Reference spirometric values in healthy Nicaraguan male workers

AMERICAN JOURNAL OF INDUSTRIAL MEDICINE 2941-48 ( I 996)

Reference Spirometric Values in Healthy Nicaraguan Male Workers

Carlos Quintero, MD, Lennart Bodin, PhD, and Kjell Andersson, MD

The main objective was to derive reference equations for the FVC, FEV,, and FEV,/FVC ratio for healthy Nicaraguan male workers without current occupational exposure to agents hazardous to the lungs. Age, height, and weight were included as independent variables in the analysis, but only age and height showed signtficant effects on the indices studied. A nonlinear relationship with age was observed,for FVC und FEV,, with a sh$t in the slope at the age of 32 years. Linear, quadratic, and multiphase models were tested in order to assess the best reference equation. The multi-phase model most closely jitted the values measured. The FEV,/FVC ratio showed a significant linear negative correlation with age. A comparison between the equations derived from this material and those reported in other studies revealed substantial differences. Racial, genetic, nutritional, work and sociocultural factors could account for the differences. 0 I996 Wdey-Lts\. Inr

KEY WORDS: spirometry, reference values, Nicaraguan workers

INTRODUCTION

Spirometry is widely used to evaluate pulmonary function for clinical and epidemiological purposes. It is a rela- tively simple, fast, and noninvasive test, and various porta- ble spirometers are available for field investigations. Spirometry is particularly advantageous for evaluating a working population exposed to noxious agents for the lungs and/or airways. However, for meaningful evaluations, adequate spirometric reference values are necessary.

Since 1846, when Hutchinson presented the first spirometric reference values, several studies have been performed with varying results [Hutchinson, 1846; Kory et al., 1961; Berglund et al., 1963; Ferris et al., 1965; Crapo et al., 1981; Knudson et al., 1983; Gustavsson et al., 1984; Dock- ery et al.. 1985; Hedenstrom et al., 1985, 1986; Petersen et al., 1985; Morris et al., 1988; Coultas et al., 1988; Castro

Department of Physiology, National Autonomous University of Nicaragua

Department of Occupational and Environmental Medicine, Orebro Medical Cen-

Address reprint requests to Dr. Carlos Quintero, Department of Physiology,

Accepted March 3, 1995.

(UNAN), Leon, Nicaragua (C.Q.).

ter Hospital, Orebro, Sweden (L.B., K.A.).

Faculty of Medicine, UNAN-Leon, Le6n. Nicaragua.

Pereira et al., 19921. Possible explanations for these dis- crepancies include differences not only in equipment and methods but also in the populations tested [Oscherwitz et al., 1972; Rossiter et al., 1974; Glindmeyer, 1981; Neeraj et al., 19901. Some studies of this type have been carried out on working populations [Rastogi et al., 1983; Petersen et al., 19851. However, few studies have been done in Latin Amer- ican countries, although they have large populations working while exposed to pollutants toxic to the respiratory system.

A need for adequate spirometric reference values was observed when Nicaraguan workers were evaluated spiro- metrically, using reference values reported in surveys carried out in the United States and Europe. Workers who had pulmonary illness and were expected to have abnormal spirometric findings had values within the normal range. This could be due to inadequate reference values which do not represent the distribution of the spirometric indices in the Nicaraguan working population. Thus, specific reference values for this population would be advantageous for both clinical and epidemiological purposes.

The main objective of this study was to establish reference values for the basic spirometric indices: forced vital capacity (FVC), forced expiratory volume in 1 sec (FEV,), and the FEV,/FVC ratio in percent (FEV,%) to be used in a spirometric evaluation of Nicaraguan male workers. This

0 1996 Wiley-Liss, Inc.

42 Quintero et al.

is the first attempt to establish reference values in a working Central American population.

