Download PDF
Methods Inf Med 1985; 24(02): 91-100
DOI: 10.1055/s-0038-1635359
Original Article
Schattauer GmbH

Analysis of Maximum Expiratory Flow Volume Curves Using Canonical Correlation Analysis[*]

Analyse der maximalen exspiratorischen Fluß-Volumen-Kurve mittels der kanonischen Korrelationsanalyse
W. van Pelt
1   (From the Departments of Physiology and Physiological Physics and of Data Theory, the University of Leiden, and the Department of Epidemiology, the University of Groningen, The Netherlands)
,
Ph. H. Quanjer
1   (From the Departments of Physiology and Physiological Physics and of Data Theory, the University of Leiden, and the Department of Epidemiology, the University of Groningen, The Netherlands)
,
M. E. Wise
1   (From the Departments of Physiology and Physiological Physics and of Data Theory, the University of Leiden, and the Department of Epidemiology, the University of Groningen, The Netherlands)
,
E. van der Burg
1   (From the Departments of Physiology and Physiological Physics and of Data Theory, the University of Leiden, and the Department of Epidemiology, the University of Groningen, The Netherlands)
,
R. van der Lende
1   (From the Departments of Physiology and Physiological Physics and of Data Theory, the University of Leiden, and the Department of Epidemiology, the University of Groningen, The Netherlands)
› Author Affiliations
Further Information

Publication History

Publication Date:
20 February 2018 (online)

    Permissions and Reprints

Summary

As part of a population study on chronic lung disease in the Netherlands, an investigation is made of the relationship of both age and sex with indices describing the maximum expiratory flow-volume (MEFV) curve. To determine the relationship, non-linear canonical correlation was used as realized in the computer program CANALS, a combination of ordinary canonical correlation analysis (CCA) and non-linear transformations of the variables. This method enhances the generality of the relationship to be found and has the advantage of showing the relative importance of categories or ranges within a variable with respect to that relationship. The above is exemplified by describing the relationship of age and sex with variables concerning respiratory symptoms and smoking habits. The analysis of age and sex with MEFV curve indices shows that non-linear canonical correlation analysis is an efficient tool in analysing size and shape of the MEFV curve and can be used to derive parameters concerning the whole curve.

Als Teil einer Bevölkerungsstudie über chronische Lungenkrankheiten in den Niederlanden wird die Beziehung zwischen Alter und Geschlecht einerseits und den die Kurve des maximalen exspiratorischen Fluß-Volumens (MEFV) beschreibenden Meßwerten andererseits untersucht.

Zur Bestimmung dieser Beziehung wurde die nichtlineare kanonische Korrelation verwendet, wie sie im Computerprogramm CANALS vorliegt: Eine Kombination der gewöhnlichen kanonischen Korrelationsanalyse (CCA) mit nichtlinearen Transformationen der Variablen. Diese Methode erhöht die Allgemeingültigkeit der festzustellenden Beziehung und hat den Vorteil, die relative Bedeutung von Kategorien oder Rängen innerhalb einer Variablen hinsichtlich dieser Beziehung aufzuzeigen.

Die obige Methode wird zur Beschreibung der Beziehungen zwischen Alter und Geschlecht einerseits und den die Atmungssymptome und Rauchgewohnheiten betreffenden Variablen andererseits angewandt. Die Analyse von Alter und Geschlecht mit den MEFV-Kurvenmeß-werten zeigt, daß die nichtlineare kanonische Korrelationsanalyse ein wirksames Werkzeug zur Analyse der Größe und Form der MEFV-Kurve darstellt und zur Ableitung von Parametern in bezug auf die gesamte Kurve benutzt werden kann.

