Maternal Infectious Diseases, Antimicrobial Therapy or Immunizations: Very few Contraindications to Breastfeeding

MacDonald, Noni E.

doi:10.1155/2006/801563

Cited by 6 publications

(1 citation statement)

References 10 publications

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“…The addition of water is also a possible pathway of contamination that might bring parasites like Cryptosporidum parvum , viruses like norovirus, and bacteria like Pseudomonas aeruginosa , Aeromonas spp., Salmonella spp., Campylobacter spp., and Escherichia coli O:157 . Neither is BM a sterile product and can contain on the one hand adverse bacteria: Escherichia coli and Staphylococcus aureus , as well as Brucella , Listeria monocytogenes , Streptococci , Salmonella , and Coxiella burnetti . On the other hand, BM is a source of pre‐/probiotics that have been associated with beneficial health effect and that are now included in some PIF formulations, intending to reproduce BM composition.…”

Section: Introductionmentioning

confidence: 99%

Development and Application of a Probabilistic Risk–Benefit Assessment Model for Infant Feeding Integrating Microbiological, Nutritional, and Chemical Components

et al. 2017

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A probabilistic and interdisciplinary risk-benefit assessment (RBA) model integrating microbiological, nutritional, and chemical components was developed for infant milk, with the objective of predicting the health impact of different scenarios of consumption. Infant feeding is a particular concern of interest in RBA as breast milk and powder infant formula have both been associated with risks and benefits related to chemicals, bacteria, and nutrients, hence the model considers these three facets. Cronobacter sakazakii, dioxin-like polychlorinated biphenyls (dl-PCB), and docosahexaenoic acid (DHA) were three risk/benefit factors selected as key issues in microbiology, chemistry, and nutrition, respectively. The present model was probabilistic with variability and uncertainty separated using a second-order Monte Carlo simulation process. In this study, advantages and limitations of undertaking probabilistic and interdisciplinary RBA are discussed. In particular, the probabilistic technique was found to be powerful in dealing with missing data and to translate assumptions into quantitative inputs while taking uncertainty into account. In addition, separation of variability and uncertainty strengthened the interpretation of the model outputs by enabling better consideration and distinction of natural heterogeneity from lack of knowledge. Interdisciplinary RBA is necessary to give more structured conclusions and avoid contradictory messages to policymakers and also to consumers, leading to more decisive food recommendations. This assessment provides a conceptual development of the RBA methodology and is a robust basis on which to build upon.

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