A second objective was to compare the resulting spirometric reference equations with other equations [Kory et al., 1961; Berglund et al., 1963; Ferris et al.. 1965; Knud- son et al., 1983; Morris et al., 1988; Coultas et al., 19881, most of them previously used as standards for spirometric evaluations in Nicaragua and other Latin American countries. We refer to these as "external reference equations. "

MATERIALS AND METHODS

Population

A population of 575 Nicaraguan mestizo male workers, aged 16-64 years, from five cross-sectional pulmonary epidemiological surveys was available for this study. They represented industrial, agricultural and office workers without current exposure to recognized agents harmful to the lungs. All surveys were carried out in two regions at sea level in Nicaragua during the period 1987-1991.

There were 36 I subjects excluded (criteria mentioned below); the data from a final population of 214 healthy, nonsmoking subjects. aged 16-58 years (mean 32, SD 9) were studied. The distribution of the population, according to their occupation, was as follows: 106 (50%) industrial workers, 53 (25%) farm workers, and 55 (26%) office workers.

Methods

The data were obtained from a questionnaire, spirometric tests. physical examinations. and chest radiographs.

Questionnaire

The questionnaire, presented to the subjects by a trained interviewer, included questions about chronic respiratory symptoms and diseases, medical history. smoking habits and history of exposure to agents harmful to the respiratory system.

In all five surveys, the questions about respiratory symptoms were chosen from the British Medical Research Council Questionnaire [MRC, 19761 and then translated and modified so that they could be easily understood. Two surveys differed slightly in questions concerning educational level and smoking habits.

Smoking was quantified in package-years (pack-years), that is. (cigarettes per day/20)x(smoking years). To be classified as a current smoker or an ex-smoker, the value of pack-years had to be 0.05 or more. The ex-smokers were those who, in addition, had stopped smoking more than six

months before the interview. Nonsmokers were those who had never smoked or who smoked occasionally with an estimated value of less than 0.05 pack-years.

Spivometry

Spirometric records for FVC, FEV,. and FEV,% were obtained after the interview. All spirometric tests in the surveys were done between 6:30 and 10:30 AM before work- shift by the same research team (a nurse, a general practi- tioner, and a physiologist) experienced in performing such tests.

Two kinds of spirometers were used i n the surveys. Thirty-three percent of the tests were collected by a Vitalo- graph 20.610 (UK) and the rest with a Collins water-sealed Survey (WE Collins, Braintree, MA). Both types of equipment met technical requirements for epidemiologic studies [Cardner et al., 1980; American Thoracic Society, 1987; Nelson et al., 19901. The spirometers were permanently placed, and their accuracy controlled daily before and after the tests, using a 3-L calibration syringe. Leaks were checked during a 1-min observation period. The recorder time scale was controlled every second week. All results were within the ATS requirements [American Thoracic So- ciety, 19871.

The ATS technical recommendations for standardization o f spirometry were followed with the subjects in sitting posture and using a noseclip. Forced expiratory maneuvers were performed (3 -7 times) until three acceptable tracings were obtained varying no more than 5% or 100 ml (which- ever was higher) for both FVC and FEV,. The recorded time was 10 sec with the Collins spirometer (provided a plateau of at least 2 sec was obtained), but only six seconds with the Vitalograph, because of its different design. By manual reading, the largest values of FVC and FEV, were obtained from the three acceptable tracings, regardless of whether they came from the same curve. The starting point for FEV, was determined by the back extrapolation method. Ambient temperature (range 28 -34°C) was recorded and the volumes corrected to BTPS conditions.

The two spirometers used for the tests were compared using 44 medical students (25 males and 19 females, aged 18-25 years) who were selected at random from the official list of the regional medical school. Each student was tested with both spirometers in random sequence. All tests were performed using the same technical procedure as in the surveys and by one person from the research team. The spirometric indices VC, FVC, and FEV, were recorded. The validation procedure showed a good agreement between both instruments for the indices studied. The mean differences ( in liters) were: -0.022 (95% C1:-0.06. 0.02), 0.018 (95% C1:-0.02, 0.06), and -0.003 (95% CI:-0.04, 0.03) for VC, FVC, and FEV,, respectively.

