American Journal of Industrial Medicine 9: 117-122 (1986)

COMMENTARY

Pulmonary Reference Standards in Occupational Medicine

Albert Miller, MD

Key words: pulmonary, reference standards, occupational medicine

INTRODUCTION

The term “pulmonary reference standards” as used in this paper refers to two different quantitative data bases-regression equations to predict normal values for pulmonary function tests (generally using the independent variables of race, sex, age, and height) and prevalence rates of various pulmonary symptoms, signs, and func- tional impairments. The material in this editorial is developed in greater detail in another publication [Miller, 19851.

PREDICTION EQUATIONS FOR PULMONARY FUNCTION TESTS

Pulmonary function tests are widely used in clinical and occupational medicine to detect evidence of disease, to quantitate its import, and to elucidate pathophysio- logic mechanisms, While there has been progress in standardizing the instrumenta- tion, methodology, and calculation of the tests (“the hardware”) [Ferris, 19781, the resulting values are meaningful only by being compared with “predicted values” for normal subjects. There is little standardization in this “software. ”

Spirometry and Flows

The equations in widest use in North America for spirometric tests (the vital capacity, VC or forced vital capacity, FVC and the forced expiratory volume in one second, FEVI), which are by far the most commonly employed measurements, are listed below:

Pulmonary Laboratory, Mount Sinai Medical Center, New York. Address reprint requests to Albert Miller, MD, Director, Pulmonary Laboratory, Annenberg 24-30, Mount Sinai Medical Center, One Gustave L. Levy Place, New York, NY 10029. Accepted for publication April 12, 1985.

0 1986 Alan R. Liss, Inc.

118 Miller

1. Morris et a1 11971, 1973, 19751. These come from a narrow population base (nonsmoking adherents of the Mormon and Seventh Day Adventist Churches living in a rural valley) that may not be representative of urban populations of diverse national origin. Testing did not conform to present day standards.

2. Crapo et a1 [1981b]. Nonsmoking subjects are from a similar narrowly defined population residing at an altitude of 5,000 feet.

3. Knudson et a1 119761. The original equations, adopted by the Federal Black Lung and Cotton Dust standards, were subsequently substantially revised by the authors [1983]. Several problems that remain are as follows: (a) These normal nonsmokers may well have been supernormal. (As the authors put it, “Data from only the healthiest segment of the population were used.”) (b) There were few male subjects in the age group of greatest importance in occupational medicine: only 86 men over the 60-year span from age 25 to 85. (c) Unlike most other investigations of pulmonary function, there is considerable skew in the data.

Two sets of prediction equations are widely used by European specialists in occupational medicine:

4. The European Coal and Steel Community survey [1973]. Values were influenced by the “healthy worker” bias and in the opposite direction by the inclusion of smokers. The studies were performed in the 1960s and do not meet current specifications.

5 . Summary equations of the Worlung Party on Standardization of Lung Func- tion Tests of the European Community for Coal and Steel [Quanjer, 19831. The publication provides an exhaustive compilation of the populations studied by various investigators and a useful listing of their regression equations. The summary equations are means of the listed regression equations after standardizing the age and height variables. They are not suitable for use “in all laboratories,” as the Working Party intended, because they failed to weight the series by number of subjects and to evaluate them for consistency, adequacy, and reproducibility of testing and for con- sistency of smoking status [Thornton and Miller, 19841.

6. Miller (submitted). The prediction equations that are most representative of the white population of North America have been developed by the Pulmonary Laboratory at the Mount Sinai School of Medicine. The subjects were a stratified cross-sample of the entire state of Michigan, a large state (9,000,000 inhabitants) comprising a metropolitan area, numerous smaller cities and industrial towns, exten- sive farmlands, and sparsely settled sylvan communities. Additional valuable contri- butions from this investigation are as follows:

