Consumption of Maternal Placenta in Humans and Nonhuman Mammals: Beneficial and Adverse Effects.
Daniel Mota-RojasAgustín OrihuelaAna StrappiniDina Villanueva-GarcíaFabio NapolitanoPatricia Mora-MedinaHugo Brígido Barrios-GarcíaYuridia HerreraEunice LavalleJulio Martínez-BurnesPublished in: Animals : an open access journal from MDPI (2020)
Placentophagia is a common mammalian behavior, and the first scientific study of the potential effects of human maternal placentophagia on lactation was in 1917. More recently, in the 1970s, human placentophagia was reported in North America with a trend toward increased consumption. There are different hypotheses about the women and nonhuman mammals' motivation towards placentophagia, but few have been subject to hypotheses testing. In women, the controversy continues; on the one hand, researchers attribute benefits like increased breast milk, weight gain in newborns, decreased postpartum depression and fatigue, and improved mothers' mood. In contrast, bacterial or viral infections, hormonal, or trace elements that could become toxic for both the mother and baby are reported as possible health risks. Other reports argue a lack of scientific rigor to support the self-reported benefits of placentophagia. Also, the way the placenta is prepared (raw, cooked, dehydrated, processed, or encapsulated) alters its components, and thus the desired effects. This review provides relevant information and the different hypotheses and points of view around placentophagia. However, there are still questions to be resolved, and more studies are needed to confirm or reject the data generated so far about placentophagia in humans and nonhuman mammals.
Keyphrases
- weight gain
- birth weight
- pregnancy outcomes
- endothelial cells
- polycystic ovary syndrome
- gestational age
- body mass index
- sleep quality
- pregnant women
- induced pluripotent stem cells
- magnetic resonance
- pluripotent stem cells
- bipolar disorder
- healthcare
- sars cov
- depressive symptoms
- emergency department
- type diabetes
- human health
- physical activity
- cervical cancer screening
- deep learning
- risk assessment
- health information
- computed tomography
- social media