Reference Spirometric Values 43

Physical examination and chest radiographs

Height and weight were measured in centimeters and kilograms, respectively, in a standing posture with light clothes and without shoes. None of the individuals was obese, defined as overweight more than 25% of the ideal body weight (Bleier et al., 19831. A medical interview was followed by a general physical examination with emphasis on the thorax. Chest radiographs were available for only 55% of the subjects because some surveys were carried out in areas in which such equipment was not available. All radiographs were considered normal after being evaluated separately by two radiologists. All individuals were free of any acute respiratory disease when tested, and without any respiratory disorders within the three months prior to the examination.

Exclusion criteria

Twenty subjects with previous exposure to known haz- ards to the respiratory system (fumes or dusts) were excluded. provided the exposure(s) had a duration of more than 2 years, or had a duration of less than 2 years, and ceased less than 5 years before the interview. Fifteen workers were excluded because they had a history of cardiopul- monary diseases, chronic respiratory symptoms according to the MRC questionnaire (cough, phlegm, wheeze, or dys- pnea at least 3 months during the past 2 years) [MRC, 19761, or chest abnormality detected on clinical examination.

All records were manually re-evaluated for the technical requirements according to the ATS criteria by the physiologist. Three subjects were excluded because a two second plateau was not obtained within a six-second recording period (with the Vitalograph). All three had a FEV, greater than 70%, but during the remaining 5 sec a clear 2-sec plateau was not reached. In addition, 19 subjects were excluded because the extrapolated volume (when determining time zero for FEV,) was higher than 5% of the FVC (maximum value 12%). or higher than 100 ml [American Tho- racic Society, 19871. Finally, both smokers and ex-smokers (n = 280 and 36, respectively) were excluded from the analysis of reference values. Since some of the workers fulfilled more than one exclusion criteria, the exclusions totaled 36 I subjects.

Data analysis

Different forms of multiple regression analysis, both linear and nonlinear models, were used to test reference equations for FVC, FEV ,, and FEV ,%. In the analyses, the spirometric indices were the effect variables, age, height, and weight were included as explanatory variables. All

spirometric values in the data analyses were in BTPS. The reference values obtained from the equations of Berglund et al. [ 19631 were corrected to BTPS by multiplying them by 1.09. The Quest [Gustavsson, 19901, SPSS [SPSS, 19921, and BMDP [BMDP, 19921 computer programs were used in the analysis.

RESULTS

Characteristics of the study population, stratified by age, are shown in Table I. Stratification by age was done in 10-year intervals, with the exception of the last age group. The statistical modeling started with a linear multiple regression model with all explanatory variables included. Us- ing an evaluation of the estimated parameters together with residual diagnostics, we examined the set of explanatory variables retained in the model for alternative functional specification. In particular, different specifications of the age variable were tested, and both logarithmic and power transformations were used. Also, the functional specification used by Cole [Cole, 19751 was tested. The first step of the analysis showed that weight, including alternative for- mulations of weight, did not contribute significantly in those models in which height was included in the model; weight was therefore excluded in the subsequent analysis.

The statistical graphing of the spirometrk indices showed a positive correlation with height, and a nonlinear relationship with age for both FVC and FEV,, which re- mained after the introduction of height in the model. In particular, the values for both FVC and FEV, indicated a shift in the slope (breakpoint) of the regression on age, that appeared somewhere in the 20- to 40-year age span. For FVC, the slope was positive up to the breakpoint; after that, it was negative, indicating that a maximum value for FVC appears in this age span. In the case of FEV,, the slope was slightly negative for younger ages; after the breakpoint, it showed an increased negative value. For FEV,%, the relationship with age was negative and approximately linear over the whole age interval, 16-58 years. Therefore, a strictly linear equation model with age and height was considered for this spirometric function.

