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Risk Factors Predicting Infectious Lactational Mastitis: Decision Tree Approach versus Logistic Regression Analysis

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Abstract

Objectives Lactational mastitis frequently leads to a premature abandonment of breastfeeding; its development has been associated with several risk factors. This study aims to use a decision tree (DT) approach to establish the main risk factors involved in mastitis and to compare its performance for predicting this condition with a stepwise logistic regression (LR) model. Methods Data from 368 cases (breastfeeding women with mastitis) and 148 controls were collected by a questionnaire about risk factors related to medical history of mother and infant, pregnancy, delivery, postpartum, and breastfeeding practices. The performance of the DT and LR analyses was compared using the area under the receiver operating characteristic (ROC) curve. Sensitivity, specificity and accuracy of both models were calculated. Results Cracked nipples, antibiotics and antifungal drugs during breastfeeding, infant age, breast pumps, familial history of mastitis and throat infection were significant risk factors associated with mastitis in both analyses. Bottle-feeding and milk supply were related to mastitis for certain subgroups in the DT model. The areas under the ROC curves were similar for LR and DT models (0.870 and 0.835, respectively). The LR model had better classification accuracy and sensitivity than the DT model, but the last one presented better specificity at the optimal threshold of each curve. Conclusions The DT and LR models constitute useful and complementary analytical tools to assess the risk of lactational infectious mastitis. The DT approach identifies high-risk subpopulations that need specific mastitis prevention programs and, therefore, it could be used to make the most of public health resources.

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Acknowledgments

We thank all the women, midwives, lactation consultants and medical practitioners who kindly participated in this study. This work was supported by CSD2007-00063 (FUN-C-FOOD, Consolider-Ingenio 2010) and AGL2010-15420 projects from the Ministerio de Ciencia e Innovación (Spain).

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Authors and Affiliations

  1. Departamento de Nutrición, Bromatología y Tecnología de los Alimentos, Universidad Complutense de Madrid, Ciudad Universitaria, Avda. Puerta de Hierro, s/n, 28040, Madrid, Spain

    Leónides Fernández, Pilar Mediano, Juan M. Rodríguez & María Marín

  2. Computing Services, Research Support, Universidad Complutense de Madrid, Madrid, Spain

    Ricardo García

Authors
  1. Leónides Fernández
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  2. Pilar Mediano
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  3. Ricardo García
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  4. Juan M. Rodríguez
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  5. María Marín
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Correspondence to María Marín.

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Fernández, L., Mediano, P., García, R. et al. Risk Factors Predicting Infectious Lactational Mastitis: Decision Tree Approach versus Logistic Regression Analysis. Matern Child Health J 20, 1895–1903 (2016). https://doi.org/10.1007/s10995-016-2000-6

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  • DOI: https://doi.org/10.1007/s10995-016-2000-6

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