Details
Category: Volume 06 Issue 03 March 2018
Hits: 1225

Title: Preference of Multivariate Analysis over Univariate Analysis in Lung Function Studies

Authors: Dr Kalavathi Lakshmipathy, Dr Ghansham Sharma, Mrs. Swetha B. Lingutla

 DOI:  https://dx.doi.org/10.18535/jmscr/v6i3.50

Abstract

Multiple dependent and independent variables affect lung function tests. Hence univariate analysis is not appropriate.  The main objectives of the study were to show the appropriateness of multivariate analysis for these types of studies, to know the exact quantification effects of factors on study variables and to study the interaction effects of factors. Eighty individuals between 29-59 years formed the study group. Using computerized spirometer, 3 study variables - Forced Expiratory Volume in 1st sec / Forced Vital Capacity , Forced Expiratory Flow rate 25-75% and Peak Expiratory Flow Rate, were determined and correlated to 3 factors - age, gender and height.   Seven Models were formulated by different combinations of factors. Each Model was analysed by Multivariate analysis of Variance (MANOVA) which resulted Wilks’ Lamda (λ),  Univariate ANOVA with full Factorial Experiments (2n) and  K-matrix with Bonferoni’s confidence interval. Geometric Mean was calculated from partial values. This methodology is superior and exact compared to univariate analysis. Overall contribution of age in influencing study variables simultaneously is 67.4%, gender 88.3%, height 63.2%, age-gender 30.9%, age-height 28.2% and gender-height 31.5%.   This effect quantification information is not available in literature as their analysis was by univariate analysis. All main effects and second order interaction effects of factors are significantly influencing study variables. It is concluded that multivariate analysis is preferred over univariate analysis in lung function studies.

Keywords: Wilks Lamda, MANOVA, K -matrix, partial .

References

  1. Spriggs E. A., Gandevia B. and Bishop P. J. John Hutchinson (1811-1861) Inventor of the Spirometer. Proceedings of Royal  Society of  1976; 69(6): 450–450.
  2. Dikshit M. B., Raje S. and Agrawal J. Lung functions with spirometry: An indian Perspective-1. Peak Expiratory Flow Rates. Indian Journal of Physiology and Pharmacology. 2005a; 49(1): 8–18.
  3. Dikshit M. B., Raje S. and  Agrawal M. J. Lung functions with spirometry: An indian Perspective-1I. Vital Capacity of Indians. Indian Journal of Physiology and Pharmacology. 2005b 49(3): 257–270.
  4. Tsukioka K., Makino S., Miyamoto T., Tanabe N. and  Akazawa K. Peak Expiratory flow in normal healthy Japanese adults: Comparisons with values reported in other races. Allergology international. 2002; 51: 101–111.
  5. Vijayan V. K., Kuppurao K. V., Venkatesan P., Sankaran K. and Prabhakar R. Pulmonary functions in healthy young adult Indians in Madras. 1990; 45: 611–615.
  6. Udwadia F., Sunavala J. D., Shetye M. and Jain P. K. The maximal flow volume curve in normal subjects in India. 1986; 89: 852–857.
  7. Williams D. E., Miller D. R. and Taylor F. W. Pulmonary function studies in healthy Pakistani adults. Thorax. 1978; 33: 243-249.
  8. Dacosta J. L. Pulmonary function studies in healthy chinese adults in Singapore. American Review Respiratory Disease. 1971; 104: 128–31.
  9. Jain S. K. and Guptha C. K. Lung function studies in healthy men and women over forty. Indian Journal of Medical  1967; 55: 612–619.
  10. Verma S. S., Sharma Y. K. and Arora S. A. Multivariate study of some lung function tests at different age groups in healthy Indian males. Indian Journal of  Chest Diseases and  Allied Sciences. 2002; 44: 85–90.
  11. Fernandez G. C. J.Residual analysis and Data Transformations: Important Tools in Statistical Analysis. Horticultural Science. 1992; 27(4): 297–300.
  12. Society, The Americal Thoracic, O. statement of the American Thoracic Society. (1991). Lung Function Testing: Selection of Reference Values and Interpretative Strategies. American Review Respiatory Disease.1991;144: 1202–18.
  13. Xu X., Laird N., Dockery D. W., Schouten J. P., Rijcken B. and Weiss S. T. Age, period and cohort effects on pulmonary function in a 24 year longitudinal study. American Journal of  1995;141: 554–66.
  14. Glindmeyer H .W., Diem J. E., Jones R. N. and Weill H. Noncomparability of longitudinally and cross-sectionally determined annual change in spirometry. American Review of Respiratory Disease. 1982; 125: 544–8.
  15. Chhabra S. K., Kumar R., Gupta U., Rahan M. and Dash J. D. Prediction Equations for Spirometry in Adults from Northern India.  Indian Journal of Chest Disease and Allied Journal Sciences. 2014; 56: 221–229.
  16. Dasgupta A., Dhar R., Ghoshal A. G.,  Kundu S.,  Mukherjee S.,  Mukhopadhyay A. and  Roychowdhury S. Reference equation for spirometry interpretation for Eastern India.  Lung India. 2015; 32(1): 34–39.
  17. Meguro O. T. Discriminant analysis of pulmonary function parameters – mild asthmatics versus moderate asthamatics. Acta Medica Okayama. 1983; 37(1): 51–58.
  18. Meguro T.Selection of effective maximal expiratory parameters to differentiate asthmatic patients from healthy adults by discriminant analysis using all possible selection procedure. Acta Medica Okayama. 1986; 40(4): 215–23.
  19. Meguro O. T. and Tsubota N. (1978). Discriminant analysis of bronchial asthma by linear discriminant function with parameters of flow-volumes: discriminant analysis of bronchial asthma in young male non-smokers. Acta Medica Okayama. 1978; 32(5): 355–361.

Corresponding Author

Dr Kalavathi Lakshmipathy

MD (Physiology), Director – Professor, Department of Physiology,

ESIC Medical College & Post Graduate Institute of Medical Sciences & Research,

Rajajinagar, Bangalore-560010, Karnataka, India.

Landline:  +91 080 23125572 (Dean), +91 080 23003604 (Chamber)

Mobile No: (+91) 9448259303, Email: This email address is being protected from spambots. You need JavaScript enabled to view it.