For FVC and FEV,, three models were analyzed, which considered the observed nonlinear relationship with age. The simplest model ignored the breakpoint, since it was a linear multiple regression equation for age and height:

y = a + b x age + c x height. ( 1 )

The second model included a quadratic term for age, thus allowing an estimate of the breakpoint as the maximum of the curve:

y = a + b, x age + b, x age' + c x height. (2)

The third niodel was obtained by reformulating the re-

44 Quintero et al.

TABLE I . Characteristics of Healthy Male Nonsmoking Nicaraguan Workers Stratified by Age

16-24 yr 25-34 yr 35-44 yr 45-58 yr (n = 43) (n = 102) (n = 44) (n = 25) All (n = 214)

Age ( Y ~ Y 21 5 2 29 f 3 38f3 51 + 4 32 f 9

Height (cm)" 165 +_ 7 166f6 166+5 163 f 6 165+6 Range 153-1 80 146-1 85 155-1 79 148-1 72 146-1 85

Weight (kg)a.b 60 + a 65 +_ 9 69*11 69 * 9 65 k 10 Range 49-85 45-92 46-98 54-85 45-98

FVC (L)a 4.28 f 0.54 4.41 _+ 0.54 4.25 _+ 0.46 3.95 _+ 0.53 4.30 lr 0.54 5thc 3.42 3.53 3.41 2.97 3.45

FEV, (L)a 3.81 k 0.50 3.75 ? 0.47 3.50 * 0.36 3.14 + 0.44 3.64 + 0.49 5thc 2.95 2.90 2.83 2.38 2.77

FEVl/FVC 89.14 _+ 4.87 85.10 + 5.66 82.44 _+ 6.36 79.53 ?r 5.46 84.71 k 6.30 5thc 80.93 75.20 71.51 67.79 74.77

aMean f SD. 'The number of obselvations on weight are 45, 78. 33, 21, and 168, respectively. 'Percentiles.

gression equation into a multi-phase regression model [Se- beret al., 19891:

for the equations, as measured by R', was obtained with equation (3) (0.29 and 0.35, respectively). Additionally, for each equation model, but also for the external reference equations, the residual sum of squares (SS) was calculated in order to evaluate the dispersion of the predicted values

y = a, + b , x age + (age - c,) x do x sign(age - c,) + e,, x height. (3)

around the true (observed) values. For the three equations developed in this study, the largest differences between the mean of the predicted values and the mean of the true val- lies, and also the largest SS, were observed for the linear

In these three models, y represents the effect variable (FVC or FEV,); in equation (3), sine stands for the sign function. The sine function i s defined as

Sine (age - c,) = - I if and

(age - c,) < 0 Sine (age - CJ = 1

if (age - cu) > 0 With the multiphase model, the breakpoint for the

spirometric function is attained at the age given by the pa- rameter c,: therefore, the age associated with the breakpoint is estimated together with the other parameters of the modcl. The procedure was maximum likelihood estimation adopted for nonlinear least-squares regression. The model was reformulated into two linear equations, the first describ- ing the age span up to and including the breakpoint c(,, the other equation starting from breakpoint co.

These two equations are, in fact. two linear regression functions, with a shift at the breakpoint c,. Using the same coefficient for height, they can be written as follows:

Age Ic,: y = a, + c, x do + (b, - d,) x age + e,, x height Age 2c,: y = a(, - c,, x d,, + (bo + d,) x age + e, x height

The breakpoints estimated with this model were at 32

In the cases of FVC and FEV,, the best goodness-of-fit years for both FVC and FEV,.

model (equation I ) , in particular in the youngest age-group. The intercepts, coefficients, R2, and standard error of

estimate (SEE) for equation (31, and the linear equation for FEV,%. are shown in Table 11. Table 111 shows the intercepts and the coefficients of the equations for FVC and FEV, derived from this material and the external equations. The parameters of the Knudson equations, in particular, the intercepts and height coefficients for the older age group, are those that deviate most from all the other equations.

The fifth percentile of the distribution of the observed spirometric value divided by the predicted value is shown in Table IV, stratified by age. The lower limit of normality is estimated by this percentile. The corresponding values for the Knudson and Coultas equations are also shown in this table. They are given for different age intervals, that is, those age intervals reported in the original references. Com- parisons with values obtained from the present study are shown.

