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Information about Data DOI: 10.5281/zenodo.6581038 September 8, 2022 Hello, and thanks for your interest in this data set. This file contains the data utilized for a journal manuscript, "Variation of human milk lactoferrin in relation to maternal-infant infection status among dyads from northern Kenya" by Nerli Paredes Ruvalcaba, Amelia N Odo, and Masako Fujita, under review for publication. Data are found under the Data tab, and the variable coding information under the Code tab. The data are for the concentrations of lactoferrin in mothers' milk and reported illnesses among 83 mother-infant dyads in Ariaal communities of northern Kenya. This is a subset of data on milk lactoferrin, characterized in the Biomarker Laboratory for Anthropological Research at Michigan State University in 2019, using cryogenically archived milk specimens. The milk specimens and other data on maternal and infant characteristics, including illness recalls, were originally collected in research among 241 mother-infant dyads by Masako Fujita in 2006 in collaboration with the Center for Public Health Research of Kenya Medical Research Institute (KEMRI) under approvals by the institutional review boards of the University of Washington and KEMRI. Please contact Fujita (masakof@msu.edu) for questions regarding the data. If you decide to use the data, please cite this file's DOI 10.5281/zenodo.6581038 and the above-mentioned manuscript upon publication, and acknowledge the following parties for grant support: National Science Foundation (BCS-0622358, BCS-1638167); Wenner-Gren Foundation (Gr. 7460, Gr. 9278); Provost Undergraduate Research Initiative Grant, Michigan State University; and African Futures Research Leadership Program of the Alliances for African Partnership, Michigan State University Thanks, Masako Fujita Masako Fujita, Associate Professor of Anthropology Michigan State University ORCID: 0000-0001-9173-6678 Emaiil: masakof@msu.edu
morbidity, lactaion, milk immune components, infection
morbidity, lactaion, milk immune components, infection
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