Abstract
Exclusive breastfeeding (EBF) is affected by multiple risk factors. Therefore, it is difficult for clinical professionals to identify women who will not practice EBF well and provide subsequent medical suggestions and treatments. This study aimed to apply a decision tree (DT) model to predict EBF at two months postpartum. The socio-demographic, clinical and breastfeeding parameters of 1,141 breastfeeding women from Nanjing were evaluated. Decision tree modelling was used to analyse and screen EBF factors and establish a risk assessment model of EBF. The Chinese version of the Breastfeeding Self-Efficacy Scale (CV-BSES) score, early formula supplementation, abnormal nipples, mastitis, neonatal jaundice, cracked or sore nipples and intended duration of breastfeeding were significant risk factors associated with EBF in the DT model. The accuracy, sensitivity and specificity of the DT model were 73.1%, 75.5% and 66.3%, respectively. The DT model showed similar or better performance than the logistic regression model in assessing the risk of early cessation of EBF before two months postpartum. The DT model has potential for application in clinical practice and identifies high-risk subpopulations that need specific prevention.
Highlights
Breast milk is the safest and most nutritious food for infants[1]
The computer-generated model is graphically represented as a tree structure that is easy to interpret and use in clinical settings compared with the OR values of the logistic regression (LR) model[25]
The aim of this study was to investigate the risk factors involved in the early cessation of exclusive breastfeeding (EBF) and construct a prediction model based on a decision tree (DT) model that can provide a tool and improve clinical professionals’ ability to identify women at risk for discontinuing breastfeeding before two months postpartum
Summary
Breast milk is the safest and most nutritious food for infants[1]. Exclusive breastfeeding during the first six months, as well as the continuation of breastfeeding with additional food for two years or longer, is recommended by the World Health Organization (WHO) and United Nations Children’s Fund (UNICEF)[1,2]. The maternal benefits of breastfeeding include a more rapid return of postpartum uterine tone, postpartum weight loss, delayed resumption of menses, and decreased risks of breast, ovarian, and endometrial cancers[3,4,5,6]. Despite the proven benefits of exclusive breastfeeding, many mothers cease the practice prematurely. All of the breastfeeding factors are variable due to culture and perinatal period differences. It is difficult for clinical nurses and breastfeeding professionals to identify women who will not practice exclusive breastfeeding well and provide effective interventions. The decision tree can be used to transform a complex decision process based on the influences of different factors into a series of simple decisions[23]. The computer-generated model is graphically represented as a tree structure that is easy to interpret and use in clinical settings compared with the OR values of the logistic regression (LR) model[25]
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