As remarked in the Introduction. the use of external reference equations may increase the risk of misclassifica- tion when applied to male Nicaraguan workers. In Table V. the fifth percentile limit has been applied on the study population. In the first case, the reference values were calcu-


TABLE II. Regression Equations for Spirometric Values of Healthy Nonsmoking Nicaraguan Males Intercepts

Intercept Age (vr) Height (cm) R 2 SEE n

FVC: <32 yr -2.912 0.01077 0.0422 0.29 0.46 121 232 - 1.895 -0.02101 0.0422 0.29 0.46 93

FEV, : <32 yr - 1.386 -0.0091 9 0.0325 0.35 0.40 121 232 -0.799 -0.02746 0.0325 0.35 0.40 93

FEV,%: All 110.236 -0.31221 -0.0944 0.21 5.60 214

TABLE 111. Intercepts and Regression Coefficients in Different Reference Equations for FVC and FEV,

Intercept Age (ml/vr) Height (ml/cm)

Equation model used FVC FEV, FVC FEV, FVC FEVj

Kory et al. [1961] Berglund et al. (1963Ia Ferris et al. [1965] Morris et al. [1988] Knudson et al. [1983Ib Knudson et al. [1983jC Coultas et al. [1988]' Present studyb Present study'

-3.600 -2.810 -3.550 -3.445 -6.887 -8.782 -2.880 -2.912 - 1.895

- 1.590 - 1.000 - 1.650 - 1.343 -6.118 -6.515 -1.621 - 1.386 -0.799

- 22 - 20 - 25 - 27 t74 - 30 -28 ti 1 -21

-28 -33 -27 -32 t64 - 29 - 29 - 09 - 27

52 48 51 54 59 84 50 42 42

37 34 36 37 52 67 38 33 33

'After correction for BTPS bYounger age group 'Older age group.

lated from the multi-phase model of this study; in the second case, by the equations of Knudson; and in the third case, by the equations of Coultas. The fifth percentile limits in the distribution of percentage predicted values were those derived in the studies in question. Age stratification was also adapted to the stratification principles used in the referenced studies. When the Nicaraguan equations are used, the percentage of subjects classified below the limit is close to 5.0, the theoretical value (due to the limited number of subjects, the theoretical value will not be exactly reproduced). For the Knudson equations, the values for both FVC and FEV, are lower than expected. The Coultas equation has an excellent value for FVC, but for FEV, there is an underestimation. The risk for a substantial increase in the rate of false-negative classifications is evident.

DISCUSSION

The study population was obtained from the nonex- posed groups in five epidemiological surveys in Nicaragua. I t represents a sample of the nonsmoking working population in three occupational areas, with some overrepresenta-

tion of industrial workers. However, in view of the similar pattern of geographic, ethnic, and sociocultural factors in these groups, we consider that the study population constitutes a reasonably representative sample of healthy nonsmoking Nicaraguan male workers.

In the analysis, age and height showed a considerable significant effect on the pulmonary variables, as in most other studies [Kory et al., 1961; Berglund et al.. 1963; Ferris et al., 1965; Knudson et al., 1983; Morris et al., 1988; Coul- tas et al., 19881.

In the data analysis, we tried to obtain reference equations that could simultaneously fulfill two somewhat con- flicting criteria: that of simplicity in the equations and that of explaining the nonlinear relationship of FVC and FEV, with age, especially the shift in the slope indicating growth or very slow decline in young men, and sharper decline at higher ages. Linear, quadratic, and multiphase statistical models were tested, which complicated the statistical treat- ment of the data. The best predicted values were obtained by using two linear equations derived from the rnultiphase model, in effect a two-phase model.

The main differences between the predicted and the

46 Quintero et al.

TABLE IV. Fifth Percentiles From the Distribution of (Observed/Predicted) x 100 for FVC and FEV,, and From the Distribution of Predicted FEV,% in Various Age Intervals and From Three Different Studies

Obslpredicted Present study Age interval (yr) FVC (Yo) Obslpredicted FEV, (YO) Predicted FEY,%

16-24 (n = 43) 83.0 25-34 (n = 102) 82.5 3544 (n = 44) 82.7 45-58 (n = 25) 78.9

81.4 80.6 81.7 75.7

86.5 83.9 80.7 77.0

Present study Knudson

Obslpredicted Obs/predicted Obdpredicted Obs/predicted Age interval (yr) FVC FEV, FVC FEV,