(a) Prediction equations for instantaneous flows at low lung volumes (forced expiratory flows when 50% and 75% of the FVC have been exhaled, or FEFso% and FEF75%, respectively). These flows are most sensitive to early obstruction in the small airways and are easily measured during the basic FVC maneuver. Previous prediction equations for flows have suffered from inadequate sampling or testing and have been grossly inconsistent one from the other. (b) Quantitation of the effect of smokmg in normal subjects. The most informative smoking variable was noted to be duration. Analysis is ongoing to quantitate the effects on smokers who have developed such consequences of their habit as cough and sputum and are therefore no longer “normal. ”

Diffusing Capacity (Transfer Factor) Spirometry and flows reflect mechanical properties of the lung. The only

sensitive noninvasive test of the gas exchanging properties of the lung is the diffusing

Pulmonary Reference Standards 119

capacity (DL, or transfer factor, TL, a term favored by British authors) for carbon monoxide, usually performed by the single breath method-DLCOsB. The test is especially useful for interstitial lung diseases (ILD), important occupational examples of which are asbestosis, berylliosis, 2nd hypersensitivity pneumonitis. The Miller equations [Miller et al, 19831 are preferred because of their demographic advantages and ability to quantitate the effects of smoking as cited above for spirometric tests and because they are compatible with the widely used earlier equations of Gaensler and Smith [ 19731.

Adoption of uniform prediction equations for each test will eliminate the most important source of inconsistency in evaluating pulmonary function results now that the tests themselves have been largely standardized. A subject's value may be reported as normal using one published equation and highly abnormal using another. This has been recognized for spirometric tests [Glindmeyer, 19811 and is illustated by Figure 1 for D L C O ~ ~ . An element contributing toward consistency is that the various prediction equations come from the same population, so that equations for one measurement are compatible with those for another.

Accounting for the effect of smolung is valuable. Such coefficients allow for the effect of smoking on pulmonary function to be separated from that of a specific illness (eg, asbestosis) in an individual subject or from that of a specific exposure in a population under study.

68 inch, 170 pound mole i l , I I I 1 I

\

'. 4 Sm Al l smoking histories

_-_ . . . . .

I I I I I T 20 30 40 50 60 70

AGE

I 1 '

Fig. 1. Regressions against age for males (height, 68 inches; weight, 170 pounds) for DLCOsB in mll mmHg/min. To demonstrate the effects of smoking on those regressions that include this variable, a cigarette consumption of 1.5 packs a day beginning at 20 years of age is assumed. NS, nonsmokers; Sm, current smokers; all, all smoking categories; undef, smoking history undefined. 1, Miller et a1 (NS) [1983]; 2, Miller (Sm); 3 , Van Ganse et al 119721 (all); 4, Van Ganse (Sm); 5 , Van Ganse (NS); 6, Gaensler and Smith [1973] (all); 7, Bates et al 119711 (undef); 8, Crapo and Morris [1981a] (NS); 9, Burrows et a1 [1961] (undet); 10, Fridriksson et al [1981] (NS); 11, Marcq and Minette [1976] (NS); 12, Frans et a1 1197.51 (NS); 13, Frans (Sm). Reproduced from Miller et al [1983] with permission.

120 Miller

DEFINING ABNORMAL VALUES; THE LOWER LIMIT OF NORMAL

An additional element contributing to consistency in reporting and interpreting pulmonary function tests resides in the very definitions of normal and abnormal. Although time-honored, defining a normal test by its percentage of the predicted value lacks statistical validity. (Such definitions are inconsistent as well, since differ- ent percentages have been used. Even when the most traditional “80% of predicted” is used, inconsistency results from variously defining the 80% boundary as normal or abnormal.) Using 80% (or 75%) of predicted will identify as abnormal many subjects whose values are statistically normal, especially when these values are smaller (in black, female, older, and shorter subjects), while the values of certain taller or younger subjects will be considered normal even when they are below confidence limits. This is illustrated by Figure 2 for one of the most reproducible and precise measurements, the FVC. For tests with greater variability such as flows, values below 75 % or 80% of predicted will be misleadingly classified as abnormal at all ages and heights, although more so at greater age (or lesser height).

