Tropical Journal of Pharmaceutical Research

Original Research Article | OPEN ACCESS

Caesarean Risk Factors in Northern Region of Bangladesh: A Statistical Analysis

Mostafizur Rahman¹, Asma Ahmad Shariff¹ , Aziz Shafie²

¹Centre for Foundation Studies in Science; ²Department of Geography, University of Malaya, Kuala Lumpur, Malaysia.

For correspondence:- Asma Shariff Email: asma@um.edu.my

Received: 26 January 2012 Accepted: 19 August 2012 Published: 18 October 2012

Citation: Rahman M, Shariff AA, Shafie A. Caesarean Risk Factors in Northern Region of Bangladesh: A Statistical Analysis. Trop J Pharm Res 2012; 11(5):823-833 doi: 10.4314/tjpr.v11i5.17

© 2012 The authors.
This is an Open Access article that uses a funding model which does not charge readers or their institutions for access and distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0) and the Budapest Open Access Initiative (http://www.budapestopenaccessinitiative.org/read), which permit unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited..

Abstract

Purpose: To explore the measurement of a scale of caesarean (C-section) risk factors and degree of risk contribution in different health facilities and to determine a suitable graphical representation (image) of caesarean cases.

Methods: Based on seventeen indicators, a composite index was computed for each respondent and classified into three groups using Beta distribution of first kind. For the analysis of contribution of risk factors between private and public patients, principal component analysis (PCA) was also used. An attempt was made to visualise a suitable graphical representation of caesarean cases by independent component analysis (ICA).

Results: The selected risk factors were more contributory to public hospital patients than to those in private hospitals on the basis of higher estimated value of range (R = 0.134) but a higher proportion of C-section occurred in private (93.4 %) than in public hospitals (30.3 %). On the other hand, PCA showed that the contribution of selected risk factors accounts for approximately 60.0 % and 68.5 % in private and public hospitals, respectively. Furthermore, from the various graphical representation, the numbers of private patients were more interlinked by ICA but not of the other graphical representations of PCA.

Conclusion: We had expected the rate of C-section would be higher among public hospital patients than private hospital patients but the results obtained indicate the reverse. It seems that the combination of the propensity of private practice doctors to carry out C-section and the financial benefits on the part of private hospitals may be contributory factors to the caesarean section rates in private health facilities.

Keywords: Caesarean risk factors, Composite index, Principal component analysis (PCA), Independent component analysis (ICA)