Age (years)
FEV, (liters) 4.5
Low dust 4
Fig. 2. FEY, versus age for three cumulative dust exposure groups (exsmokers). Exposuregroups(ghlm'): low, 0.10). The results certainly did not indicate that the combined effect of smoking and dust exposure is worse than the additive effect of each. In order to eliminate any effects due to CWP on the relationship between FEV 1 and dust exposure, the basic model was fit to the subset of miners who had no radiographic evidence of CWP at the time of examination (n = 4,913). The results revealed a dust exposure coefficient of -0.75 ml/gh/m" (p < 0.001), which is essentially the same as the value previously obtained for all miners. The last analysis of this series used the medical data for miners working at only those mines sampled in the BOM environmental survey (14). Because only 17
of the NSCWP mines were in common with those visited by the BOM industrial hygienists, it might be thought that the derived cumulative dust exposures should be applied only to those mines. The coefficient on dust exposure was found to be just under - 0.65/ml/gh/m3 for this subset, and thus close to that for all miners shown earlier. PVC and FEV11FVCO/O and
Dust Exposure The basic model shown in table 2 was fit also to FVC and FEVI/FVCOJo (table 3). The findings for FVC were very similar to those for FEV h with a dust exposure relationship being detected, albeit to a somewhat lesser extent (-0.49 mIl gh/rn", p < 0.001). The fit of the basic
TABLE 2 REGRESSION COEFFICIENTS AND t STATISTICS FOR FEV, AGAINST AGE, HEIGHT, REGION, SMOKING, AND CUMULATIVE DUST EXPOSURE' Cosfficient Variable Constant, ml Height, inches Age, yr Smoking status relative to never smokers Exsmokers Current smokers Pack-years Regional effects relative to the West Anthracite Central Pennsylvania Northern Appalachia Southern Appalachia South Midwest Estimated cumulative dust exposure, gh/m'
R2 Residual root mean square error Residual df Definition of abbreviation: df ~ degrees of freedom. • Test that coefficients are different from zero.
t p < 0.0001.
ml
-1,702 100 -31 -36 208 -5.0
38.2t -31.4t -10.0t -1.6 -9.9t
t -242 -158 -225 -224 -204 -219 -0.69 0.47 0.55 7.126
-5.5t
model to FEV 1IFVC OJo was not as good, the R 2 value being 0.17. Moreover, the regional effects were not so pronounced as for FEV 1 and FVC, although strong relationships were seen with age, height, pack-years, and cumulative dust exposure (p < 0.0001). No suggestion of an interaction effect between smoking and dust exposure was seen for FVC (p = 0.48) for the FEV 1/FVCOJo ratio (p == 0.57). The basic model was also fit using FVC and FEV 1/FVCOJo to the two subsets of miners defined on the basis of absence of CWP and the BOM/NSCWP overlap. In the first case, relationships with dust exposure were still evident after the omission of all miners with X-ray appearances of CWP, the coefficients being almost unaltered in value. The same was true for the NSCWP subset, although as with FEV 1 the coefficients were slightly smaller in magnitude. Discussion This report represents the first attempt at using data from the NSCWP to correlate pulmonary function with cumulative dust exposure estimates derived from actual mine airborne dust measurements. The various models of exposure show consistent declines in FEVI, FVC, and FEV l/FVC with increasing dust exposure. The environmental data used to derive the cumulative dust exposures employed here have both positive and negative qualities. On the plus side, they are based on many hundreds, and often thousands, of observations. In addition, data were available for nearly all jobs worked by the miners in the study, and the sampling tended to be more intense where dust levels were higher. On the other hand, the dust samples were collected toward the end of the period to which they were applied in this analysis; lack of any published information on temporal changes in dust level for the period 1950 to 1970 makes it impossible to assess whether this back-extrapolation is completely valid. (It is felt that conditions remained fairly constant from about 1960 to 1970, but it is unclear whether dust levels were higher or lower before that time [unpublished communications].) One point favoring the validity of the exposure estimates is their correlation with prevalence of CWP (15). In derivation of the dust exposure estimates used here it was not completely clear which of the many variations in approach was the most valid. The results
ATTFIELD AND HODOUS
608 TABLE 3 REGRESSION COEFFICIENTS AND t STATISTICS FOR FVC AND FEV,/FVC% AGAINST AGE. HEIGHT. REGION. SMOKING. AND CUMULATIVE DUST EXPOSURE' FEV,/FVC%
FVC
Constant. ml Height. inches Age. yr Smoking status relative to never smokers Exsmokers Current smokers Pack-years Regional effects relative to the West Anthracite Central Pennsylvania Northern Appalachia Southern Appalachia South Midwest Estimated cumulative dust exposure. gh/m'
%
ml
Variable
-4.584 155 -26
R2 Residual root mean square error Residual df
28 -87 -2.3
51.1:1: -22.8:1:
106.8 -0.261 -0.253
-6.7:1: -17.1:1:
1.1 -3.6t -4.1:1:
-1.18 -3.17 -0.069
-3.6t -10.2:1: -9.7:1:
:j:
-451 -232 -366 -309 -282 -342 -0.49 0.44 0.64 7.126
t
1.73 0.31 0.87 -0.03 0.09 0.58 -0.008 0.18 8.2 7.126
• Test that coefficients are different from zero.