Most investigators have adopted the one-sided confidence lower limit to define abnormal values for FVC, FEVI, and DLCO [Miller and Thornton, 19801. Since results for these tests are usually distributed symmetrically about the regression line for age and since the distribution of residuals (predicted value - observed value) is Gaussian, this is equivalent to ranking at the fifth percentile: the value above which 95 % of observations fall separates normal from abnormal.

The one-sided 95% confidence lower limit is easily obtained by subtracting 1.645 x the standard deviation (SD) of the regression (similar to the standard error of the estimate), from the predicted value. Since 1.645 X SD is a constant, the same

507 MORRIS MALES

20 30 40 50 60 70 80 AGE ( Y E A R S )

Fig. 2. The relationship between the regression line for predicted FVC at a height of 70 inches, the line for 80% of predicted, and the line for lower 95% confidence. Note that 80% of predicted is increasingly above the lower 95 % confidence limit from age 30 on. For the decade 20-30 years of age on the other hand (an age range of many active industrial workers), the 95% confidence limit is above the line for 80% of predicted. Reproduced from Miller et a1 [1980] with permission.

Pulmonary Reference Standards 121

value is substracted from any predicted value to arrive at the lower limit, which may then be 82 % of predicted for FVC at age 20 and 72 % at age 70, as seen in F i p r e 2.

COMPARING GROUPS

When large numbers of subjects are compared (eg, industrially exposed popu- lations versus controls), small differences in their distribution of values (means + SDs) may be statistically significant even when the tests themselves have great variability, such as flows at low lung volume. Statistically signi$cunt does not mean clinimlly important.

PREVALENCE RATES IN REFERENCE POPULATIONS

The populations may be workers in a specific industry or company or small (eg, Berlin, NH) or larger (eg, Tucson, AZ) communities. Again, the Mount Sinai survey of the state of Michigan is cited because the population sampled was large and representative of North America [Miller et al, 19821. Prevalence rates of interest are as follows: (a) Respiratory symptoms-dyspnea, cough, sputum, wheezing. Many surveys report these, although definitions of the symptoms vary. Information on the following is much scantier: (b) Physical signs-rales, wheezes, clubbing, diminished breath sounds, increased antero-posterior (AP) diameter of the chest. (c) Radiographic signs-emphysema (flattened diaphragm, diminished vascularity, increased AP di- ameter and retrosternal air), interstitial infiltrates, pleural thickening, etc. (d) Func- tional impairments-diminished FVC, FEVl, flows, and DLCOsB using both conventional and statistical definitions of abnormality. Interesting results are obtained when the conventional definitions of abnormality are applied even to normal non- smoking subjects, eg, 17.8 % of such subjects had an FEF25-75% < 75 % of predicted, and 19.7% had an FEVI/FVC < 0.70 [Miller et al, 19801. In the general population of Michigan, 15 % of male smokers had an abnormal FVC and 43 % had an abnormal FEF25-75%. The latter test was abnormal in 38% of ex-smokers [Miller and Thornton, 19801. Thus, an investigator who reports a “high prevalence of small airway obstruc- tion” in an industrial population, most of whom have a smoking history, would not be justified in attributing this abnormality to occupational exposure unless the rate were significantly greater than this range!

REFERENCES

Bates DV, Macklem PT, Christie RV (1971): “Respiratory Function in Disease: An Introduction to the Integrated Study of the Lung.” Philadelphia: W.B. Saunders Co, pp 93-94.

Burrows BJ, Kasik JE, Niden AH, Barclay WR (1961): Clinical usefulness of the single-breath pulmo- nary diffusing capacity test. Am Rev Rcspir Dis 84:798-806.

Crapo RO, Morris AH (l98la): Standardized single breath normal values for carbon monoxide diffusing capacity. Am Rev Respir Dis 123: 185-189.

