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Body Composition Evaluation using Bioelectrical Impedance and its Impact on Academic Performance of Nursing Students
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Body Composition Evaluation using Bioelectrical Impedance and its Impact on Academic Performance of Nursing Students
Journal
ECTM 2023 - 2023 IEEE 7th Ecuador Technical Chapters Meeting
Date Issued
2023
Author(s)
Romero Riaño, Paola
Facultad de Ciencias de la Salud y Bienestar Humano
Camaño Carball, Lilian
Facultad de Ciencias de la Salud y Bienestar Humano
Yánez-Rueda H.
Buele, Jorge
Facultad de Ingenierías
Type
Conference Paper
DOI
10.1109/ETCM58927.2023.10309027
URL
https://cris.indoamerica.edu.ec/handle/123456789/8301
Abstract
In the past, nutritional assessment relied on manual measurements that did not allow for the differentiation of body composition components. With technological advancements, the introduction of bioelectrical impedance has provided a more specific approach to obtaining results. This study aims to utilize this innovative method to assess the connection between body composition and academic performance in nursing students. The research focused on a representative sample of 89 participants, utilizing bioelectrical impedance to measure the primary bioelements of the human body. Strong and significant correlations were observed between height and weight, height and muscle mass, and muscle mass and weight. A moderate correlation was found between weight and fat, as well as significant weak correlations between age and fat, and between fat and body mass index. Additionally, a significant weak negative correlation was observed between height and fat. Of the participants, 42.2% of women and 48% of men were classified as overweight. However, the statistical analysis did not reveal significant correlations between academic performance and variables such as weight, muscle mass, fat, and body mass index. Based on this information, it was concluded that most students had a body mass index within the normal range, and no direct relationship between body composition and academic performance was identified. Continuous monitoring of overweight students using this technology is recommended to promote healthy nutritional practices. © 2023 IEEE.
Subjects
Brownian model; credi...
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Acquisition Date
Dec 6, 2024
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