t p < 0.001. :I: p < 0.0001.
presented are based on the strategy felt to be most reliable. Other exposure estimates, developed using variations on the basic strategy (13), were correlated with ventilatory function in an attempt to assess the sensitivity of the results to variations in method. They gave rise to coefficients for dust exposure ranging between -0.51 to -0.62 ml/gh/m", Although these are a little smaller than the figure of -0.69 in table 1, they were still very unlikely to be due to chance (P < 0.0001). Regional effects were included in the regression models in order to allow for systematic differences between geographic areas ofthe country. Results from British miners have indicated that such factors exist and should be taken into account (6). It is not known why systematic effects occur, but they could have been due to many factors, including climate, life-style, ethnicity, season of year, and technical reasons. However, one problem with allowing for regional effects is that geographic region is confounded with geologic variations in coal type. Hence, allowance for region may remove some of the effect rightly due to coal dust exposure. To determine the possible extent of this effect, the basic model was run omitting regional effects. When this was done, the dust exposure coefficient on FEV 1 rose from - 0.69 to - 0.80 ml/gh/m", Dust concentrations for certain jobs at the coal mine face were apparently 6 mg/m" or greater on average before the 1969 Federal Coal Mine Safety and
Health Act (14), implying a yearly exposure of about 10 gh/m", These exposures, taken in conjunction with the various estimates for dust exposures on FEV 1 noted previously, suggest a decrement of 5 to 9 ml/yr, Under the current 2 mg/m" federal dust limit, the predicted dust effect should obviously be about one-third of that (i,e., 2 to 3 mllyr). In this respect, an exposure of 2 mg/m! over a 4O-yr working life at the coal face would be associated with roughly a l00-mlloss in FEV l • If it is thought that a 5- to 9-ml decrement of FEV 1 per year is clinically insignificant, it must be remembered that the average decrement for smokers was only 5 ml per pack-year. This, in itself, is also a minor loss in lung function. However, it is well known that smoking can cause severe effects in some smokers. Hence, this small average loss among smokers conceals some severe long-term effects in a minority. Could it then be that the average decrement of 5 to 9 ml associated with dust exposure also hides some severe dust exposure effects? Further study is continuing on this topic. The existence of such an effect is suggested in the findings of Hurley and Soutar (7), who detected a subgroup of miners with severe dust-related losses in FEV l . Pack-years was used in the regression analyses in this report because its use has been stated to be more appropriate than employment of categorical terms for smoking adjustment (17). However, since some prefer the latter approach, an anal-
ysis was undertaken replacing pack-years with dummy variables for the three smoking groups, and variables representing their interaction with age. The results gave rise to a dust exposure coefficient of -0.65 ml/gh/m" (p < 0.001), very similar to that obtained in the model using pack-years. Addition of an interaction term representing systematic differences in dust exposure between the smoking groups to this model did not suggest that the exposure effect varied over the smoking groups (p > 0.10). Because the interaction terms for smoking and dust exposure in the latter model and in that based on pack-years werenot significantly different from zero, synergism between smoking and dust exposure was not evident in these data. Indeed, if anything, there was a suggestion that smokers might suffer less of an effect of dust exposure than did their neversmoking colleagues. It would be unwise to conclude from this that smoking might have a protective effect against dust exposure, however, because the observed effect could wellhave been due to selection caused by the departure from the industry of miners affected by their exposure to both tobacco smoke and dust. In any study such as this, with several time-related variables, multicollinearity is a potential problem. Although collinearity does not lead to biased estimates of coefficients, their variability may be increased, with the result that estimates of the coefficients may be far from their true values in any particular analysis. However, the effects of multicollinearity can be offset by increasing the sample size, as variance is inversely proportional to numbers of observations. Because of the large sample size in this study, the problems associated with collinearity are somewhat mitigated. A