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Article citations


Kumara, D.M.A. and Perera, H. (2009) Evaluation of Six Commonly Used Formulae for Sonographic Estimation of Fetel Weight in a Srilankan Population. SriLanka Journal of Obstetrics and Gynaecology, 31, 20-33.

has been cited by the following article:

  • TITLE: Statistical Analysis of Variables Influencing Type of Birth in Sri Lanka: A Logistic Regression Approach

    AUTHORS: H. P. R. R. Pathirana, N. Varathan

    KEYWORDS: Caesarean, Logistic Regression, Type of Birth, Odds Ratio, Chi-Square Test

    JOURNAL NAME: Open Journal of Statistics, Vol.8 No.2, April 13, 2018

    ABSTRACT: Caesarean is a major surgical procedure undertaken in obstetrics and its rate is increasing in Sri Lanka as well as in the world. In Sri Lanka, health statistics show an increase in caesarean rates from 13.3% in 1998 to 30.6% by 2007. Due to its potential serious risks and the burden on the health system, many authorities have recommended reducing the caesarean rate for many years. This motivated us to study the most influential variables on the type of birth in Sri Lanka. In this study, based on the Anuradhapura Teaching Hospital records, entire 805 new born babies’ birth information was considered during the month of May, 2015. The variable “Type of Birth” (Normal/Caesarean) was considered as a binary response variable and age, height, weight of mother and sex, weight, length, shoulder length, head circumference of the baby were treated as explanatory variables. Logistic regression was used to model the data and using stepwise regression; mother’s age, height and weight were identified as the most influential variables on the type of birth. Further, it was observed that the odds of having normal birth is 80% higher for woman who belongs to the age group less than or equal to 30 years compared to woman who belongs to the age group greater than 30 years. Moreover, the Hosmer-Lemeshow goodness of fit test was used to check the adequacy of the fitted model. Results from this study revealed that in future, the type of birth may be predicted by considering these identified influential variables.