16-24 (n = 43) 83.0 81.4 79.0 81.2 25-39 (n = 132) 83.1 80.7 81.1 79.1 4c-58 (n = 39) 80.7 77.3 73.4 77.2

Present study Coultas

Obs/predicted Obslpredicted Obs/pred icted Obs/predicted Age interval (yr) FVC FEY, FVC FEV,

16-18 (n = 11) 82.8 88.5 82.3 82.8 19-24 (n = 32) 82.7 79.3 (62.2)” (80.9)a 25-58 (n = 171) 81.9 80.7 82.1 79.0

‘These values are based on a linear interpolation of neighboring values, as no values were given in the original reference.

TABLE V. Percentage of Individuals of the Present Study Group (n = 214), Classified Below the Lower Fifth Percentile Value, Using Limit Values of Three Different Studies

Study FVC (Yo) FEV, (Yo)

Present study Knudson et al. [I9831 Coultas el al. [I9881

4.2 2.3 5.1

4.2 2.8 2.8

observed values were seen at the lower and higher ends of the age range, and it was the simple linear model that failed in this area. The quadratic model leads to a somewhat better fit close to the breakpoint, whereas the two-phase model must make a transition from one linear form to the other. However, the quadratic model was not consistent with the linear relationship observed in the higher age groups. Our concern with the predictions in the age extremes was the main reason for choosing the two-phase model. This model also provides a continuous sequence of predicted values without discontinuities for sequential age groups.

Regarding the simplicity of the data analysis, the multiphase model causes an estimation problem, since i t is a

nonlinear model. However, once the estimation has been done, the model can be interpreted and used as two linear equations. This makes the model suitable for use in the field. As an additional aid for field work, tables with the predicted values for different combinations of age and height, including the fifth percentile to define the lower liniit of normality as recommended by the American Tho- racic Society [ 199 I ] , have been prepared.

For this study population, we recommend the use of the fifth percentile as the lower liniit of normality, since this measure is not dependent on the distributional assumptions. That does not imply that the assumption of a gaussian distribution for the spironietric indices is rejected, i t is simply not fully justified. Tables I and I1 present data regarding the standard deviations (SD) and the standard error of the estimate (SEE) for those who still prefer to use the lower limit of normality based on these quantities. We do not recommend the use of a fixed percentage such as 80% of the predicted value.

In the analysis of FEV,%, the linear equation showed satisfactory results, and no alternative formulation was considered.

The nonlinear relationship between FVC and FEV, with age has also been described by Berglund et al. [ 19631,


Knudson et al. [ 19831, and Coultas et al. [ 19881. However, these investigators treated age in a different way in formu- lating and evaluating the models. In the equations we have chosen as external references, all but the Knudson and Coultas equations are linear in age and height. For adult males. Knudson stratified the subjects into two age groups: below and above 25 years of age. In each age group, a separate equation using age and height as explanatory variables was fitted. Coultas et al. stratified the analysis into three age groups: that is, 6-18 years of age. 19-24 years of age, and 25 years of age and above. For the age group over 25 years, linear equations in age and height have been used. For the age group 6-18 years, a linear equation using the logarithmic value of the spirometric measurement and the logarithmic value of height has been used. In the age interval 19-24 years. no separate equations have been formed because of the small number of subjects. As an alternative to regression equations, a linear interpolation between the predicted values for 18 years of age and for 25 years of age is recommended. This is the approach we have used for calculating predicted values and for determining approxi- mate 5% limits for the Coultas equations. Of course this is a somewhat arbitrary approach for the application of the Coultas equations in a working population in the present age interval.

The breakpoint in our equations is higher than those reported by both Knudson and Coultas. It is not clear what criteria Knudson and Coultas used for determining the breakpoint. In our case, the breakpoint was the result of the application and estimation of a specific model. The resulting multiphase model seems not to give the steep decline with age shown by all external reference equations. Also. as a mathematical property of the chosen model, the multiphase model gives a continuous shift in the predicted values at and around the breakpoint. This will not be the case if two linear equations are fitted separately in two strata.