study of collinearity in the data revealed that as the dust exposure coefficient declined toward zero, the age coefficient rose to smokingadjusted values of - 32 to - 37 ml/yr, values much greater than those commonly encountered ill prediction equations for FEV l (-23 to -29 mllyr) (18-22). These large age-related declines seem less plausible than the alternative view that a real dust exposure effect exists. Morgan (23) has argued that the effects of smoking and dust exposure are different, smoking leading to severedamage in a minority whereas dust exposure causes small losses in the majority. In an analysis relating to this topic, Attfield and Hodous (results presented at the 1989 American Thoracic Society conference) examined the distribution of FEV 1 values
PULMONARY FUNCTION OF U.S. COAL MINERS
in smokers and never smokers but failed nificance of their dust exposure coeffito find support for this hypothesis. Over- cient was less than for the models involvall, it appeared that dust and smoking ing FEV 1 and FVC. In summary, this study has found clear acted similarly on ventilatory function in causing a general shift of the FEV 1 dis- exposure-response relationships between various pulmonary function parameters tribution to lower values. The estimates of FEV 1 decline on dust and estimated cumulative dust exposure exposure given in this report are very simi- in a large national cohort of U.S. underlar to figures reported for British miners. ground coal miners. The results indicate Rogan and coworkers (5) detected a that miners working in dusty conditions reduction in FEV 1 with cumulative dust (6 mg/m") could experience average efexposure of - 0.6 ml/gh/m". Soutar and fects not unlike those seen for smokers. Hurley (6) obtained an estimate of the The results weregenerally consistent with dust exposure effect of -0.76 ml/gh/m" findings from a study of British underground coal miners. among a group of current and exminers. As in this study, they found that the effect Acknowledgment of dust was not greater in current smokers. Furthermore, they also showed that The writers thank the many who have assistthe relationship between dust exposure ed in the collection and processing of data, and FEV 1 was similar in miners who did those who have given other information or advice, and those who have reviewed the and did not have pneumoconiosis. Soutar and Hurley (6) found that not manuscript and supplied many useful comonly was FEV 1 related to cumulative dust ments and suggestions. exposure, but that a similar trend was also References found for FVC. This observation had 1. Jacobsen M, Rae S, Walton WH, Rogan JM. been reported earlier by Morgan and coThe relation between pneumoconiosis and dust exworkers for U.S. miners (11) using years posure in British coal mines. In: Walton WH, ed. of underground work. Because the cur- Inhaled particles. III. Old Woking, Surrey,UK: Unrent report is based on essentially the win Bros., 1971; 903-19. same set of data, it is not surprising that 2. McLintock JS, Rae S, Jacobsen M. The attack the same phenomenon appears in the rate of progressive massive fibrosis in British In: Walton WH, ed, Inhaled particles. present results. Morgan and coworkers, coalminers. III. Old Woking, Surrey, UK: Unwin Bros., 1971; however, did not use dust exposure esti- 933-52. mates, and hence the present results have 3. Jacobsen M, Burns J, Attfield MD. Smoking not been reported previously. The cur- and coal workers' simple pneumoconiosis. In: Walrent results confirm the trend of FVC ton WH, ed. Inhaled particles. IV. Oxford: Pergamon Press, 1977; 759-71. with dust exposures seen in the British 4. Rae S, Walker DD, Attfield MD. Chronic bronminers. chitis and dust exposure in British coal miners. In: Morgan and colleagues reported that Walton WH, ed. Inhaled particles. III. Old Wokyears underground had no effect on ing, Surrey, UK: Unwin Bros., 1971; 883-96. 5. Rogan JM, Attfield MD, Jacobsen M, Rae S, FEV 1/FVCOJo. The findings of this study Walker DD, Walton WHoRole of dust in the workdo not support that statement, as a rela- ing environment in the development of chronic tionship with FEV l/FVCOJo and estimat- bronchitis in Britishcoal miners.Br J Ind Med 1973; ed dust exposure was detected (- 0.0080J01 30:217-26. gh/m", p < 0.0001), although the size of 6. Soutar CA, Hurley JF. Relation between dust exposureand lung function in minersand ex-miners. the effect was clearly not large. Soutar Br J Ind Med 1986; 43:307-20. and Hurley (6) also found a small coeffi- 7. Hurley JF, Soutar CA. Can exposure to cient for the ratio (-0.OO50J0/gh/m 3 ) ; in coalmine dust cause a severe impairment of lung contrast to this study, the statistical sig- function. Br J Ind Med 1986; 43:150-7.