Crapo RO, Morris AH, Gardner RM (1981b): Reference spirometric values using techniques and equipment that meet ATS recommendations. Am Rev Respir Dis 123:659-664.

European Community for Steel and Coal (1973): Industrial Health and Medicine Series, Second Edition. Aide-Mtrnoire of Spirogrdphic Practice for Examining Ventilatory Function, Luxembourg.

Ferris BG (Principal Investigator) (1978): Epidemiology standardization project. Am Rev Respir Dis 118, No. 6, Part 2.

122 Miller

Frans A, Stanescu DC, Veriter C, Clerbaux T, Brasseur L (1975): Smoking and pulmonary diffusing capacity. Scand J Respir Dis 56:165-183.

Fridriksson HV, Malmberg P, Hedenstrom H, Hillerdal G (1981): Reference values for respiratory function tests in males. Prediction formulas with tobacco smoking parameters. Clin Physiol

Gaensler EA, Smith AA (1973): Attachment for automated single breath diffusing capacity measurement.

Glindmeyer HW 111 (1981): Predictable confusion. J Occup Med 23:845-849. Knudson RJ, Leibowitz MD, Holberg CJ, Burrows B (1983): Changes in the normal maximal expiratory

flow-volume curve with growth and aging. Am Rev Respir Dis 127:725-734. Knudson RJ, Slatin RC, Lebowitz MD, Burrows B (1976): The maximal expiratory flow-volume curve.

Normal standards, variability and effects of age. Am Rev Respir Dis 113:587-600. Marcq M, Minette A (1976): Lung function changes in smokers with normal conventional spirometry.

Am Rev Respir Dis 114:723-738. Miller A, Thornton JC, Warshaw R, Bernstein J, Teirstein AS, Selikoff U (Submitted): Mean and

instantaneous expiratory flows, FVC and FEV,: Prediction equations for nonsmokers and smok- ers from a random sample of Michigan, a large industrial state.

Miller A (1985) “Pulmonary Function Tests in Clinical and Occupational Lung Disease.” Orlando: Grune and Stratton.

Miller A, Thornton JC (1980): The interpretation of spirometric measurements in epidemiologic surveys. Environ Res 23:444-468.

Miller A, Thornton JC, Smith H Jr, Morris JF (1980) Spirometric “abnormality” in a normal male reference population: Further analysis of the 1971 Oregon Survey. Am J Indust Med 1:55-68.

Miller A, Thornton JC, Teirstein AS, Anderson HA (1982): Prevalence of clinical respiratory and spirometric abnormalities in a representative sample of the general population of the state of Michigan. Am Rev Respir Dis 125 No. 4 (Part 2): 163.

Miller A, Thornton JC, Warshaw R, Anderson H, Teirstein AS, Selikoff IJ (1983): Single breath diffusing capacity in a representative sample of the population of Michigan, a large industrial state: Predicted values, lower limits of normal, and frequencies of abnormality by smoking history. Am Rev Respir Dis 127:270-277.

Morris JF, Koski A, Breese ID (1975): Normal values and evaluation of forced expiratory flow. Am Rev Respir Dis 111:755-762.

Morris JF, Temple WP, Koski A (1973): Normal values for the ratio of one-second forced expiratory volume to forced vital capacity. Am Rev Respir Dis 108:1000-1003.

Morris JF, Koski A, Johnson LC (1971): Spirometric standards for healthy nonsmoking adults. Am Rev Respir Dis 103:57-67.

Quanjer PH (1983): Standardized lung function testing. Report of Working Party on “Standardization of Lung Function Tests” of the European Community for Coal and Steel. Bull Physiopath Resp 19

Thornton JC, Miller A (1984): Standardized lung function testing (Letter to the editor). Bull Physiopath

Van Ganse WF, Ferris BG Jr, Cotes JE (1972) Cigarette smoking and pulmonary diffusing capacity

1:349-364.

Chest 63:136-145.

(SUPPI 5).

R C S ~ 20:571-572.

(Transfer factor). Am Rev Respir Dis 105:30-41.