The different regression equations analyzed in this study showed both small and large dissimilarities with re- spect to the regression coefficients. Large dissimilarities were found for the Knudson equations whose parameters deviate from all other equations. They are numerically the largest parameters indicating a greater impact on the spirometric functions based on a one-unit increase in the explanatory variables. The multiphase model developed in this study is also exceptional because, in contrast to all other equations but Knudson’s, it allows for a shift in the slope at a certain age. As a concluding remark, we have found that both the age and height coefficients of the external equations are somewhat larger (numerically) than the values obtained by the multiphase model developed in this study. This indicates that the influence of age and height on the observed values for FVC and FEV, in the population of male Nicaraguan workers seem to be less than the predicted

influence by the external reference equations, at least in the age and height interval studied.

Some differences are also observed in the intercepts, with the large values of the Knudson equations as extremes. The Nicaraguan equations on the other hand have smaller intercepts, numerically. Since these parameters can be considered as the “baseline level” of the spirometric values they may be interpreted as representing racial differences, as discussed by Neeraj et al. [1990].

The comparison should not only consider the values of the coefficients and the intercepts. An important point for practical work is the ability of the equation to produce rea- sonable values for the ratio of observed/predicted spirometric index. The distribution of this value is used also to estimate the lower point of normality.

In our study population, the results for the external reference equations showed that the effect of age is not always well accounted for. For the older Nicaraguan male workers, lower than expected spirometric indices were predicted, resulting in high values for the observed/predicted estimate. For younger workers, the tendency was in the opposite direction. High values for the ratio observed/predicted might lead to an increased risk of false negative results as Table V has shown. They may also, as a conse- quence, lead to a decreased risk of false positive results. It is the risk of false negatives that are of the highest concern, and should ideally be minimized, in the screening of an exposed population. Also, shorter Nicaraguan male workers are predicted, by the external reference equations, to have comparably lower values than the tallest group. The latter observation could be explained by the fact that the external reference equations have been developed in populations where the mean height is higher than in the study population in Nicaragua.

Although a deeper discussion on this matter is beyond our aims, it should be pointed out that this could summarize important anthropometric differences among the study populations. In addition, our results, for both FVC and FEV,, as concerns the age and height coefficients. are very similar to those found by Restrepo et a]. [1988], in a sample of 405 Colombian workers with almost the same age and height distribution as in our study population.

The results of this study support the need for specific reference equations for male Nicaraguan workers, and per- haps for other Latin American populations, formulated to account for particular racial, environmental, social, eco- nomic, and other factors.

CONCLUSION

This study constitutes the first attempt to establish reference spirometric standards for male Central American workers (nonsmokers). Reference equations for FVC, FEV,, and FEV,% have been established from a sample of

48 Quintero e t al.

hcalthy Nicaraguan male workers; the tables present practical field work with the lower limit of normality based on the fifth percentile.

Differences between predicted values obtained from previously used reference equations and the values observed in our study population have been found. This result could he due to differences in populations concerning racial, genetic, nutritional, geographical, occupational, and sociocultural aspects [American Thoracic Society, 19911. Therefore, Nicaraguan equations are recommended to evaluate Nica- raguan workers. However, it remains to be determined whether these conclusions can be extrapolated to the general Nicaraguan population, or to other Latin American populations.

ACKNOWLEDGMENTS

The authors are grateful for the cooperation of the research teams in the source surveys, Drs. Aurora Aragon, Ntstor Castro, Edgard Delgado, and Douglas Vargas. We thank Professor Christer Hogstedt and Drs. Rob McConnell and ke Thorn for their support in different aspects of the study, to Professor Per Malmberg, Drs. Bengt Sjogren, Per Gustavsson, and Ingvar Lundberg, for their comments on the manuscript. We also thank the Swedish Agency for Research Cooperation with Developing Countries (SAREC) for its financial support.

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Reference spirometric values in healthy Nicaraguan male workers

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