Key-Words:

MEFV Curve - Curve Analysis - Canonical Correlation Analysis - Non-linear Transformations

Schlüssel-Wörter:

MEFV-Kurve - Kurvenanalyse - kanonische Korrelationsanalyse - nichtlineare Transformationen

* Requests for reprints: W. van Pelt, Physiology Laboratory, P. O. Box 9604, 2300 RC Leiden, The Netherlands


 

  • REFERENCES

  • 1 Adelman I, Geier M, Morris C. T. Instruments and goals in economic development. Amer. Econ. Rev 1969; 59: 409-426.
    PubMedGoogle Scholar
  • 2 Bartlett M. S. Internal and external factor analyses. Brit. J. statist. Psychol. statist, sect 1948; 1: 73-81.
    PubMedGoogle Scholar
  • 3 Benzecri J. P. L’analyse des Données (2 vols). Paris: Denod; 1973
    Google Scholar
  • 4 Black L. F, Offord K, Hyatt R. E. Variability in the maximal expiratory flow-volume curve in asymptomatic smokers and in non-smokers. Amer. Rev. Resp. Dis HO 1974; 282-292.
    PubMedGoogle Scholar
  • 5 Burrows B, Cline M. G, Knudson R. J, Taussig L. M, Lebowitz M. D. A descriptive anaylsis of the growth and decline of FVC and FEV,. Chest 1983; 5: 717-724.
    PubMedGoogle Scholar
  • 6 Cherniack R. M, Raber M. B. Normal standards for ventilatory function using an automated wedge spirometer. Amer. Rev. Resp. Dis 1972; 106: 38-46.
    PubMedGoogle Scholar
  • 7 Colebatch H. J. H, Greaves I. A, Ng C. K. Exponential analysis of elastic recoil and aging in healthy males and females. J. appl. Physiol 1979; 47: 683-691.
    CrossrefPubMedGoogle Scholar
  • 8 Comstock G. W, Meyer M. B, Helsing K. J, Tockman M. S. Respiratory effects of household exposure to tobacco smoke and gas cooking. Amer. Rev. Resp. Dis 1981; 124: 143-148.
    PubMedGoogle Scholar
  • 9 Dawson S. V, Elliott E. A. Wave speed limitation on expiratory flow – a unifying concept. J. appl. Physiol 1977; 43: 498-515.
    CrossrefPubMedGoogle Scholar
  • 10 Dodge R. R, Burrows B. The prevalence and incidence of asthma and asthma-like symptoms in a general population sample. Amer. Rev. Resp. Dis 1980; 122: 567-574.
    PubMedGoogle Scholar
  • 11 Ferris B. G, Higgins I. T. T, Higgins M. W, Peters J. M. Chronic non specific lung disease in Berlin, New Hampshire, 1961 to 1967, a follow-up study. Amer. Rev. Resp. Dis 1973; 107: 110-122.
    PubMedGoogle Scholar
  • 12 Fletcher C. M, Elmes P. C, Fairbairn A. S, Wood C. H. The significance of respiratory symptoms and the diagnosis of chronic bronchitis in a working population. Brit. med. J. No 1959; 5147: 257-266.
    PubMedGoogle Scholar
  • 13 Fletcher C. M, Peto P, Tinker C. M, Speizer R. E. The natural history of chronic bronchitis and emphysema. London and New York: Oxford University; 1976
    Google Scholar
  • 14 Gerrard J. W, Cockcroft D. W, Mink J. T, Cotton D. J, Poonawola R, Dosman J. A. Increased non specific bronchial reactivity in cigarette smokers with normal lung function. Amer. Rev. Resp. Dis 1980; 122: 577-581.
    PubMedGoogle Scholar
  • 15 Gifi A. Non-linear multivariate analysis. Department of Data Theory, University of Leiden, The Netherla 1981 Reissued Leiden; DSWO Press. 1985
    Google Scholar
  • 16 Gifi A. Princals User’s Guide. Department of Data Theory, University of Leiden. The Netherlands: 1983
    Google Scholar
  • 17 Gittins R. Ecological application of Canonical Analysis. In. Orloci L, Rao C. R, Stiteler W. M, Fairland M. D. (Eds) Multivariate Methods in Ecological Work. International Cooperative Publishing House; 1979: 309-535.
