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Title: EVOBREATH. Datasets for evolutionary bioenergetics research on anthropology
Authors: Mateos Cachorro, Ana
Rodríguez, Jesús
Keywords: Human energetics;Metabolic rates;Body composition;Anthropometry;Palaeolithic physical activities
Issue Date: Apr-2023
Publisher: Elsevier
Citation: Data in Brief, 2023, 47, 108955
Abstract: Human bioenergetics has been incorporated into the palaeobiology of human ancestors during the last years to broaden our understanding of Human Evolution. The hypotheses based solely on the taxonomy and phylogenetic relationships of the fossil record, cannot easily explain many of the questions about the physiology of past humans. Data on the energetics and physiology of recent humans, together with comprehensive analyses of body proportions and body composition in relation to human metabolism, are needed to understand the evolutionary constraints of hominin ecophysiology. Furthermore, specific datasets including energetic data from modern humans are required to model hominin palaeophysiology. EVOBREATH Datasets were gradually developed since 2013 to store and manage all the data obtained in the Research Programs on Experimental Energetics developed by the Palaeophisiology and Human Ecology Group and the Palaeoecology of Mammals Group of the National Research centre on Human Evolution (CENIEH, Burgos, Spain). All experimental tests were developed either in the CENIEH BioEnergy and Motion Lab (LabBioEM) or in the field, using mobile devices. Datasets include quantitative experimental data related to human anthropometry (Height, Weight, all postcranial dimensions and segments, including hands and feet, and computation of anatomical indices), body composition (fat mass, fat-free mass, muscular mass, body water), and energetics (resting metabolic rate and energetic expenditure in different physical activities, oxygen consumption (O2) and carbon dioxide (CO2) production measured breath-by-breath) obtained in multiple studies with in vivo subjects of different ages (adults, adolescents and children) and both sexes (n = 501). These datasets are useful to optimize the time-consuming process of generating experimental data and to facilitate their reuse by the scientific community. Researchers can readily employ the datasets in their own research endeavours.
ISSN: 2352-3409
DOI: 10.1016/j.dib.2023.108955
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Type: Article
Appears in Collections:Bioenergía y Análisis del Movimiento

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