609 8. LoveRG, Miller BG. Longitudinal study of lung function in coal miners. Thorax 1982; 37:193-7. 9. Marine WM, Gurr D, Jacobsen M. Clinically important respiratory effects of dust exposure and smoking in British coal miners. Am Rev Respir Dis 1988; 137:106-12. 10. Kibelstis JS, Morgan EJ, Reger R, Lapp NL, Seaton A, Morgan WKC. Prevalence of bronchitis and airways obstruction in American bituminous coal miners. Am Rev Respir Dis 1973; 108:886-93. 11. Morgan WKC, Handelsman L, Kibelstis J, Lapp NL, Reger R. Ventilatory capacity and lung volumes of US coal miners. Arch Environ Health 1974; 28:182-9. 12. Hankinson JL, Reger RB, Fairman RP, Lapp NL, Morgan WKC. Factors influencing expiratory flow rates in coal miners. In: Walton WH, ed. Inhaled particles. IV. Oxford: Pergamon Press, . 1977; 735-55. 13. Attfield MD, Morring K. The derivation of dust exposures for U.S. coal miners working before 1970. Am Ind Hyg Assoc J (In Press). 14. Jacobson M. Respirable dust in bituminous coal mines in the U.S. In: Walton WH, ed. Inhaled particles. III. Old Woking,Surrey, UK: UnwinBros., 1971; 745-55. 15. Attfield MD, Morring K. Some investigations into the relationship between coalworkers' pneumoconiosis and dust exposure in U.S.coal miners. Am Ind Hyg Assoc J (In Press). 16. SAS Institute Inc. SAS$ User's Guide: Statistics, version 5 edition. Cary, NC: SASInstitute Inc., 1985; 433-506. 17. Morgan WKC. Letter to the editor. Thorax 1983; 38:878. 18. Crapo RO, Morris AH, Gardner RM. Reference spirometric values using techniques and equipment that meet ATS recommendations. Am Rev Respir Dis 1981; 123:659-64. 19. Knudsen RJ, Slatin RC, Lebowitz MD, Burrows B.The maximal expiratory flow-volume curve. Normal standards, variability, and effects of age. Am Rev Respir Dis 1976; 115:587-600. 20. Knudsen RL, LebowitzMD, Holberg CJ, Burrows B. Changes in the normal maximal expiratory flow-volume curve with growth and aging. Am Rev Respir Dis 1983; 127:725-34. 21. Miller A, Thornton JC, Warshaw R, Bernstein J, Selikoff IJ, Teirstein AS. Mean and instantaneous expiratory flows, FVC and FEV,: prediction equations from a probability sample of Michigan, a large industrial state. BullEur Physiopathol Respir 1986; 22:589-97. 22. Morris JF, Koski A, Johnson LC. Spirometric standards for healthy nonsmoking adults. Am Rev Respir Dis 1971; 103:57-67. 23. Morgan WKC. On dust, disability, and death (editorial). Am Rev Respir Dis 1986; 134:639-41.
