Volume 9, Issue 2 (Spring 2021)                   Iran J Health Sci 2021, 9(2): 9-17 | Back to browse issues page


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Sheykholeslami A S, Behnampour N, Mohammadpour R A, Abdollahi F. Application of Survival Tree Model in Determining Affecting Factors in Breastfeeding Duration. Iran J Health Sci. 2021; 9 (2) :9-17
URL: http://jhs.mazums.ac.ir/article-1-731-en.html
Department of Biostatistics, Faculty of Health , Mohammadpour2002@yahoo.com
Abstract:   (359 Views)
Background and Purpose: Survival tree model is a nonparametric method which can be used to identify the affecting factors from a specific time to the onset of an event. In this method, the categories are selected according to the most important factors. The purpose of this study was to determine the factors affecting the duration of breastfeeding in mothers and introduce the homogeneous subgroups using a survival tree model.
Methods:  It was a historical cohort study analyzing the survival data of mothers with healthy single childbirths referring to the rural and urban health centers of Agh-Ghala County since 2011 until 2014. Data analyses and groupings of breastfeeding survival were performed using survival tree model with conditional inference algorithm in R Software. A separation criterion (SEP) confirmed the relevance of the model.
Results: Survival tree model results revealed that the type of consumed milk with the complementary nutrition, ethnicity and the time interval between current childbirth and the previous delivery were the most important factors affecting the duration of breastfeeding. The SEP's criterion was 2.082. Thus, due to the significant difference between the subgroups and the value of more than 1 for SEP criterion, the efficiency of the model was confirmed.
Conclusions: Survival tree model could be introduced as a suitable and powerful method for ranking the duration of breastfeeding rate which presents four homogeneous subgroups for analysis in addition to identifying the predictive variables.
Full-Text [PDF 648 kb]   (171 Downloads)    
Type of Study: Original Article | Subject: Biostatistics

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