    Google Scholar
  • 18 Green M, Mead J, Turner J. M. Variability of maximum expiratory flow-volume curves. J. appl. Physiol 1974; 37: 67-74.
    CrossrefPubMedGoogle Scholar
  • 19 Higgins M. W, Keller J. B, Metzner H. E. Smoking, socioeconomic status, and chronic respiratory disease. Amer. Rev. Resp. Dis 1977; 116: 403-410.
    PubMedGoogle Scholar
  • 20 Hoeppner V. H, Cooper D. M, Zamel N, Bryan A. C, Leisner H. Relationship between elastic recoil and closing volume in smokers and non-smokers. Amer. Rev. Respir. Dis 1974; 109: 81-86.
    PubMedGoogle Scholar
  • 21 Hotelling H. Relations between two sets of variates. Biometrika 1936; 28: 321-327.
    CrossrefPubMedGoogle Scholar
  • 22 Israels A. Z, Sikkel D. Correspondence analysis and comparisons with other techniques. Central Bureau of Statistics BPA No:. 1982: 7458-82-MI.
    Google Scholar
  • 23 Jansen J. M, Peslin R, Bohadana A. B, Racineux J. L. Usefulness of forced expiratory slope ratios for detecting mild airway abnormalities. Amer. Rev. Resp. Dis 1980; 122: 221-230.
    PubMedGoogle Scholar
  • 24 Knudson R. J, Slatin R. C, Lebowitz M. D, Burrows B. The maximal expiratory flow-volume curve. Normal standards, variability and effects of age. Amer. Rev. Resp. Dis 1976; 113: 587-600.
    PubMedGoogle Scholar
  • 25 Knudson R. J, Burrows B, Lebowitz M. D. The maximal expiratory flow-volume curve: Its use in the detection of ventilatory abnormalities in a population study. Amer. Rev. Resp. Dis 1976; 114: 871-879.
    PubMedGoogle Scholar
  • 26 Landau L. L, Tissig L. M, Macklem P. T, Beaudry P. H. Contribution of inho-mogeneity of lung units to the maximum expiratory flow-volume curve in children with asthma and cystic fibrosis. Amer. Rev. Resp. Dis 1975; 111: 725-731.
    PubMedGoogle Scholar
  • 27 Lubischew A. A. On the use of discriminant functions in taxonomy. Biometrics 1962; 18: 455-477.
    CrossrefPubMedGoogle Scholar
  • 28 Manfreda J, Nelson N, Cherniack R. M. Prevalence of respiratory abnormalities in a rural and an urban community. Amer. Rev. Respir. Dis 1978; 117: 215-226.
    PubMedGoogle Scholar
  • 29 Mardia K. V, Kent J. T, Bibby J. M. Multivariate Analysis. New York: Academic Press; 1979: 281-295.
    Google Scholar
  • 30 Mead J, Turner J. M, Macklem P. T, Little J. B. Significance of the relationship between lüng recoil and maximum expiratory flow. J. appl. Physiol 1976; 42: 95-108.
    PubMedGoogle Scholar
  • 31 Mead J. Analysis of the configuration of maximum expiratory flow-volume curves. J. appl. Physiol 1978; 44: 156-165.
    CrossrefPubMedGoogle Scholar
  • 32 Michaels R, Sigurdson M, Thurlbeck S, Cherniack R. Elastic recoil of the lung in cigarette smokers: The effect of nebulized bronchodilator and cessation of smoking. Amer. Rev. Respir. Dis 1979; 119: 707-716.
    PubMedGoogle Scholar
  • 33 Pride N. B, Permutt S, Riley R. L, Bromberger-Barnea B. Determinants of maximal expiratory flow from the lungs. J. appl. Physiol 1967; 23: 646-662.
    CrossrefPubMedGoogle Scholar
  • 34 Quanjer P. H. (Edit.) Standardized lung function testing. Report Working Party “Standardization of Lung Function Tests”, European Community for Coal and Steel, Luxembourg. Bull. Europ. Physiopath. Resp. 19 Suppl 1983; 5: 1-95.
    PubMedGoogle Scholar
