The results of ventilatory function tests (FVC, FEV1, and FEV %) depend to a great extent on age and height. In epidemiological investigations, the main purpose of which is to analyse the influence of environmental factors on lung function in the population, it is therefore necessary to use multiple regression methods. This form of statistical analysis is difficult and laborious when there is no access to a computer. An alternative method is to use indices of ventilatory function that adjust

more »

... age and height. Khosla (1971) has recently developed a series of such indices. These indices show a high correlation with ventilatory tests and are independent of age and height. The main purpose of our work was to test the value of these new indices on material from our own epidemiological studies of chronic non-specific chest disease carried out in two small industrial enterprises in Krakow, taking into account the possible anthropological differences between the British and Polish populations. MATERIAL AND METHODS The epidemiological studies which have been described in detail elsewhere (Sawicki, 1971) were carried out in two occupational groups, A (drivers) and B (workers of a chemical factory), using questionnaires slightly modified and translated from the English Medical Research Council questionnaire. Chronic cough and chronic phlegm were defined as chronic bronchitis. Spirometric tests were carried out on each person and simple anthropometric features such as standing height, sitting height, and weight, were measured. The subjects were asked to blow into a Vitalograph spirometer five times, and FVC, FEV1, and FEYV%, adjusted to BTPS, were calculated from the highest spirogram. Calculations were made of the Khosla indices and of predicted FVC, FEV1, and FEV % values for *Index for FEV1 = FEV, * Age i, for FVC = FVC * Age i and Ht2 Ht2 for FEV % = FEV% * Age A each person by multiple regression analysis. As we came to the conclusion that the regression was linear we used the following equations: FVC = a1 age+b, height+cl FEV1 = a2 age+b2 height+c2 FEV% = a3 age+c3 All calculations were carried out on the Polish computer ODRA 1204 and the program was written in ALGOL-1204. The first step of the analysis showed that the distributions of the new indices were perfectly normal. Table I shows basic data concerning the examined populations, and Table lI the results of the ventilatory function tests transformed into Khosla indices. As is evident from Table II , the indices were lower for bronchitics than for non-bronchitics in both populations but especially in factory B, where the workers were exposed to a dusty environment.