  • 35 Schoenberg J. B, Beck G. J, Bouhuys A. Growth and decay of pulmonary function in healthy blacks and whites. Respir. Physiol 1978; 33: 367-313.
    CrossrefPubMedGoogle Scholar
  • 36 Tattersall S. F, Benson M. K, Hunter D, Mansell A, Pride N. B, Fletcher C. M. The use of tests of peripheral lung function for predicting future disability from airway obstruction in middle-aged smokers. Amer. Rev. Resp. Dis 1978; 118: 1035-1050.
    PubMedGoogle Scholar
  • 37 Tintner G. Some applications of multivariate analysis to economic data. J. Amer, statist. Ass 1946; 41: 472-500.
    CrossrefPubMedGoogle Scholar
  • 38 Van der Burg E. CANALS User’s Guide. Department of Data Theory. University of Leiden: The Netherlands; 1983
    Google Scholar
  • 39 Van der Burg E, De Leeuw J. Nonlinear canonical correlation. Brit. J. math, statist. Psychol 1983; 36: 54-80.
    CrossrefPubMedGoogle Scholar
  • 40 Van der Lende R, De Kroon J. P. M, Van der Meulen G. J, Tammeling G. J, Visser B. F, De Vries K, Orie N. G. M. Possible indicators of endogenous factors in the development of CNSLD. In. Orie N. G. M, van der Lende R. (Eds) Bronchitis III Assen: Royal Van Gorcum; 1970: 52-70.
    Google Scholar
  • 41 Van der Lende R, Orie N. G. M. The MRC-ECCS questionnaire on respiratory symptoms. Use in epidemiology. Scand. J. resp. Dis 1972; 53: 218-226.
    PubMedGoogle Scholar
  • 42 Van der Lende R, Visser B. F, Wever-Hess J, Tammeling G. J, De Vries K, Orie N. G. M. Epidemiological investigations in the Netherlands into the influence of smoking and atmospheric pollution on respiratory symptoms and lung function disturbances. Pneumologie 1973; 149: 119-126.
    CrossrefPubMedGoogle Scholar
  • 43 Van der Lende R, Kok T. J, Peset Reig R, Quanjer Ph H, Schouten J. P, Orie N. G. M. Decreases in VC and FEV] with time: indicators for effects of smoking and air pollution. Bull. Europ. Physiopath. Resp 1981; 17: 775-792.
    PubMedGoogle Scholar
  • 44 Van Hartevelt J. H, Kruyt E. W, Van Zomeren B. C. On-line bepaling van flow-volume curves. Proceedings Medisch Informatica Congress 79. Antwerpen: J. L. Willems; 1979: 229-232.
    Google Scholar
  • 45 Webster P. M, Zamel N, Bryan A. C, Kruger K. Volume dependence of instantaneous time constants derived from the maximum expiratory flow-volume curve: A new approach to the analysis of forced expiration. Amer. Rev. Resp. Dis 1978; 115: 805-810.
    PubMedGoogle Scholar
  • 46 Wood D. A, Erskine J. A. Strategies in canonical correlation with applications to behavioural data. Educ. Psychol. Measurement 1976; 36: 861-S78.
    CrossrefPubMedGoogle Scholar
  • 47 Yernault J. C, De Troyer A, Rodenstein D. Sex and age differences in intrathoracic airway mechanics in normal man. J. appl. Physiol 1979; 46: 556-564.
    CrossrefPubMedGoogle Scholar
  • 48 Young F. W. Quantitative analysis of qualitative data. Psychometrika 1981; 46: 347-388.
    CrossrefPubMedGoogle Scholar
  • 49 Young F.W, De Leeuw J, Takane Y. Regression with qualitative and quantitative variables. An alternating least squares method with optimal scaling features. Psychometrika 1976; 41: 505-529.
    CrossrefPubMedGoogle Scholar
  • 50 Zandee M, Haasnoot J. Studies in theJ uncus articulantsL. -J. acutiflorusEhrh. -J. ancepsLahorpe -J. alpinoarticulatus -Chaix aggregate. II Comparative anatomy of the panicle axis, culm and leaf. Proc. K. Ned. Acad. Wet. C 1983; 86: 275-304.
    PubMedGoogle Scholar